EM360 Podcast: Recent Episodes
EM360
A weekly show hosted by Matt Harris, Content Producer at EM360, exploring the ever-changing world of enterprise tech. Every week a new expert walks us through a different topic in such areas as cybersecurity, data, AI, emerging tech, unified communications, and more!
Artificial intelligence has spent the last several years getting smarter on screens, recommending what to watch, drafting what to write, answering what we ask. This type of progress is now spilling out into the physical world, where machines are starting to move, sense, and adapt on their own. In this episode of Tech Transformed, host John Santaferraro, Founder and Analyst at Ferraro Consulting, talks with Prith Banerjee, Senior Vice President of Innovation at Synopsys, about what happens when AI has to obey the laws of physics instead of just the patterns in a dataset.
Banerjee brings a rare vantage point to the conversation. Before Synopsys, he led HP Labs worldwide, served as group CTO at ABB and Schneider Electric, and ran engineering simulation software company ANSYS as CTO until its acquisition by Synopsys roughly a year ago - a deal that now anchors much of what he describes as Synopsys's "silicon to systems" strategy.
The Road to Physical AIBanerjee traces AI's progress through distinct phases he's tracked across his career. It started with analytics, which was the correlation engines behind a Netflix recommendation, or the placement and routing improvements Synopsys has long applied inside its own chip design tools. Generative AI came next, giving machines the ability to produce original language, images, and video from a prompt rather than just surface existing content. Agentic AI followed close behind, handing off entire tasks, drafting a slide deck, prepping a sales call to systems that act more like assistants than tools.
Physical AI is the phase Banerjee sees unfolding now, and it's a different kind of leap. Instead of learning from words or pixels, these systems learn from real physical measurements: pressure, temperature, stress, and strain. Training that kind of intelligence takes synthetic data generated across structural, fluid, and electromagnetic physics precisely the simulation capability ANSYS brought into Synopsys.
Teaching Robots to Learn Like HumansThe shift shows up clearly in how robots are built today. A decade ago, getting a robotic arm to pick up a bottle without crushing it meant writing enormous programs, sometimes 100,000 lines of code specifying exactly how each motor should move. Physical AI throws that playbook out. Banerjee compares it to teaching a child to ride a bike: nobody narrates which pedal to push. The child watches, tries, falls, and adjusts.
Robots now learn the same way, refining their behaviour through reward and penalty as they attempt a task thousands of times. Autonomous vehicles follow the identical pattern at far greater scale, learning from millions of hours of driving footage until they recognise, for instance, that a pedestrian stepping into the street means stop. Synopsys works with autonomous vehicle and robotics companies to generate the synthetic training data that makes this kind of learning possible without requiring endless real-world testing.
Engineering the Intelligent Systems of TomorrowThat intelligence has to run on something, and the conversation turns to what it takes to build the silicon underneath it. Chips that once held a few hundred thousand transistors now carry tens or hundreds of billions, some approaching trillions, stacked using advanced 3D and chiplet techniques. Designing them means balancing power, performance, and thermal limits simultaneously rather than simply over-engineering for safety margin, which Banerjee calls co-design.
Synopsys is tackling that complexity with what it calls agent engineers. AI systems introduced at its Converge conference that work alongside human chip designers on tasks like RTL design, test benches, and sign-off, effectively multiplying engineering capacity without multiplying headcount. The same pressure shows up at the edge, where trained AI models have to run inside a drone, car, or warehouse robot on a fraction of the power a data centre would use, with no room for cloud latency. Banerjee shares his perspective on why many AI projects struggle. He argues that the real challenge lies in balancing innovation with trust: robots operating alongside people raise questions of safety and collaboration, while autonomous systems connected to networks demand security, traceability, and clear explanations for the decisions they make.
His advice to engineering leaders is to treat this shift as organisation-wide rather than a single team's problem, from legal and marketing functions already using agentic tools to engineering teams rethinking how code gets written. The goal, as he puts it, isn't replacing people but making them capable of far more than they could manage alone. If you would find out more about this, visit Synopsys or follow Prith Banerjee on LinkedIn.
Most conversations about artificial intelligence eventually return to the same concerns: is it going to replace my job, disrupt, and create an uncertain future? But what if we are looking at AI through the wrong lens?
On the latest episode of Tech Transformed, host Trisha Pillay sits down with Kevin Surace, an author, AI expert and technology pioneer who has spent three decades working on technologies that helped lay the foundations for products such as Siri and Alexa. His perspective is very different from the usual debate. Rather than viewing AI primarily as a threat to human work, Surace sees it as a tool that can expand what people are capable of achieving.
This shift changes the conversation from what AI might replace to what it could make possible. The discussion explores how AI can help people work faster, tackle problems that were previously out of reach and spend more time on areas where human judgment, creativity and experience still matter. For Surace, the question is not whether AI will change the way we work. That change is already happening. The more important question is what we choose to do with the capabilities it puts in our hands.
Silicon Valley Author and AI ExpertSurace holds 95 patents and is often credited as the father of the AI assistant. His work goes back to General Magic, an early-1990s Apple spinout where his team built the first digital agents and a programming language called Telescript. That early assistant technology had millions of users well before anyone was talking about chatbots.
His upcoming book, The Joy Success Cycle, grew out of a question people kept asking him: Why does he seem to enjoy his work so much? The answer, he told Pillay, comes down to sequencing. Most people wait for success before they let themselves feel joy. Surace argues it works the other way. Joy has to come first, and success follows from it.
How AI Brings JoySurace's favourite example is presentations. He used to spend a full week getting slides right, not because the ideas took that long to develop, but because formatting, alignment, and design details ate up all his time. Now he outlines what he wants to say, hands it to an AI tool, and gets a polished deck back within the hour.
The lesson he draws from that isn't about speed for its own sake. It's about separating the parts of a job that actually bring satisfaction from the parts that never did. Moving a font two pixels to the left never gave anyone joy, he says. Delivering an idea to a room full of people can. AI, in his view, quietly removes the first category and leaves more room for the second.
AI and the Case for More JobsSurace pushed back hard on the idea that AI shrinks the job market. He pointed to every major shift he's lived through from the PC, email, the smartphone, and the internet. Each one triggered the same fear, and each one ended up creating more roles than it eliminated.
He sees the same pattern playing out with software development right now. Coders using AI tools are shipping features and fixing bugs far faster than before, and instead of trimming teams, many companies are hiring more developers to keep pace with the new demand their own speed has created. The job itself has changed. Writing code line by line matters less than guiding the output and checking it. But the need for people hasn't gone away.
Rethinking Workflows With AIOne point Surace kept returning to was how companies get AI wrong when they try to automate their existing process instead of questioning why that process exists in the first place. He used car insurance claims as an example. The old approach sends an inspector to look at damage, fills out paperwork, and routes it through several people before a check gets issued. An AI-first approach skips most of that. A customer photographs the damage, uploads it, and a payment can go out the same day. This kind of redesign, he argues, is where the real gains sit. Businesses that only bolt AI onto old workflows will see modest improvements. Businesses willing to rebuild the workflow from scratch stand to cut costs dramatically and outpace competitors who don't.
Cybersecurity in the Age of AIThe conversation also turned to security, an area where Surace runs a company building biometric authentication devices. He explained that attackers rarely bother breaking into networks directly anymore, since most data sits encrypted. Instead, they use AI to generate convincing phishing emails and fake login pages designed to trick people into handing over multi-factor authentication codes. Surace believes fingerprint-based verification is where things are headed, since voices and faces can now be convincingly faked, but a fingerprint can't. He expects verified-identity badges to become common online within the next few years, giving people a way to confirm they're actually talking to the person they think they are.
What Leaders Should Do NowWhen asked what businesses should do now, Surace's advice was simple: get every employee using AI tools regularly, not occasionally. He compared it to the early days of the PC, when companies had to run training sessions just to get staff comfortable with word processors and spreadsheets. Adoption took time, but the alternative was falling behind. He sees AI the same way. Leaders who wait for their teams to come around on their own risk losing ground to competitors who move faster. If you would like to learn more, visit Kevin Surace's website or follow him on Linkedln.
Takeaways* AI removes repetitive work so people can focus on higher-value tasks. * Joy drives success in the AI era. * AI will create new jobs by accelerating innovation. * An AI-first culture is key to staying competitive. * Biometric security will help counter AI-powered fraud
Chapters00:00 Introduction to Kevin Surace and AI's Potential
01:52 Kevin's Journey and the Joy Success Cycle
04:14 AI as a Joy Maker in Daily Work
06:07 The Cycle: Joy Leads to Success
07:39 AI's Opportunity for Increased Jobs
12:15 Is AI a Technology Cycle or a Transformation?
13:50 The Ubiquity of Smartphones and AI's Role
14:39 Workforce Transformation and AI Adoption
23:06 Cybersecurity Challenges in the AI Era
26:55 Advice for CEOs and Leaders in an AI World
AI is changing the conversation around legacy modernisation, but successful transformation demands far more than powerful models and automated code generation. It requires engineering discipline, governance, and a clear-eyed view of where AI genuinely adds value and where it doesn't.
On a recent episode of Tech Transformed, host Christina Stathopoulos, founder of Dare to Data, sat down with Shodhan Sheth, Enterprise Modernisation Platform and Cloud Lead, and Alessio Ferri, Lead Software Engineer, both part of Thoughtworks' Global Legacy Modernisation Service Development Team, to unpack exactly that.
Legacy Modernisation With AIThe conversation around AI in legacy modernisation is often muddied by marketing noise. As Sheth puts it, "value and hype can coexist". Overpromising doesn't automatically mean a technology is worthless. The real question for technology leaders is whether AI meaningfully improves the cost-time-value equation for a specific problem.
This will always start with problem-solution fitness: has someone already solved a comparable challenge with AI, and does the proposed use case genuinely fit that pattern? As Sheth notes, "most things can be judged by cost, time, and value", which is a simple but effective filter for cutting through the noise.
Rethinking Legacy ModernisationGenerative AI is inherently probabilistic, while enterprise software has always relied on deterministic, predictable behaviour. Ferri unpacks this tension by separating two very different use cases: using AI to build systems, and embedding AI within operational systems.
When AI writes code, inconsistency is manageable; developers review, test and refine the output before it ships. Production systems are a different matter entirely, where unpredictable behaviour carries real operational risk. As Ferri explains, "AI in production requires different guardrails than AI for building."
The practical answer is controlled use. AI might suggest alternative products in a marketplace, for instance, while deterministic rules still guarantee that only in-stock items are ever shown. This lets AI add value within a firm, enterprise-grade constraints.
Why AI Alone Won't Modernise Legacy SystemsTechnology is only part of the story. Sheth is clear that modernisation is fundamentally about change, and change is hard, especially across large enterprises with tangled, interconnected systems. Tasks that resist automation are often the hardest, like upskilling teams, explaining complex trade-offs, and winning buy-in; these cannot be solved with code alone. These human and organisational factors are routinely underestimated. Where the impact of a change is broad, he also advises either aligning teams properly across the business or breaking the change into smaller, more manageable pieces, a strategy that reduces resistance and smooths the path to adoption.
If you would like to learn more about this, visit Thoughtworks or connect with both Sheth and Ferri on LinkedIn.
Takeaways* Applying AI to modernise complex enterprise systems. * Distinguishing hype from practical AI applications. * Balancing probabilistic AI with deterministic enterprise software. * Organisational and leadership challenges in AI modernisation. * Building control, traceability, and abstractions in AI workflows. * Advice for CIOs and CTOs on AI adoption.
Chapters00:00 Introduction to AI and Legacy Modernisation
01:18 Meet the Experts: Shodhan and Alessio
02:47 Distinguishing Hype from Value in AI
05:51 The Tension Between Probabilistic and Deterministic Systems
10:13 The Human Element in Modernisation
17:12 AI's Role in Enterprise Transformation
19:26 Distinguishing Hype from Value in AI
22:13 Probabilistic vs Deterministic Systems
27:45 People and Processes in Modernisation
29:03 Lessons in AI for Legacy Modernisation
Every customer service call now produces a measurable outcome, which is exactly why customer experience has become the place where agentic AI either proves itself or falls apart. Most enterprise AI hype centres on generation and productivity. But according to Sneha Iyer, who leads AI value delivery and analytics at Observe.ai, the real test of agentic AI is happening somewhere less flashy, which is the contact centre. In a recent episode of Tech Transformed, host Ravit Jain asked Iyer why customer experience (CX) has become the industry's default stress test and what that means for enterprises still sorting isolated chatbots from genuine AI agents. Iyer has spent nearly a decade watching CX change from manual quality assurance to a blended workforce of human and AI agents. This shift, she says, has quietly rewritten the metrics, tooling, and governance decisions every enterprise leader now has to make.
Why Customer Experience Became AI's Testing GroundIyer explains that CX generates more human-AI interaction data than almost any other business function. Every conversation resolves in a clear outcome, resolved or not, retained or churned, and it spans every modality a company touches, from voice to chat to email. Solve AI reliability here, and the lessons transfer everywhere else.
What's actually changed, she notes, isn't that AI got smarter; it's that AI stopped just watching and started acting. Where AI agents once flagged patterns in a transcript after the fact, they now issue refunds, verify identities, and book appointments in real time. This has split the workforce in two, namely, AI agents absorb the high-volume, low-risk interactions, while human agents get pushed toward the complex, judgment-heavy calls machines shouldn't handle alone. Old metrics like containment and deflection no longer capture that split; leaders now need blended resolution measures that account for both.
Fragmented AI StacksIf you ask most contact centres what their AI stack looks like, you'll find what Iyer calls a "Frankenstein stack": one tool for analytics, another for telephony, another for conversational intelligence, stitched together and barely talking to each other. That setup was tolerable when each tool did one isolated job. It breaks the moment you add agentic AI, because these types of systems depend on shared context to function.
Without that context, a customer verified by an AI agent has to repeat everything to the human agent who picks up next, which turns an already frustrating support call into a worse one. Fragmented tools also make it nearly impossible to prove ROI, since every vendor tracks success differently and costs stack with each new integration.
This is the case for unified CX platforms: not as a nice-to-have, but as the only way to preserve context across a customer's full journey. Iyer points to "companion agents" as a concrete example of real-time, in-context support for human agents that shows them exactly why an AI agent escalated a call and what happened before they picked up.
Build vs. BuyOn the build-versus-buy question, Iyer highlights that building in-house looks cheap upfront and rarely stays that way. Models change every few weeks, which turns any custom build into a permanent maintenance commitment most teams underestimate, including in regulated industries like healthcare and finance, where leaders often assume building keeps data safer. In practice, established vendors have already solved the compliance groundwork, data residency, model governance, and audit trails that a custom build would take months to replicate.
Trust, she argues, isn't really about doubting AI's competence. It's the fear of the one catastrophic interaction happening at scale. That's what simulation testing and evaluation frameworks are for, stress-testing AI agents against the hardest, most ambiguous scenarios before launch, not just the easy paths, backed by governance frameworks that can roll back a deployment fast if something breaks.
Looking six to twelve months out, Iyer expects three shifts, continued consolidation around unified platforms, evaluation frameworks becoming the real competitive edge (not raw model performance), and pricing models moving from seat-based to outcome-based. Her advice to leaders is to build auditability and governance into your AI strategy now, before regulation forces the issue.
Building Customer ExperienceThe throughline of Iyer's conversation with Jain is that agentic AI in customer experience succeeds or fails on infrastructure and trust, not on which model you're running. Enterprises that unify their data, rethink their success metrics, and choose vendors who can prove reliability through thorough testing are the ones positioned to scale AI-driven CX without breaking it. If you would like to find out more about this visit observe.ai or connect with Sneha Iyer on LinkedIn.
Takeaways* Shift from isolated AI tools to integrated agent systems. * Importance of simulation testing and evaluation frameworks. * Benefits of unified customer experience platforms. * Build versus buy decision in enterprise AI. * Future trends in AI-powered customer experience.
Chapters00:00 Introduction to Tech Transform and AI Evolution
02:01 Sneha Iyer's Role and Background in AI
09:35 The Shift in Customer Experience with Agentic AI
13:24 The Move Towards Unified Customer Experience Platforms
18:55 Build vs. Buy: Navigating AI Solutions in Enterprises
20:59 The Cost of AI Maintenance and Vendor Insights
22:20 Navigating Compliance in Regulated Industries
24:52 Building Trust in AI Adoption
30:00 Use Cases Driving AI Value
34:31 Future Trends in AI Customer Experience
The semiconductor industry is undergoing one of its most profound transformations in decades. Driven by the insatiable demand for compute power largely fueled by AI workloads, engineers are moving away from traditional monolithic chips and shifting toward complex multi-die designs. This shift brings a new set of challenges that conventional design and validation methods simply cannot handle.
In a recent episode of the Tech Transformed podcast, host Dana Gardner sat down with Shekhar Kapoor, Executive Director of Product Line Management at Synopsys, to explore how the growing complexity of semiconductors is changing the way engineers design and validate modern systems. From thermal management to AI-driven automation, the conversation reveals why the old way of building chips is no longer good enough and what the future looks like.
Multi-Die DesignKapoor explains that the transition to multi-die design is no longer a matter of preference but a necessity. He attributes this shift to the relentless demand for greater compute capacity, driven largely by the rapid growth of AI.
Traditional monolithic chips are hitting hard limits. Reticle sizes are maxing out, and rising yield and cost challenges make it increasingly impractical to pack more functionality onto a single die. Multi-die designs solve this by disaggregating functionality across smaller dies, each targeting the most appropriate process technology, then integrating them into a unified, optimised package.
Leading AI systems already integrate multiple compute and I/O dies alongside large high-bandwidth memory (HBM) stacks, scaling to 3x–5x reticle-class designs and beyond. The design challenge is very different. As Kapoor puts it: "You're no longer optimising a single chip, you're optimizing a system of chips."
This requires system-level co-design from day one, spanning architecture, silicon, packaging, power delivery, and interconnect strategy simultaneously. Engineers must think in terms of System Technology Co-Optimisation (STCO), not just chip-level optimization. The design tools, methodologies, and team workflows all need to change. For engineers and technology leaders looking to explore these trade-offs, Synopsys has published a comprehensive eBook on accelerating multi-die design and innovation.
Thermal Analysis and Multi-Physics ValidationHistorically, thermal, power, and electromagnetic analyses were performed as downstream validation steps once the core design was complete. In a multi-die world, that approach is no longer viable.
"Thermal management is becoming the number one issue when designing these multi-die designs. It has to be managed across a range of scales, from transistor activity to package and board level," Kapoor says.
The problem with late-stage validation is timing. By the time thermal or power integrity issues surface, the most critical decisions are already locked in floorplans, interconnect topologies established, and packaging assumptions embedded.. At that point, the only options are costly ECOs, excessive margining, or a full redesign. Industry estimates suggest over-design can lead to up to 30-35 per cent wasted silicon and hundreds of millions of dollars in optimisation loss.
The solution is a shift-left approach that embeds multiphysics analysis from the earliest stages of design. When thermal hotspots, voltage drop issues, and electromagnetic interactions are identified early, engineers can adjust partitioning and placement strategies before they become expensive problems.
This is the methodology detailed in the Synopsys ebook on Multiphysics Fusion for multi-die design, which covers how teams can build continuous multiphysics validation into their flows to avoid late-stage surprises and protect both performance and reliability.
Multiphysics Fusion and AI-Driven Chip DesignTo operationalise the shift-left methodology at scale, Synopsys has introduced the concept of Multiphysics Fusion. This is the native integration of AI-powered EDA technologies with ANSYS's gold-standard multiphysics sign-off analysis capabilities.
Within the 3DIC Compiler platform, this means unifying the implementation environment with RedHawk-SC, RedHawk-SC Electrothermal, and HFSS-IC technologies. This brings IR drop, thermal, signal, and power integrity analysis directly into the design loop. The result is greater predictability, tighter correlation between in-design analysis and sign-off, and significantly fewer design iterations.
The impact on design closure times has been substantial. According to Kapoor, teams using the Multiphysics Fusion solution have seen turnaround times shrink "from weeks to days, and in some cases even hours" even for large, high-performance multi-die designs.
AI amplifies these gains further. Synopsys employs AI in two primary ways: assistive automation through its 3DSO.ai technology, which integrates multiphysics feedback into the optimization loop in real time, and agentic workflow orchestration, which becomes increasingly critical as system complexity scales toward designs incorporating hundreds or even thousands of GPUs. As Kapoor notes, at that scale, "agentic workflows could help engineers converge faster" and manage trade-offs that would otherwise be intractable. If you would like to find out more about this, download the full eBook: Multiphysics Fusion Technology for Multi-Die Designs Explained from Synopsys, which expands on each of these themes with real-world examples, design methodologies, and guidance for implementation teams. You can also connect with Shekhar Kapoor on LinkedIn.
Takeaways* Multi-die architectures and their drivers. * Challenges of traditional monolithic chips. * Importance of early multi-physics analysis. * Multiphysics fusion and its benefits. * AI's role in design automation. * Reducing time-to-market through integrated platforms. * System-level co-design. * Thermal management in 3D IC stacking. * Shift left approach in multi-physics validation. * Future trends in semiconductor design.
Chapters00:00 Introduction to Semiconductor Complexity
02:00 The Shift to Multi-Die Designs
04:30 Challenges in Multi-Die Design
08:11 The Importance of Early Multi-Physics Analysis
10:05 Introducing Multiphysics Fusion
12:37 AI's Role in Semiconductor Design
16:37 Reducing Time to Market
19:39 Applications Beyond AI
21:12 Real-World Examples of Multi-Physics Validation
26:20 Practical Advice for Engineers
When most people hear "digital divide," they picture communities without broadband. But in 2026, that definition is dangerously outdated. "The digital divide is no longer just about internet access." These words from Graeme Gordon, Chief Executive Officer of Converged Solutions Group, set the tone for one of the most pressing conversations in technology today.
In this episode of Tech Transformed, host Trisha Pillay sits down with Gordon to unpack the changing digital divide, the massive impact of AI adoption, and what it truly takes. Gordon, whose background spans electrical engineering, oil and gas robotics, and three decades of founding and scaling tech companies, says that the new digital divide is about meaningful participation in the AI-driven economy, not just connectivity.
“More people are connected than ever before,” Gordon explains. “But connection without capability is just noise.” He points to mobile internet adoption as a case in point. Billions of people now access the internet via smartphones. However, the gap between scrolling social media and using cloud-based AI tools to build products and services remains wide.
This participation gap is the new frontier of digital exclusion. The implications stretch well beyond individual users. Organisations, governments, and education systems that fail to close this gap risk being locked out of the innovation economy entirely.
AI Adoption Without EducationFew developments have accelerated the digital divide conversation quite like the arrival of ChatGPT in late 2022. Gordon calls it plainly: "ChatGPT has disrupted and transformed the sector," and not just for technologists. The tool put generative AI in the hands of business professionals, students, and everyday users almost overnight.
Gordon says it's time to rethink our approach to AI. At a recent event he attended with 100 business leaders in the room, every hand went up when asked if they had used an AI platform in the last 24 hours. When asked who had received any formal training on how to use those tools, not a single hand was raised. This is the core paradox of AI adoption today. The tools are everywhere. The understanding of how to use them safely, strategically, and effectively is not. Without structured digital literacy and education, rapid AI adoption becomes a liability rather than an asset for individuals and organisations alike.
Barriers to Digital InclusionGordon identifies several interconnected barriers preventing organisations from fully participating in the digital economy. Let's have a look:
- Skills gaps remain the most acute. Technology evolves faster than most training programmes, let alone formal education curricula. University degrees and annual school terms were not designed for the pace of AI-driven change.
- Trust and credibility are equally critical. Gordon warns of what he calls "AI slop", the growing proliferation of AI-generated content and half-built solutions that look polished but lack substance or security. Organisations that rely on AI without proper oversight risk undermining the customer trust they're trying to build.
- While infrastructure quality is improving globally, it still creates disparities, particularly around data sovereignty. The question of where your data sits, who can access it, and under what compliance framework is no longer just a legal concern. It is a competitive and ethical one.
Sovereign AIOne of the most forward-looking concepts Gordon introduces is sovereign AI, the idea that organisations must control not just their data, but the AI infrastructure that touches it. Just as data sovereignty became a boardroom priority, AI sovereignty is now following the same path.
"Business leaders type sensitive information into ChatGPT or Copilot without thinking twice," Gordon cautions. The solution isn't to avoid AI, it's to build internal AI agents and platforms that interact with large language models without exposing proprietary data to the open web. This is why hyperscaler data centres are appearing in unexpected geographies: latency is secondary; sovereignty is the driver.
Gordon's advice to business leaders is refreshingly direct: go experiment. "You won't break anything," he says. The AI-driven economy rewards curiosity, iteration, and speed of learning, not perfection. Leadership teams need to model responsible AI use, invest in upskilling their people, and treat education as a strategic asset. This applies as much to frontline healthcare workers as it does to C-suite executives.
If you would like to find out more, connect with Graeme Gordon on LinkedIn.
Takeaways* The evolving digital divide from access to participation. * Impact of AI and ChatGPT on business and society. * Importance of secure and sovereign AI infrastructure. * Role of education in digital literacy for all. * Leadership strategies for AI adoption and trust. * Barriers to digital inclusion: skills, trust, infrastructure. * Practical steps for organisations to implement AI responsibly.
Chapters00:00 Understanding the Digital Divide
02:49 The Role of AI in Participation
06:01 Barriers to Digital Adoption
09:07 The Importance of Education
11:45 Building a Secure AI Foundation
14:51 Trust and Credibility in AI
18:11 Practical Advice for Organisations
AI isn't just speeding up recruiting; it's actually forcing companies to redesign work itself, blending human judgment with agentic execution across hiring, mobility, and skills development. As a result, most conversations these days are about AI in the enterprise centre on software development and engineering. Recruiting, hiring, and talent management get far less attention, but they may be where AI's impact is most immediate.
In a recent episode of Tech Transformed, host Dana Gardner spoke with Meghna Punhani, Chief People Officer at Eightfold AI, about how organisations are rethinking talent acquisition, workforce planning, and employee development in an AI-driven world. Meghna Punhani's perspective is shaped by nearly two decades at Google, a stint leading employee experience at Palo Alto Networks, and her current dual role at Eightfold AI, where she both leads the people function and helps build the product her team relies on. That vantage point gives her a practical, ground-level view of what works and what doesn't when AI meets HR.
Reimagining the Talent Lifecycle with AI Punhani's central argument is that most legacy HR systems were designed for a different purpose, one that has evolved as work itself has changed and the workforce now includes AI agents alongside people. Simply bolting automation onto existing processes, she argues, isn't enough. Organisations that are succeeding are the ones re-engineering roles, workflows, and organisational structures from the ground up, treating this as an operating-model shift rather than an IT upgrade.
This shift touches the entire talent lifecycle, from how companies find candidates and evaluate skills instead of just job titles to how they support internal mobility. Punhani points out that skills now have a much shorter shelf life than in the past, which means static job descriptions are giving way to dynamic, skills-based decision-making. AI, she says, helps surface pathways for employees that traditional resumes and titles would never reveal, including her own nontraditional route into HR leadership.
How AI Is Reshaping Workforce Strategy Trust is the recurring theme throughout the discussion. Punhani is candid that employees often fear AI-driven decisions, especially around jobs and evaluations. Her approach is focused on transparency first. When Eightfold rolled out digital twins internally, employees were uneasy until leadership explained how the technology worked and used it themselves, which helped build organisation-wide confidence.
That same principle shows up in Eightfold's own hiring practice. One example is the company's campus recruiting programme in India, where its AI interviewer conducted roughly 90 per cent of interviews. This enabled recruiting to scale from around eight or 10 university partners to more than 150, and from approximately 5,000 applications to 15,000, without pulling engineers away from their day-to-day duties.
Time-to-offer dropped from around six weeks to as little as four days in some technical roles, largely because interviews could happen around the clock rather than around a recruiter's or hiring manager's schedule. Beyond recruiting, Eightfold's internal initiative, nicknamed Project Andromeda, applies the same re-engineering approach across sales and finance, reportedly reclaiming thousands of employee hours through redesigned, agent-assisted workflows.
AI and the Future of TalentLooking ahead, Punhani doesn't frame AI as a threat to human contribution, but she frames it as an amplifier of it. As tools become more accessible across every function, she believes the people who will succeed won't be the ones who know the most facts, since AI can answer those questions. Instead, it will be the people who ask better questions, orchestrate multiple AI agents, and apply judgment where the right answer isn't obvious.
For HR leaders specifically, Punhani's advice is to claim a seat at the table now, rather than letting AI adoption happen without a people-first lens. This means learning the technology firsthand, demonstrating its value to non-technical teams, and partnering closely with CTOs and CIOs to shape decisions jointly. Her advice for individuals entering this shifting job market is similarly grounded: focus on learning agility over any single technical skill, since the skills in demand today may look different within months.
Future of AI in Talent ManagementAcross the conversation, Punhani returns to one idea, and that is AI in talent management isn't primarily a technology problem; it's a leadership and trust problem. Organisations that treat it that way, redesigning work with both humans and agents in mind, are the ones seeing measurable gains in speed, candidate experience, and internal mobility.
For HR leaders exploring AI adoption, the takeaway from this episode is to start before you feel ready, build trust through transparency, and let AI handle evaluation and execution so people can focus on judgment, empathy, and connecting the dots across the organisation. If you would like to find out more, visit eightfold.ai or connect with Meghna Punhani on LinkedIn.
Takeaways* AI's impact on talent acquisition and management. * Reengineering work processes with AI. * Building trust and transparency in AI systems. * Skills-based internal mobility and workforce planning. * AI-driven candidate evaluation and employee development.
Chapters00:00 Introduction to AI in Talent Management
02:59 Understanding AI's Role in Talent Acquisition
06:07 AI's Impact on Workforce Planning and Skills Development
10:02 Building Trust in AI for Hiring Processes
13:04 Internal Use of AI at Eightfold AI
18:58 Measuring ROI from AI in Talent Acquisition
25:02 Enhancing Candidate Experience with AI
29:53 Future Directions for AI in Talent Management
With enterprises now rushing to integrate AI agents into their operations and security, the most imperative focus now becomes the AI model itself. However, Eric Tschetter, Chief Architect at Imply, believes the real challenge is within the data infrastructure that supports these systems.
In the recent episode of the Tech Transformed podcast, Kevin Petrie, BARC Vice President of Research, sat down with Tschetter to talk about how AI is actually increasing the current needs around scale, performance, and data access.
“Agents are always running queries. They’re always doing stuff,” Tschetter stated.
Unlike human analysts, AI systems work continuously, producing much higher query volumes and putting more pressure on the data platforms underneath. This leads to a greater demand for observability architectures that can manage more data, more users, and more machine-to-machine interactions without losing speed.
For Tschetter, the solution is not to create new observability tools, but to rethink the data layer that supports them.
Key Takeaways* AI is transforming observability and security disciplines. * The observability warehouse concept is gaining traction. * AI agents increase the volume of queries significantly. * Data silos remain a major challenge for enterprises. * Collaboration between IT and security teams is essential. * Observability and security teams often consume the same data. * A decoupled architecture can enhance data accessibility. * The semantic layer must support multiple query languages. * Effective data management is crucial for AI-driven workloads. * Data should be stored once and accessed from multiple platforms.
Chapters* 00:00 Introduction to AI and Observability * 02:08 Challenges in Observability with AI * 06:44 Modernising Architecture for Observability * 10:49 Decoupled Observability and Semantic Layers * 16:31 Collaboration Between IT and Security Teams * 22:23 Imply's Observability Warehouse and Data Lakes
For more information on AI, observability and Imply’s observability warehouse and data lakes, please visit imply.io.
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Across every industry, boards are approving AI budgets. Inside many enterprises, however, the reality is the same. Pilots never scale, tools sit unused, and transformation programmes struggle to justify their investment. In this episode of the Tech Transformed podcast, host Trisha Pillay sits down with Darin Patterson, VP of Product Advocacy and Market Strategy at Make, to find out what separates the organisations genuinely operationalising AI from those still running expensive experiments.
AI Adoption GapEnterprise AI investment is accelerating. What is not accelerating at the same pace is business value. Patterson is direct about why he believes that most organisations are measuring the wrong things, assigning ownership to the wrong people, and deploying tools before they have defined the problem.
"The AI adoption gap is real," Patterson tells Pillay, "and it starts at the top. Leaders are approving investments without a clear framework for what success looks like."
For C-suite executives, this is a critical signal. AI adoption is not primarily a technology challenge; it is an organisational one. Strategy, culture, and accountability structures determine if AI initiatives produce compounding returns or accumulate as technical debt.
Ownership ModelsOne of the most instructive conversations in this episode concerns who should own AI inside an enterprise. Patterson's position is that ownership must live with the people closest to the business function being transformed.
"Ownership models are often unclear," he says. "And unclear ownership is where AI initiatives go to die."
When AI is owned exclusively by a central IT or data science function, it becomes disconnected from the operational realities of the teams it is meant to serve. When it is owned entirely by individual business units without central governance, you get fragmented tooling, inconsistent data practices, and security exposure. The hybrid model Patterson advocates centralises governance standards, security, and infrastructure while pushing execution authority down to functional leaders. This structure creates accountability at the point of value creation rather than at a remove from it.
For C-level executives building or restructuring their AI operating model, the actionable question is: do the leaders of each business unit have both the mandate and the capability to own AI outcomes in their domain?
Stop Starting With the ToolA pattern Patterson sees consistently across enterprises is what he calls tool-first thinking. An organisation identifies a capable AI platform, deploys it, and then attempts to work backwards to the business problem it should solve.
"Focus on your business process first," he advises. "The tool is never the strategy."
This is especially relevant for executives evaluating vendor proposals. The quality of an AI platform matters far less than the clarity of the problem definition sitting upstream of it. Organisations that achieve sustainable AI ROI typically begin by mapping their highest-friction processes, quantifying the cost of those inefficiencies, and only then evaluating which AI capability best addresses the root cause. The discipline of process-first thinking also prevents a common failure mode by automating a broken process rather than fixing it. AI applied to a flawed workflow does not eliminate the flaw but rather accelerates it.
Culture Is the MultiplierPatterson also points to a softer but critical success indicator, which is cultural adoption. If the teams closest to an AI deployment are not using it willingly and consistently, the business case will not hold, regardless of what the pilot showed.
The final, and perhaps most important, dimension Patterson raises is culture. Technical capability and strategic clarity are necessary but not sufficient conditions for AI success at scale. The organisations that are genuinely ahead are those that have invested in building an AI-literate workforce, not just an AI-enabled one.
"Invest in people as much as you invest in AI," Patterson says. "The technology will keep improving. Your competitive advantage comes from people who know how to use it well."
For C-level leaders, this means reframing AI investment as a human capability programme as much as a technology programme. Training, change management, and psychological safety around experimentation are not soft additions to an AI strategy, but they are core to its delivery.
Listen to the full conversation with Darin Patterson on the Tech Transformed podcast. Connect with Darin on LinkedIn and explore Make's automation platform at make.com.
Takeaways* AI adoption challenges * Organisational culture and AI * Ownership models for AI * Measuring AI success * Operational AI examples
Chapters00:00 The AI Adoption Landscape
03:01 Bridging the ROI Gap in AI
05:48 Ownership and Responsibility in AI Implementation
08:57 Strategic Approaches to AI
11:57 Measuring Success in AI Initiatives
15:00 Cultural Transformation for AI Success
18:53 Real-World AI Implementation Examples
24:00 Advice for C-Level Leaders on AI Investment
For years, enterprise AI conversations have centred on chatbots, search assistants, and tools that respond when asked, but that era is ending. A new class of AI system, one that reasons, plans, and takes autonomous action, is moving from the research lab into live production environments. For C-suite leaders, the question is no longer if AI will arrive in their organisations, but whether those organisations are ready for it.
In a recent episode of Tech Transformed, host Christina Stathopoulos, founder of Dare to Data, sat down with Cathal McCarthy, Chief Strategy Officer of Kore.ai, and Dan Leiva, founder of CXamplify and author of Amplified, to lay out what this shift actually means in practice and why most enterprises are less prepared than they think.
Have a look at Artemis, the agent platform from Kore.ai, or you can book a demo.From AI Pilot Projects to ProductionMost large organisations have run AI pilots. Far fewer have moved those pilots into meaningful production at scale. McCarthy and Leiva argue that this gap is not primarily a technology problem. It is a governance and accountability problem.
Conversational AI systems, which are the kind that answer questions or generate text, operate within a relatively contained risk envelope. A poorly worded response can be corrected, and a hallucinated answer can be flagged. The stakes, whilst real, are manageable.
Agentic AI operates differently. These systems do not simply respond to prompts. They assess situations, make decisions, trigger actions, and in some cases instruct other AI agents or software systems to carry out tasks on their behalf. When something goes wrong in an agentic workflow, the consequences can cascade quickly, across processes, data, customer interactions, and operational outputs.
This is why the move from pilot to production represents a fundamentally different risk conversation. As McCarthy puts it, "technology is now a decision-making actor." That framing has significant implications for how enterprises structure ownership, oversight, and accountability around their AI deployments.
What Agentic AI Actually Means for Your OrganisationThe term “agentic AI” is often used loosely, so it is important to clarify what it actually means. An agentic system can:
- Break a complex goal down into sub-tasks without human prompting at each step.
- Use tools, APIs, databases, and other software to execute those tasks.
- Adapt its approach based on intermediate results.
- Operate across extended time horizons without continuous human input.
This is meaningfully different from a large language model that generates a report when asked, or a copilot that suggests the next line of code. Agentic systems take initiative, which means it's both their value and their risk.
Leiva's book, Amplified, explores how organisations can harness this capability without losing control of it. The central argument is that autonomy is not a binary switch; it is a dial. Organisations need to be deliberate about where they set that dial across use cases, risk profiles, and stages of deployment maturity.
A Framework for Smarter AI DecisionsOne of the most practical tools discussed in the episode is the three-class decision model. Rather than treating all AI decisions as equivalent, it asks leaders to classify decisions by consequence and reversibility.
The first class covers routine, low-stakes decisions where agentic systems can operate with high autonomy, like scheduling, data routing, and standard customer queries. The second class covers decisions with moderate consequences, where human review should be triggered before action is taken. The third class covers high-stakes decisions where human authority must remain the final step.
Mapping AI deployments to this framework is the foundation of a defensible governance structure, one that can satisfy board scrutiny and regulatory requirements simultaneously. It also forces a critical question: who owns the decision about which class a given AI action falls into? That ownership question, the guests argue, is where most enterprise AI programmes currently have a blind spot.
The Leadership ImperativeWith that said, the organisations that will benefit most from the agentic era are not necessarily those with the most sophisticated technology. As Leiva writes in Amplified, they are the ones who have thought most carefully about how to deploy that technology in a way that is accountable, adaptable, and aligned with how their people actually work.
Boards are already asking harder questions about AI risk. Leaders who can answer them confidently because they have built the governance frameworks and defined the accountability structures will hold a material advantage. For leaders ready to move beyond the pilot stage, McCarthy and Leiva offer grounded guidance. Listen for more insights, and if you have any questions, feel free to get in touch with them directly.
Connect with the guests:
- Cathal McCarthy — LinkedIn | Kore.ai
- Dan Leiva — LinkedIn | CXamplify
Further reading: Amplified by Dan Leiva — available on Amazon
Have a look at Artemis, the agent platform from Kore.ai, or you can book a demoTakeaways* The shift from conversational to agentic AI * Enterprise AI governance and accountability * Operationalising AI at scale and risk management * Building trust and transparency in autonomous AI systems * Turning AI experimentation into measurable business outcomes
Chapters00:00 – Welcome to the Agentic Era
02:33 – The Shift in AI Utilisation
06:47 – From Pilots to Production: Understanding Risks
10:10 – Gaps in AI Readiness
13:11 – Rethinking Governance and Accountability
16:50 – Operationalising Agentic Systems
20:09 – Applying Agentic Workflows in Practice
22:43 – Actionable Advice for Leaders
Podcast: Tech Transformed
Guest: Mihir Nanavati, GM and Product Executive in MarTech and AdTech
Host: Doug Laney, Research & Advisory Fellow at BARC and Author of Infonomics & Data Juice
AI might have overtaken the industry with processing data, automating workflows, and creating content. The next big thing could be a major one, says Mihir Nanavati, GM and Product Executive in MarTech and AdTech, “AI is moving from managing data to making decisions with it.”
In the recent episode of the Tech Transformed podcast, host Doug Laney, Research & Advisory Fellow at BARC and Author of Infonomics & Data Juice, sat down with Nanavati to talk about a larger transformation in data and decision-making systems driven by AI.
They particularly focus on the integration of agentic AI in marketing and customer data platforms. They explore the challenges of fragmentation in ad tech, the importance of connecting customer data to revenue outcomes, and the transformative role of AI in decision-making processes. Mihir shares insights on how companies can leverage AI to enhance their marketing strategies and the future of first-party data.
"This is not a cost exercise, it’s about how much more you can get done and how many more ideas you can execute," said Nanavati.
For years, enterprises went through waves of technological change, including cloud infrastructure, mobile platforms, and customer data platforms (CDPs). Each development helped enterprises collect, store, and manage larger amounts of data. However, Nanavati asserts that humans making most decisions will never change. Now, AI agents are introducing a new model.
How AI has Moved from Data Navigation to Making DecisionsIn the past, customer data initiatives aimed to create a unified view of customers. Enterprises built warehouses, ETL pipelines, and data platforms that were designed to be reliable.
However, Nanavati suggests that AI agents are changing these expectations. "Machines can reason, and that is fundamentally different."
Rather than simply serving as another analytical feature in existing systems, AI agents are increasingly acting as decision-makers. They weigh trade-offs, learn from results, and execute plans based on specific goals.
This change has significant implications for customer data platforms. CDPs are not just repositories for customer information now. Instead, they are becoming layers that enable intelligent actions.
"The role of customer data platforms is evolving into ‘how do you make meaning of this?’" While, decisions about which customer segment to target, which message to send, or which offer to present may increasingly be guided by AI-driven systems.
What’s the Fragmentation Problem in Modern AdTechWhile AI agents create new opportunities, Nanavati pointed out a persistent issue in the AdTech and MarTech ecosystem – fragmentation. Brands today tend to lean towards deploying multiple advertising and customer engagement platforms. These include social platforms, retail media networks, email tools, and specialised ad technologies. Each system may optimise effectively within its own space, but often fails to connect at the customer level.
Nanavati calls it a "paradox of choice." "Each system is optimising locally for its own clicks and conversions, but none of that is coordinated at the consumer level."
The result is a customer experience that many consumers notice, alluding to repeated retargeting for products they have already bought, irrelevant recommendations, or disconnected interactions across channels.
As enterprises adopt AI agents, fragmented data environments may become an even bigger problem. AI systems can process information quickly, but they still rely heavily on context. "AI doesn't need perfect data in many cases, but it needs context."
What’s Next for Enterprise Tech?As AI adoption continues, Nanavati believes that successful enterprises will be recognised not by how many experiments they run, but by how fast they learn and use the results.
"Learn very rapidly. Then scale what you've learned." For leaders, this may require a stronger commitment than just isolated pilot programs or limited rollouts. It may also need organisational changes that place AI decision-making and customer context at the centre of growth strategies.
For companies navigating the intersection of AI agents, CDPs, and customer data, the question may no longer be whether AI can automate processes. The ultimate question is about who is calling the shots.
Key Takeaways* AI is fundamentally changing how decisions are made in marketing. * The shift from third-party to first-party data is crucial for businesses. * Fragmentation in ad tech leads to a paradox of choice for brands. * Connecting customer data to revenue outcomes is essential for success. * AI can help marketers make better decisions without needing perfect data. * Customer data platforms are evolving to support real-time decision-making. * Companies can run significantly more marketing experiments with AI. * Leaders must personally drive change in their Enterprises. * Successful AI implementation requires a focus on revenue outcomes. * First-party data collection is becoming more sophisticated and essential.
Chapters00:00 Navigating the Shift in Data and AI
03:03 The Evolution of Decision-Making in Marketing
05:55 Challenges of Fragmentation in Ad Tech
09:00 Connecting Customer Data to Revenue Outcomes
11:56 The Role of AI in Customer Data Platforms
14:55 Real-World Applications of Agentic AI
18:05 Blueconic's Approach to Customer Growth
21:14 The Future of First-Party Data
24:02 Building Habits for Successful AI Implementation
Listen to the full episode of Tech Transformed for a deeper discussion on AI agents, customer data platforms (CDPs), first-party data strategies and the future of AdTech. Subscribe for upcoming episodes and join the conversation across our social channels.
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Podcast: Tech Transformed
Guests: Maxim Fateev, Co-Founder and CTO, Temporal Technologies and Cornelia Davis, Developer Advocate, Temporal Technologies
Host: Kevin Petrie, VP of Research at BARC
Artificial Intelligence (AI) models have been breaking ground in the last three years. In the race to boost capabilities month by month among platforms like OpenAI, Anthropic, and Google’s Gemini models. However, for many enterprises, the main challenge is not creating AI prototypes; it's ensuring they can reliably support real business processes.
In a recent episode of the Tech Transformed podcast, Kevin Petrie, VP of Research at BARC, hosted a discussion with Maxim Fateev, Co-Founder and CTO, Temporal Technologies and Cornelia Davis, Developer Advocate, Temporal Technologies. They talked about why enterprises find it hard to transition AI from experimentation to production and how infrastructure must change to support autonomous systems.
Why AI Demos Break in the Real WorldAccording to Davis, many organisations make a common mistake: they focus on the "happy path" during experiments and overlook real-world operational challenges. “We have always ignored the non-functional requirements until we go to prod at our peril,” Davis said. “A lot of our experimentation is so focused on the models that we forget about the non-functional requirements.”
This means developers often prioritise model performance but neglect reliability, scaling, and system resilience. Agent frameworks used in experiments—usually lightweight Python or TypeScript libraries—add to the issue.
“What you’re really building is a highly distributed system that’s calling Large Language Models (LLMs) that will be rate-limited… networks are going to go down,” Davis explained. “When we move into prod, we haven’t considered scale or instability.”
As enterprises expand AI into their workflows, these overlooked details become imperative. A single outage, rate limit, or infrastructure failure can disrupt a complicated workflow that involves multiple AI steps.
Also Watch: Developer Productivity 5X to 10X: Is Durable Execution the Answer to AI Orchestration Challenges?
What Risks are Surfacing Since the Rise of Agentic Systems?The transition from simple AI workflows to autonomous agents adds a new layer of complexity. Traditional AI applications have predictable flows—such as summarising documents, tagging data, or creating recommendations. In contrast, agentic systems choose tools and decide on actions dynamically.
“When we move from non-agentic to agentic, we introduce unpredictability,” Davis said. “The tools and the order they run in are unpredictable. Whether we go through the agentic loop once or a hundred times is unpredictable.”
Such unpredictability creates new governance and compliance challenges, especially in regulated industries. “Enterprises are still responsible for predictable outcomes,” Davis noted. “We need stronger audit trails to understand why the agent made the decisions it did.”
For enterprises, this means AI systems must ensure traceability, accountability, and compliance, even when decision paths differ from one interaction to another.
Why is Durable Execution the New Foundation for Enterprise AIFateev argues that to manage such newly surfacing risks, enterprises need a new architectural layer focused on reliability. His concept, “Durable Execution,” aims to ensure that complex workflows keep running even when infrastructure fails.
“You write code as if failures don’t exist,” Fateev explained. “If a process crashes, we recover all the state and continue executing.” In practical terms, Durable Execution allows long-running AI workflows to survive interruptions—from network outages to system crashes—without losing progress or data.
This is essential as agents start interacting with real systems and taking real actions. “The moment agents start acting on the external world—changing files, submitting orders—you absolutely don’t want those things to get lost,” Fateev said.
The Temporal co-founder further emphasised that enterprise AI will not completely replace traditional software systems.
“You will always have deterministic code,” he said. “You can’t imagine banks dynamically deciding what a money transfer means.”
Instead, the future architecture will combine deterministic software with agents that interact through controlled tools and reliable communication layers.
Also Watch: How Do You Make AI Agents Reliable at Scale?
Key Takeaways* AI projects fail in production when non-functional requirements are ignored * Agentic systems bring unpredictability, making governance, traceability, and auditability essential. * Lightweight experimentation frameworks aren't suited for enterprise workloads. * Durable execution enables reliable AI workflows, ensuring processes continue despite infrastructure failures. * Enterprise AI will blend deterministic software with agents.
Chapters* 00:00 Introduction to AI's Impact on Business * 03:53 Challenges in Integrating AI into Business Workflows * 13:00 Understanding Non-Functional Requirements in AI * 19:14 The Role of Orchestration in AI Systems * 24:26 Exploring Durable Execution in AI Workflows * 30:28 Future Architectures for Autonomous AI Systems * 36:05 Key Takeaways for Executives in AI Implementation
For more information, please visit em360tech.com and temporal.io.
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For years, data sovereignty was treated as a compliance requirement, focused mainly on keeping data within specific geographic borders. Today, that definition is no longer sufficient. True data sovereignty now encompasses control, visibility, and accountability over data wherever it resides, moves, or is processed.
In an era shaped by AI adoption and increasingly fragmented cloud environments, sovereignty has become a core driver of enterprise resilience and operational autonomy rather than a regulatory checkbox. In this episode of The Security Strategist, Tim Pfaelzer, Senior Vice President and General Manager, EMEA at Veeam, explains how the meaning of data sovereignty has fundamentally changed.
From Compliance Concept to Strategic PriorityA decade ago, data lived in well-defined corporate environments managed by internal IT teams. Today, it is distributed across public cloud platforms, SaaS ecosystems, edge devices, and third-party suppliers. This distribution has expanded the attack surface while making ownership and control significantly harder to define.
As a result, organisations are being forced to rethink sovereignty not as a legal constraint, but as a foundation for resilience, security, and trust.
Why Data Sovereignty Requires Cultural ChangeOne of the key arguments Pfaelzer makes is that data sovereignty cannot be solved through technology alone. It requires organisational alignment and executive ownership.
Data is now created and consumed across every business function, which means governance must extend beyond IT. Leadership teams must treat data as a critical business asset, with clear accountability structures across its lifecycle.
This shift is reinforced by regulatory pressure. Frameworks such as GDPR, the EU Data Act, and emerging AI governance rules now require organisations to demonstrate not only where data is stored, but how it is accessed, processed, and protected.
The Five Dimensions of Modern Data ControlPfaelzer outlines five core dimensions that define effective data sovereignty today:
- Visibility: Knowing where all data exists, including backups and third-party copies
- Ownership: Clear accountability for data across its lifecycle
- Access governance: Controlled and regularly reviewed permissions
- Portability: The ability to move data without vendor lock-in
- Compliance readiness: Continuous compliance rather than audit-only validation
Together, these determine how much real control an organisation has over its data estate.
Data Sovereignty as the Foundation of ResilienceModern resilience is no longer defined by backup alone. It is defined by recovery speed, completeness, and operational continuity. A prolonged outage or ransomware incident can cause significant damage, but the difference between minutes and days of downtime often comes down to recovery architecture and how rigorously it has been tested under real-world conditions. In this context, sovereignty and resilience are directly linked. Without control over data, there is no predictable recovery.
AI Has Raised the StakesArtificial intelligence has introduced a new layer of data risk that many organisations are still underestimating. As AI systems increasingly automate decision-making and customer interactions, the quality and integrity of training and operational data become critical. If that data is corrupted, incomplete, or outdated, the impact can spread silently across business processes before detection.
Unlike infrastructure failures, AI-driven data issues are not always immediately visible. This makes governance even more important. Pfaelzer argues that AI systems should operate under the same strict data controls as human users, including lineage tracking, access controls, and continuous validation of data integrity.
Why Data Sovereignty Now Defines Enterprise Autonomy
Ultimately, data sovereignty has changed into a measure of enterprise independence. Organisations that understand, govern, and control their data are better positioned to manage risk, comply with regulation, and adopt new technologies such as AI safely. Those who do not risk becoming dependent on opaque systems where visibility and control are limited. In 2026 and beyond, sovereignty is no longer just about where data lives. It is about who controls it, how it is used, and how quickly an organisation can recover when things go wrong.
Takeaways* Data sovereignty beyond geographic boundaries * Risks of data fragmentation across cloud and edge environments * Strategies for rapid data recovery and resilience * Ensuring data integrity and trust in AI systems * Control and ownership of data in a distributed landscape
Chapters00:00 Introduction to Data Sovereignty and Resilience
02:49 The Evolution of Data Management
06:03 Control, Risk Exposure, and Accountability in Data
08:57 Data Sovereignty Beyond Geography
12:04 Ensuring Data Integrity in AI Systems
15:05 Human Error and Data Management
18:02 Case Study: University of Manchester's Data Strategy
21:01 Non-Negotiables for Building a Resilient Data Strategy
Podcast: Tech Transformed podcast
Guest: John Newton, Chief Innovation Strategist at Hyland
Host: Dana Gardner, President and Principal Analyst at Interabor Solutions
Enterprise leaders rushing to integrate artificial intelligence (AI) into their operations often think the biggest challenge is the technology itself. In reality, the issue is much closer to home. It’s in the piles of unstructured enterprise data spread across documents, systems, and repositories.
In the recent episode of the Tech Transformed podcast, John Newton, Chief Innovation Strategist at Hyland, sits down with host Dana Gardner, President and Principal Analyst at Interabor Solutions. They discussed how enterprises can unlock the full value of enterprise AI by addressing fragmented information and building stronger governance frameworks.
Their conversation highlights that unstructured data is not an obstacle; it is the foundation for next-generation AI-driven productivity. As Newton stated, “The opportunity to truly use AI and use it effectively in your organisation really depends on that unstructured information.”
For companies looking to adopt AI on a large scale, the real work is in organising and contextualising their internal knowledge.
Is Unstructured Data the Hidden Fuel for Enterprise AI?Most enterprise data does not sit neatly in structured databases. Instead, it exists in contracts, reports, emails, videos, policies, and operational documents, creating a vast amount of unstructured content.
The enormous amount of such unstructured data ends up creating a challenge for AI projects that rely solely on foundation models. Large language models (LLMs) may be trained on public data, but they cannot inherently access proprietary business intelligence.
Newton argued that enterprise AI must therefore be built around internal knowledge systems. “Foundation models can’t train on your internal information,” he explained. “What you really want is that information to be part of the AI when you’re answering questions, doing research, or executing business processes.”
This change requires organisations to rethink how information flows across the enterprise. Instead of isolated systems—CRM platforms, ERP databases, content repositories—companies need an interconnected information structure that connects multiple sources in real time.
Such a structure enables AI systems and AI agents to find the right data at the right time. This also improves decision-making, automation, and operational intelligence.
How to Reorganise Chaotic Unstructured Data?If unstructured data is the fuel, curation is the engine that drives effective AI. Newton emphasised that an enterprise data strategy must start with mapping, organising, and cleaning information assets. The aim is to reduce noise and increase clarity.
“I like to look at things from a signal-to-noise perspective,” Newton says. “Curation is the key to removing uncertainty in the information.”
The method could typically comprise a combination of several enterprise technologies such as content management platforms with business process management (BPM) and AI agents and LLMs.
A pairing of the above strategies is aimed at helping enterprise data become more valuable. Enterprises can implement AI models to automate workflows, enhance knowledge discovery, and speed up processes across departments—from finance and manufacturing to customer operations.
Importantly, Newton noted that this work also allows flexibility in the AI ecosystem. With a solid information foundation, companies can use open-source models, hyperscaler services, or internal AI deployments without tying themselves to a single vendor.
In other words, an enterprise AI strategy should first focus on data readiness, not model selection.
Key Takeaways* Unstructured data is the foundation for effective enterprise AI. * Data curation improves AI accuracy and reduces information noise. * Connecting enterprise systems enables AI to deliver real-time insights. * AI guardrails help manage security, compliance, and data governance. * AI automation boosts employee productivity by reducing repetitive work.
Chapters* 00:00 Unlocking AI's Potential with Unstructured Data * 05:20 Signal to Noise: The Clarity Challenge * 11:21 Guardrails for AI: Balancing Control and Flexibility * 14:41 Harnessing the Enterprise Context Engine * 17:48 Real-World Applications: Case Studies in AI * 20:37 Curation: The Key to Effective Automation * 22:21 Future Business Value: Productivity and Beyond
For more information, please visit hyland.com
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Ecommerce no longer rewards scale alone. As customer expectations rise and margins tighten, revenue growth and conversion optimisation depend on how well organisations use their data, align their teams, and simplify their technology stack. Brands that fail to adapt are discovering that being data-rich but insight-poor is no longer a survivable position.
In this episode of Tech Transformed, host Christina Stathopoulos, Founder of Dare to Data, speaks with Kailin Noivo, President and Co-Founder of Noibu, and Rohit Nathany, Chief Product and Technology Officer at Mejuri. Together, they unpack what is holding ecommerce teams back from sustained revenue and conversion growth and what actually works in practice.
Ecommerce Revenue Growth in a High-Cost, High-Expectation MarketToday’s ecommerce environment is shaped by rising acquisition costs, operational sprawl, and customers who expect speed, relevance, and reliability by default. Rohit points to macroeconomic pressure, tariffs, and shifting buying behaviour as forces that are squeezing margins while raising the bar for customer experience.
At the same time, brands are struggling to connect the dots between marketing spend, on-site behaviour, and conversion outcomes. Personalisation is widely discussed, but execution often breaks down when teams cannot see how customer interactions move from ad click to checkout. Kailin describes this as a “perfect storm”, explaining that: “infrastructure scaled rapidly during the pandemic, and now needs consolidation, optimisation, and clearer ownership.”
Customer Experience, Team Alignment, and the Practical Use of AIImproving customer experience at scale requires more than simply adopting new technology. Organisations also need the right data, processes, and operational alignment to turn those tools into meaningful customer outcomes. It requires teams to work from the same signals and trust the same data. Both Kailin and Rohit stress that AI and automation only deliver value when they remove friction from day-to-day operations rather than adding another layer of complexity.
Used well, AI can support data analytics by automating routine monitoring, surfacing patterns that matter, and freeing teams to focus on higher-value work. Used poorly, it becomes just another disconnected tool. The difference comes down to team alignment and culture, like clear ownership, shared goals, and a willingness to continuously refine how decisions are made.
For ecommerce leaders, this is less about digital transformation as a slogan and more about operational discipline. Simplifying the stack, aligning teams around outcomes, and treating customer experience as a measurable business driver are what sustain revenue growth when conditions are uncertain.
If you would like to find out more, visit: https://www.noibu.com/
Takeaways* Building resilience in revenue and conversion growth is crucial. * Ecommerce leaders face a perfect storm of challenges. * AI is central to enhancing customer experience in ecommerce. * Data-rich environments often lead to insight-poor outcomes. * Connecting the dots between data and decisions is essential. * A strong culture of experimentation fosters innovation. * Tool consolidation can streamline operations and reduce costs. * Visibility in data access is critical for effective decision-making. * Speed of action is influenced by organisational culture. * Establishing a KPI tree helps unify team efforts.
Chapters00:00 Introduction to Ecommerce Challenges
06:04 Real-World Applications of Ecommerce Analytics & Monitoring
11:50 The Role of AI in Ecommerce
17:57 Data Utilisation and Decision Making
24:13 Culture and Team Alignment in Ecommerce
29:56 Practical Strategies for Ecommerce Leaders
SaaS companies moving toward usage-based and hybrid pricing models are discovering that revenue is no longer secured when the contract is signed.
Instead, revenue is earned continuously through product usage, introducing new challenges for finance teams around billing accuracy, revenue visibility, forecasting, and managing increasingly complex cost structures driven by AI-powered products.
In the latest episode of Tech Transformed, host Dana Gardner speaks with Lee Greene, Vice President of Sales at Vayu, about how AI and usage-based pricing are reshaping the economics of SaaS and why many companies are discovering that their pricing strategy is only as strong as the infrastructure behind it.
One idea from the conversation“Pricing strategy is only as strong as the infrastructure behind it.”
What you will learn in this episode* Why usage-based pricing exposes hidden revenue leakage in many SaaS companies * • How AI-driven products introduce unpredictable cost structures and margin pressure * • Why disconnected CRM, product, and ERP systems break revenue visibility * • What finance and revenue teams need to support scalable usage-based billing and forecasting
Why SaaS Economics Are Breaking Away From Fixed SubscriptionsGreene argues that usage-based pricing isn’t simply an emerging trend. It is a response to assumptions that no longer hold true.
Traditional SaaS subscription models were built around predictable costs and relatively stable product usage. AI-driven products have fundamentally changed that equation. Each interaction with an AI-powered system can create variable cost, making static pricing models increasingly difficult to sustain.
This shift is also changing buyer expectations. Customers increasingly resist flat pricing structures and instead prefer models that reflect the value they actually receive. Usage-based pricing aligns economic benefit with real consumption, allowing buyers to justify spend internally while pushing vendors to be accountable for measurable outcomes rather than bundled feature sets.
AI’s Double RoleThe conversation also highlights how AI is introducing a structural challenge for SaaS finance and revenue teams.
Usage-based pricing generates enormous volumes of data across product usage, customer behaviour, and cost inputs. Traditional billing systems were not designed to process this level of complexity.
At the same time, AI is also becoming the only scalable way to manage it. Automated usage tracking, dynamic pricing logic, and real-time billing reconciliation are increasingly necessary to maintain operational accuracy and financial control.
Treating AI solely as a product capability, rather than embedding it into revenue operations, can leave organizations exposed to billing errors, misaligned pricing models, and revenue leakage.
Revenue Management Shifts From Contracts to OperationsOne of Greene’s key observations is that usage-based pricing does not necessarily create revenue leakage. Instead, it reveals problems that already existed.
The difference is visibility.
In traditional SaaS models, revenue was largely secured at the moment of contract signature. In usage-based models, revenue must be earned continuously through product consumption. This means billing accuracy, system integration, and data flow directly influence financial performance.
Disconnected CRM, product, and ERP systems can create gaps that lead to misbilling, delayed revenue recognition, and customer disputes. As a result, the infrastructure supporting revenue operations becomes inseparable from pricing strategy itself.
What SaaS Leaders Must Build to Stay Economically ViableThe discussion concludes with a broader perspective on how SaaS companies must evolve to support this new economic model.
The future belongs to organizations that design their pricing and revenue systems for variability. Pricing models must adapt to changing demand, and the systems behind them must support that flexibility without relying on heavy manual processes.
Automation and no-code AI tools are increasingly enabling finance and revenue teams to adjust pricing models as usage patterns evolve. This agility is not simply about speed. It is about maintaining control in an environment where AI-driven cost structures and product usage can shift rapidly.
Usage-based pricing is doing more than changing how SaaS products are sold. It is reshaping how companies think about value, risk, and revenue itself, making flexibility, intelligent automation, and data-driven decision making central to long-term success.
About VayuVayu helps SaaS companies manage complex usage-based and hybrid revenue models by connecting product usage data, billing systems, and finance infrastructure.
Learn more at:https://www.withvayu.com/
Takeaways* The shift from fixed subscription models to usage-based pricing driven by AI * How AI is both creating and solving new pricing and billing challenges * Why revenue infrastructure plays a critical role in preventing revenue leakage * The importance of flexible pricing models that adapt to demand and usage patterns * The growing role of automation and AI in modern revenue operations
Chapters00:00 – Introduction
02:30 – The economic shift in SaaS: Moving toward usage-based models
05:00 – The role of AI in transforming SaaS pricing and revenue streams
06:47 – Buyer preferences and evolving value quantification
08:38 – Infrastructure's role in supporting flexible billing models
11:49 – How finance teams can shape technology to control revenue
14:24 – Process reengineering and AI-driven automation
17:15 – Adaptable SaaS infrastructure and market signals
20:30 – Preparing for the unknown: sandboxing and scenario modeling
24:49 – Opportunities in connecting SaaS apps and managing data flow
28:54 – Building automated, scalable billing and integration flow
Managing product complexity has become increasingly critical as customers demand greater customisation. Manufacturers face the challenge of connecting disparate data systems effectively. In this episode of Tech Transformed, host Christina Stathopoulos and Laura Beckwith, Director of Product Management at Configit, discuss the complexities of managing product data in manufacturing, focusing on the concept of the digital thread. They explore the challenges manufacturers face in connecting disparate data systems, the importance of customisation, and how a Configuration Lifecycle Management (CLM) approach can provide a reliable foundation for digital threads.
Understanding the Digital ThreadThe digital thread represents the traceability of all decisions and information regarding a product from its inception and throughout its lifecycle. According to Laura Beckwith, the digital thread allows manufacturers to trace decisions made during the requirements stage through to engineering and ultimately to manufacturing and service. This traceability is not just about having data; it’s also about ensuring that various teams and systems can access the right information to facilitate informed decision-making.
Challenges in Implementing the Digital ThreadDespite the promise that digital threads hold, manufacturers face significant challenges in connecting data from multiple systems. Beckwith highlights the example of a smartphone, which undergoes various phases from design to manufacturing. Each phase involves distinct software systems—like CAD for design and ERP for manufacturing—many of which do not communicate well with one another. This lack of integration often leads to inefficiencies, such as manual data entry and miscommunication between teams.
The Impact of Customisation on ComplexityAs customisation becomes the norm, the complexity of managing product data increases exponentially. Beckwith notes that while smartphones may have limited customisations, products like cars offer vast configurability. For instance, when configuring a car, consumers can choose from an extensive array of options. Behind the scenes, however, manufacturers must manage numerous engineering constraints and compliance regulations. This is where the digital thread becomes essential, enabling manufacturers to track and manage these complex configurations effectively.
The Role of Configuration Lifecycle Management (CLM)The upcoming CLM Summit 2026 will focus on mastering customisation complexity and building a reliable data foundation for configurable products. Beckwith explains that a scalable CLM approach is crucial for establishing a reliable digital thread. It ensures that all product configurations, such as the combination of seat heating and memory seats in a car, are tracked accurately. This not only aids in the manufacturing process but also enhances customer service by allowing manufacturers to address issues based on specific configurations.
More broadly, the digital thread provides manufacturers with a framework for managing the growing complexity of modern product development. By enabling seamless communication between data systems and implementing effective CLM practices, organisations can better align engineering, manufacturing, and service functions.
For more information visit: https://configit.com/
Takeaways* The digital thread provides traceability of product decisions. * Manufacturers face challenges due to siloed data systems. * Customisation complexity is increasing in manufacturing. * Digital threads are crucial for configurable products like cars. * CLM helps bridge the gap between engineering and marketing. * Starting small can lead to the successful implementation of digital threads. * Data alignment is essential for effective communication. * Real-world examples illustrate the benefits of digital threads. * A strong digital thread enhances customer experience. * AI can leverage data from digital threads for predictive maintenance.
Chapters00:00 Introduction to Digital Threads in Manufacturing
02:14 Understanding the Digital Thread
06:47 Challenges in Connecting Data Systems
11:12 Customisation, Complexity, and Digital Threads
15:43 The Role of Configuration Lifecycle Management (CLM)
20:23 Real-World Use Case: Implementing Digital Threads
23:42 Guidance for Early Adopters of Digital Threads
As AI systems move rapidly from experimentation into production, organizations are discovering that adoption alone is not the hard part, understanding, governing, and trusting AI in live environments is.
In this episode of the Tech Transformed, Shubhangi Dua speaks with Camden Swita, Head of AI, New Relic, about why AI observability has become a critical requirement for modern enterprises, particularly as agentic AI and AI-driven operations take on increasingly autonomous roles.
The discussion explores how traditional observability models fall short when applied to probabilistic systems, why many AI ops initiatives stall at proof-of-concept, and what security and IT leaders must prioritize to safely scale AI in production.
Be the first to see how intelligent observability takes you beyond dashboards to agentic AI with business impact at New Relic Advance, February 24, 2026.
Why AI Adoption Is Outpacing Operational ReadinessWhile AI adoption is accelerating rapidly, most organizations still lack visibility into what their AI systems are actually doing once deployed. Generative AI is already widely used for natural language querying, coding assistants, customer support bots, and increasingly within IT operations and SRE workflows.
As these systems move into production, new challenges emerge around cost control, governance, performance quality, and trust. Leaders recognize AI’s potential value, but without deep observability, they struggle to determine whether AI-enabled systems are delivering consistent outcomes or introducing hidden operational and security risks.
How Observability Must Evolve for Agentic AI and AI OpsThe episode then examines how observability itself must evolve to support agentic and autonomous AI systems. While core observability principles still apply, AI introduces a new layer of complexity that requires visibility into model behavior, agent decision-making, and multi-step workflows.
Modern AI observability extends traditional application performance monitoring by capturing telemetry from LLM interactions, agent orchestration layers, and automated evaluations of output quality against intended use cases.
Without this visibility, teams are effectively operating blind, unable to diagnose failures, validate compliance, or confidently deploy AI at scale. At the same time, AI is increasingly being embedded into observability platforms to reduce noise, accelerate root cause analysis, and improve incident response.
Making Agentic AI Work in PracticeSuccessful adoption starts with low-risk, high-friction tasks such as incident triage, dashboard interpretation, and runbook summarization, rather than fully autonomous remediation. These use cases deliver immediate productivity gains while preserving human oversight. Over time, stronger feedback loops, better context management, and human-in-the-loop learning allow agents to become more reliable and useful. Looking ahead, Camden predicts that 2026 will be a turning point for agentic AI in production, driven by maturing AI observability platforms, richer semantic data, and knowledge graphs that connect technical telemetry to real business outcomes.
Listen to Are “Vibe-Coded” Systems the Next Big Risk to Enterprise Stability?
When Vibe Code Breaks OpsAI-generated code is pushing prototypes into production faster than ops can cope. How observability becomes the gatekeeper for enterprise resilience.
Key Takeaways1. AI adoption is accelerating in enterprise environments. 2. Organizations face complexities in productionizing AI features. 3. Natural language querying is a common AI application. 4. AI agents are increasingly used in IT operations. 5. Observability is crucial for understanding AI systems. 6. Traditional observability solutions are evolving to include AI monitoring. 7. Incident response teams struggle with alert noise and context gathering. 8. AI can assist in incident management and root cause analysis. 9. Future trends include more reliable AI agents and monitoring solutions. 10. Organizations need to invest in AI observability to succeed.
Chapters1. 01:20 The Current State of AI Adoption 2. 02:28 Purposeful AI Usage in Organizations 3. 04:40 Observability in the Age of AI 4. 08:05 Evolving Observability Solutions 5. 11:36 Challenges in Incident Response 6. 16:04 Integrating AI in Operations 7. 23:33 Future Trends in AI Monitoring 8. 30:29 Investment Strategies for AI Solutions
ArtificialIntelligence #EnterpriseAI #GenerativeAI #AgenticAI #AIAgents #AIObservability #AIInProduction #AIOps #AISecurity #AIGovernance #ModelMonitoring #LLMOps #ITOperations #SRE #DevOps #IncidentResponse #RootCauseAnalysis #DigitalTransformation #Automation #FutureOfAI
Did you know that on average, 35 per cent of calls to automotive dealerships go unanswered? In today’s competitive market, missed calls mean missed sales and dealerships are turning to AI and analytics to fix this.
In this episode of Tech Transformed, host Jon Arnold and Ben Chodor, Chief Executive Officer of CallRevu, about how AI is reshaping the way dealerships handle calls, manage repair orders, and engage with customers throughout their journey. They explore the role of real-time analytics in improving interactions, the importance of answering every incoming call, and why AI has become essential in modern dealership operations.
Customer Experience Has ChangedThe customer journey is no longer a simple transaction. Today, it spans pre-purchase research, purchasing, and post-purchase support. Chodor highlights that every interaction matters; customers now expect engagement and guidance at every stage, not just information.
Competition in automotive sales is fierce, and customers expect fast responses. Chodor notes that dealerships leveraging AI can provide updates on service times, answer inquiries promptly, and ensure no customer engagement is lost. Real-time insights also empower managers to make better operational decisions and improve the overall customer experience.
AI in Automotive DealershipsAI technology is changing the way dealerships operate. Chodor discusses how CallRevu’s technology listens to every sales and service call, providing real-time analytics to dealerships. This capability allows managers to intervene in calls, ensuring that customer concerns are addressed promptly. For instance, if a call goes unanswered, the system can alert management, enabling them to engage with the customer immediately, thus reducing missed opportunities.
The integration of AI and analytics in automotive dealerships is not just about improving sales; it's about transforming the entire customer experience. From ensuring every call is answered to providing real-time insights for better decision-making, technology is reshaping how dealerships engage with customers. As the automotive industry continues to evolve, those who prioritise customer experience through innovative solutions will undoubtedly lead the way.
If you would like to find out more information, go to https://www.callrevu.com/
Takeaways* AI enhances customer engagement in automotive dealerships. * Real-time analytics can significantly improve communication. * Every call to a dealership is crucial for sales. * AI helps reduce the number of calls going to voicemail. * Dealerships must adapt to a more competitive landscape. * Customer experience is more than just selling cars. * AI can provide instant responses to customer inquiries. * Training tools powered by AI can improve sales techniques. * The automotive industry is shifting towards data-driven decisions. * AI is essential for modern dealership operations.
Chapters00:00 Introduction to Customer Experience in Automotive Dealerships
05:00 The Role of AI in Enhancing Communication
10:08 Transforming Customer Engagement with Real-Time Analytics
15:03 The Importance of Incoming Calls and Tracking
19:55 AI's Impact on the Automotive Industry
24:49 Future Trends in Automotive Technology
Podcast: Tech Transformed Podcast
Guest: Manesh Tailor, EMEA Field CTO, New Relic
Host: Shubhangi Dua, B2B Tech Journalist, EM360Tech
AI-driven development has become obsessive recently, with vibe-coding becoming more common and accelerating innovation at an unprecedented rate. This, however, is also leading to a substantial increase in costly outages. Many organisations do not fully grasp the repercussions until their customers are affected.
In this episode of the Tech Transformed Podcast, EM360Tech’s Podcast Producer and B2B Tech Journalist, Shubhangi Dua, spoke with Manesh Tailor, EMEA Field CTO at New Relic, about why AI-generated code, also called vibe-coding, rapid prototyping, and a focus on speed create dangerous gaps. They also talked about why full-stack observability is now crucial for operational resilience in 2026 and beyond.
AI Vibe Code Prioritising Speed over StabilityAI has changed how software is built. Problems are solved faster, prototypes are created in hours, and proofs-of-concept (POC) swiftly reach production. But this speed comes with drawbacks.
“These prototypes, these POCs, make it to production very readily,” Tailor explained. “Because they work—and they work very quickly.”
In the past, the time needed to design and implement a solution served as a natural filter. However, the barrier has now disappeared.
Tailor tells Dua: “The problem occurs, the solution is quick, and these things get out into production super, super fast. Now you’ve got something that wasn’t necessarily designed well.”
The outcome is that the new systems work but do not scale. They lack operational resilience and greatly increase the cognitive load on engineering teams.
New Relic's research indicates that in EMEA alone:
- The annual median cost of high-impact IT outages for EMEA businesses is $102 million per year
- Downtime costs EMEA businesses an average of $2 million per hour
- More than a third (37%) of EMEA businesses experience high-impact outages weekly or more often.
Essentially, AI-driven development heightens risks and increases blind spots. “There are unrealised problems that take longer to solve—and they occur more often,” Tailor noted. This is because many AI-generated solutions overlook operability, scaling, or long-term maintenance.
Modern architectures were already complex before AI came along. Microservices, SaaS dependencies, and distributed systems scatter visibility across the stack.
“We’ve got more solutions, more technology, more unknowns, all moving faster,” he tells Dua. “That’s generated more data, more noise—and more blind spots.”
Traditional monitoring tools were built for known issues—predefined components, predictable dependencies, and static systems. “Monitoring was about what you already understood,” Tailor explained. “Observability is about the unknown unknowns.”
AI-generated code complicates the situation because teams often lack detailed knowledge of how that code was created, how components interact, or how dependencies change over time.
This is where full-stack observability becomes essential—not as a standalone tool, but as a coordinated capability that connects signals across applications, infrastructure, data, and AI systems in real time.
Also Watch: How Do AI and Observability Redefine Application Performance?
Reactive to Proactive: The Role of AI in ObservabilityIronically, the same AI that increases complexity is also necessary to manage it. According to New Relic data, 96 per cent of organisations plan to adopt AI monitoring and 84 per cent plan to implement AIOps by 2028.
However, Tailor stresses that success relies on using AI to enhance—rather than replace—human expertise. “We have to leverage AI to establish baselines much faster,” he said. “But humans still bring experience and judgment that machines don’t have.”
AI allows teams to shift from responding to known patterns to proactively spotting anomalies before they turn into customer-facing incidents.
Beyond uptime and performance, observability is becoming a regulatory requirement. “If it’s not observed, then it’s rogue,” Tailor warned.
New regulations like the EU AI Act and ISO 42001 will require organisations to show visibility into AI systems, decision-making processes, and operational behaviour. “You won’t be allowed to operate AI solutions without the right level of observability,” he added.
The 2026 Takeaway: Observability is Essential for AIAs AI-driven development becomes the norm, Tailor’s message to CIOs, CTOs, and CDOs is: “Observability isn’t an option. Without it, your AI strategy simply won’t work.”
Organisations that neglect to invest in centralised, full-stack observability risk more than outages—they risk compliance failures, security issues, and rising operational costs.
“Otherwise,” Tailor stated, “you will limit the ability to benefit from your AI strategy.”
To learn more, visit NewRelic.com or listen to the full episode of the Tech Transformed podcast at EM360Tech.com.
Also Watch: How Can AI Bridge the Gap from Observability to Understandability?
Takeaways1. If you don't get your observability house in order, all the grand plans with AI may be at risk. 2. Speed has been favoured over good governance and engineering standards. 3. Observability is about understanding the relationship between components, not just monitoring known issues. 4. AI can help establish baselines faster in a rapidly changing environment. 5. Without observability, you can't make your AI strategy work.
Chapters1. 00:00 Introduction to AI and Observability 2. 01:11 The Risks of Rapid Software Development 3. 04:21 Understanding the Cost of Outages 4. 06:30 Blind Spots in AI-Driven Systems 5. 11:29 Transitioning to Full-Stack Observability 6. 13:58 Moving from Reactive to Proactive Monitoring 7. 18:54 Real-World Applications of AI Monitoring 8. 19:51 The Future of AI and Observability
Observability #AIOps #AIDrivenDevelopment #FullStackObservability #ITOutages #VibeCoding #AIinProduction #DevOps #NewRelic #TechPodcast
In a world where climate change is reshaping the way we grow, transport, and consume the things we rely on, understanding the first mile of supply chains has never been more critical. That’s the stage where over 60 per cent of risks arise, yet it remains the hardest to measure and manage. In a recent episode of Tech Transform, Trisha Pillay sits down with Jonathan Horn, co-founder and CEO of Treefera, to explore how artificial intelligence is providing clarity, actionable insights, and sustainable solutions for this complex ecosystem.
The First Mile and Climate PressuresHorn’s perspective comes from a mix of experience: growing up on a farm, studying physics, and working in investment banking. That combination gives him a lens on both the natural systems that underpin agriculture and the data-driven tools that help manage risk.
Extreme weather patterns like droughts, heavy rainfall, and hurricanes are putting pressure on crops such as cocoa, coffee, wheat, and soy. The consequences ripple outward: production costs rise, commodity prices fluctuate, and supply chains become less predictable. A simple example illustrates this clearly: certain chocolate biscuits in the UK have moved from being chocolate-filled to chocolate-flavoured, reflecting disruptions in cocoa production in West Africa caused by extreme weather and disease. These changes are not isolated; they affect global markets and everyday products.
Turning Data into Actionable InsightsAI can help make sense of the complexity. Treefera, for instance, combines satellite imagery, sensor data, and other datasets to provide insights on crop yields, supply risks, and climate impacts. Horn describes it like a car dashboard: “You don’t need to know every technical detail to understand what’s happening and act accordingly.”
The value of AI lies not in flashy algorithms but in its ability to translate raw data into practical decision-making tools. By analysing multiple signals from weather events to agricultural output, AI can highlight trends, flag potential disruptions, and support planning for traders, insurers, or supply chain managers. The goal is clarity and action, not simply more information.
Data, Regulation, and Responsible UseAlongside operational complexity, organisations face questions about data governance. Emerging regulations such as the EU AI Act aim to ensure AI is used responsibly, and companies need to maintain control over proprietary information while leveraging technology effectively. Horn stresses the importance of frugal, transparent AI applications that produce meaningful insights without unnecessary complexity.
In practice, this means balancing innovation with compliance: using AI to understand risks, improve planning, and support sustainability without overstating its capabilities or creating new vulnerabilities. The conversation underlines a key point: the impact of AI is most tangible when it’s applied thoughtfully, in service of real-world decisions.
In short, AI is helping organisations navigate the increasingly unpredictable intersection of climate, risk, and supply chain complexity. The first mile, long a blind spot, is becoming visible not through hype or marketing claims, but through practical, data-driven insight that helps people respond to the world as it is, not as we wish it to be.
Takeaways* AI can significantly improve the management of supply chains. * Climate change is causing more extreme weather patterns, affecting agriculture. * Data sovereignty is crucial for companies to maintain control over their proprietary data. * AI native businesses leverage AI as a core component of their operations. * The EU AI Act aims to create a framework for responsible AI use. * AI can help simplify complex information into actionable insights. * Frugal AI usage can lead to more efficient operations. * The evolution of AI technologies includes advancements in large language models. * Understanding the risks associated with climate change is essential for supply chain management. * Companies must balance compliance with innovation in AI applications.
Chapters00:00 Introduction to AI in Supply Chains
04:40 Navigating Climate Challenges with AI
09:40 AI-Native Business Models
13:57 The Evolution of AI Technologies
18:16 Understanding Data Sovereignty
21:54 Balancing AI Regulation and Innovation
25:48 Future of AI in Sustainability
About John HornJonathan Horn is the founder of Treefera, an AI platform delivering accurate, auditable data to support carbon offsetting and nature-positive initiatives for landowners, investors, governments, NGOs, scientists, and marketplace participants. An innovative thinker and problem solver, he holds a PhD in Theoretical Fluid Dynamics and has extensive experience designing and implementing AI and data analytics solutions at scale. Jonathan has also applied data mesh principles to enable distributed, data-driven organisations, with a background in optimising banking operations through advanced data and AI systems.
Mass customisation has long been the holy grail for industrial manufacturers, offering the ability to provide highly tailored products while maintaining efficiency, scalability, and profitability. However, as products become increasingly complex, traditional methods of managing configurations are starting to reveal their limitations.
In a recent episode of Tech Transformed, host Christina Stathopoulos, Founder of Dare to Data, spoke with Stella d’Ambrumenil, Product Manager at Configit, about the operational realities and future potential of generative AI technology in manufacturing.
The Challenge of ComplexityModern manufacturers often operate somewhere between make-to-order and assemble-to-order models. While these approaches allow flexibility, they also expose companies to a major problem, such as fragmented configuration processes. Sales teams, engineers, and manufacturing units may all handle different aspects of customisation separately, relying on spreadsheets or outdated product documentation. The result is inefficiency, errors, and an inability to scale effectively.
“The problem isn’t just that you have lots of options,” Stella explains. “It’s that the knowledge about those options is scattered. If configuration is handled differently across departments, you inevitably get mistakes and lost time.”
Configit Ace® Prompt: Bridging the GapEnter Configit Ace® Prompt, the latest tool designed to tackle this very problem. At its core, Configit Ace® Prompt converts unstructured data into structured configuration logic that can be used across all departments. Formalising configuration knowledge ensures that customisation is accurate, repeatable, and manageable.
This approach not only reduces errors but also democratizes access to critical product information. Engineers, product managers, and sales teams no longer need to interpret fragmented data manually — they can work from a single source of truth. Early adopters report significant time savings, fewer mistakes, and smoother collaboration.
Why Configuration Lifecycle Management MattersConfigit Ace® Prompt is a key enabler of Configuration Lifecycle Management (CLM). CLM is an approach to maintaining consistent data and processes across the entire product lifecycle — from design and engineering to manufacturing and service. This is crucial for companies seeking to scale customisation without creating chaos in operations.
By adding generative AI technology, manufacturers can implement a CLM approach faster to automate logic creation, catch configuration errors early, and ensure that complex products are delivered efficiently.
Looking Ahead: CLM Summit 2026For professionals interested in deepening their understanding of configuration management, Configit’s CLM Summit 2026 — an online event scheduled for May 6 & 7 - will provide insights into best practices, advanced strategies, and tools like Configit Ace® Prompt. It’s an opportunity to see how companies can leverage configuration management to stay competitive in a world of growing product complexity.
For more insights, visit: configit.com
Takeaways* Manufacturers face increasing challenges with product complexity and customisation demands. * Configit Ace® Prompt helps convert unstructured product knowledge into usable configuration logic. * Configuration Lifecycle Management (CLM) is crucial for establishing and maintaining a shared source of truth. * Product data fragmentation leads to inefficiencies in manufacturing processes. * AI can assist in catching errors in configuration data. * The tool aims to lower the barrier to entry for data consolidation. * Excel remains a popular tool, but Configit Ace® Prompt offers a familiar interface. * Early beta testers have reported significant time savings with Configit Ace® Prompt. * Generative AI has potential applications in guided configuration and data analysis. * The upcoming CLM Summit will provide insights into product configuration management.
Chapters00:00 Introduction to Tech Transformed and Configit
02:48 Understanding Product Complexity in Manufacturing
05:54 The Role of Configit Ace® Prompt in Configuration Management
08:53 Configuration Lifecycle Management Explained
11:52 The Importance of Data Consistency and Cleanup
15:14 User Experience and Adoption of Configit Ace® Prompt
17:54 Generative AI and Its Future Applications
21:07 Conclusion and Future Events
About ConfigitAt Configit, we help our customers globally to master the challenges of getting configurable products to market faster, with higher quality and engineered at lower costs. As a pioneer of Configuration Lifecycle Management (CLM), we have been instrumental in driving the adoption of CLM solutions globally. Trusted by the world’s largest manufacturing companies for their mission-critical functions, our advanced configuration platform built on patented Virtual Tabulation® technology handles the most complex products on the market. Our customers include ABB, Jaguar Land Rover, John Deere, Grundfos, Vestas, Siemens, Danfoss amongst others.
As organisations navigate the rapid rise of AI, the challenge is no longer simply acquiring technology; it’s preparing people to use it effectively. Many companies are realising that access to AI tools alone doesn’t translate into business impact. Employees need meaningful opportunities to develop skills that can be applied immediately, helping teams work smarter and make better decisions.
In this episode of Tech Transformed, Christina Stathopoulos, Founder of Dare to Data, speaks with Gary Eimerman, Chief Learning Officer at Multiverse, about the pressing challenge of closing the AI and data skills gap in the workforce. They explore how organisations can build an AI-ready workforce, focusing on non-technical employees and the importance of a skills-first approach to learning.
The Skills-First ApproachMultiverse champions a skills-first approach to upskilling employees in AI and data, asserting that this targeted training drives measurable business impact, including increased productivity, revenue growth, and time savings. This strategy moves beyond general AI literacy to focus on practical, applied learning. By diagnosing both organisational needs and individual skill levels, the approach identifies gaps and prescribes tailored, project-based learning experiences. Employees don’t just complete modules in isolation; they work on real-world projects that apply the skills they are learning from day one, reinforcing retention and ensuring that training contributes to tangible outcomes.
Learning in the AI EraGary explains that learning in the AI era is not simply about providing tools or access to content; it’s about driving behaviour change, aligning learning with business outcomes, and embedding a culture of continuous skill development. As AI reshapes both the work we do and the way we learn, organisations that invest in people-first strategies position themselves to thrive rather than merely adapt. This conversation demonstrates that the future of work is always on learning, and that meaningful investment in AI and data skills is no longer optional; it’s a critical driver of business success.
Unlocking Workforce PotentialBy combining practical, applied training with ongoing support and measurable outcomes, companies can not only close the AI skills gap but also unlock the full potential of their workforce in an era defined by rapid technological change.
Takeaways* Technology alone is never enough; people must be invested in. * Reskilling is a necessity due to technological disruption. * Organisations must focus on human behaviour change, not just software deployment. * A skills-first approach is critical for effective learning. * Learning should be project-based and applied immediately. * Non-technical roles are increasingly adopting AI tools. * Creating time and space for learning is essential. * Highlighting success stories builds confidence in using AI. * Measuring impact through metrics like revenue per employee is vital. * The future of work requires a cultural shift towards continuous learning.
Chapters00:00 Closing the AI and Data Skills Gap
02:02 Challenges in Building an AI-Ready Workforce
06:06 The Skills First Approach to Learning
10:04 Supporting Non-Technical Employees in AI
13:46 Measuring the Impact of AI Skills Investment
18:13 The Evolution of Learning in the AI Era
22:59 Preparing for the Future of Work
About MultiverseMultiverse is the upskilling platform for AI and tech adoption. Multiverse has partnered with over 1,500 companies to deliver a new kind of learning that’s transforming the workforce through tech skills.
Multiverse apprenticeships are for people of any age or career stage and focus on critical AI, data and tech skills. Multiverse learners have driven $2bn + ROI for their employers, using the skills they’ve learned to improve productivity and measurable performance.
For more information, visit www.multiverse.io
In the automotive industry, trust and transparency are no longer optional; they have become key components. Dealerships that communicate clearly and responsibly with their customers strengthen relationships and improve overall experiences. In this episode of Tech Transformed, host Trisha Pillay speaks with Sean Barrett, Chief Information Officer at CallRevu, about how dealerships can navigate the changing landscape of communication while maintaining accountability, compliance and operational resilience.
The Evolution of Dealership CommunicationCommunication has always been at the heart of dealership operations. The phone system was once the primary lifeline between customers and dealerships, giving managers the visibility needed to ensure interactions were handled correctly. Today, communication extends far beyond the phone. SMS, MMS, instant messaging, and other channels allow customers to engage in multiple ways.
Sean explains how integrating these channels into a single technology platform provides managers with a clear view of all interactions, ensuring employees follow policies and customers receive the attention they deserve. This approach strengthens trust and improves the overall customer experience.
Compliance and Data Privacy in Automotive CommunicationAlongside multi-channel communication, compliance and data privacy are critical. Regulations like GDPR and UN R155 require dealerships to protect customer data while maintaining seamless communication. Transparent practices, combined with adherence to regional rules, help build trust and protect both customers and the dealership’s reputation. Observing patterns in customer interactions also allows dealerships to make informed decisions, improve processes, and enhance service quality. Using these data insights, dealerships can make communication more effective and meaningful for every customer.
Infrastructure That Keeps Dealerships OperationalReliable infrastructure underpins all communication efforts. Sean shares how dealerships can prepare for unexpected disruptions with geo-redundant systems, cloud-based platforms, and layered internet backups, including options like Starlink or fibre connections. These measures ensure dealerships stay operational, customers can reach them without interruption, and business continuity is maintained.
Preparing for Emerging Communication ChannelsAs new channels emerge, proactive preparation is key. Dealerships that view communication as an investment, rather than a cost, position themselves for long-term success. Monitoring trends, adapting quickly, and fostering transparency help maintain strong customer relationships even as expectations evolve.
Training and Staff DevelopmentStaff development is a critical component of a communication strategy. By using insights from technology platforms, dealerships can guide employee training, build accountability, and create a culture of learning. Confident, well-trained teams contribute to consistent, high-quality interactions that enhance customer trust.
Success in automotive communication isn’t just about adopting the latest tools—it’s about building systems and practices that protect customers, support employees, and foster trust at every touchpoint. Sean Barrett’s insights provide a roadmap for dealerships aiming to elevate communication strategies, improve customer satisfaction, and maintain resilience in an increasingly connected world.
Learn more: callrevu.com
Takeaways
- Trust and transparency are essential for customer relationships.
- The evolution of communication systems has introduced multi-channel interactions.
- Compliance challenges vary across regions and regulations.
- AI can provide deeper insights into customer interactions.
- Training with AI can enhance employee performance and accountability.
- Dealerships should view communication as an investment, not an expense.
- Data insights are crucial for improving customer experience.
- Emerging communication channels require proactive preparation.
- A risk-free training environment can foster employee growth.
- Customer lifetime value is realised through effective data utilisation.
Chapters00:00 Introduction to Trust and Transparency in Automotive Communication
03:06 Evolution of Dealership Communication Systems
05:02 Building Reliable Communication Infrastructure
07:13 Navigating Compliance Challenges in Automotive
09:12 Preparing for Emerging Communication Channels
11:15 The Role of AI in Automotive Communication
14:10 Bridging the Gap Between AI and Human Interaction
16:35 Success Stories and Training Innovations
18:22 Practical Actions for Dealerships
22:14 Conclusion and Key Takeaways
About CallRevuCallRevu is the leading communication intelligence platform built for automotive retail, empowering dealerships to take control of every conversation, from the first ring to the final result. Its unified solution combines a hosted phone system, call monitoring, performance training, and reputation management fueled by AI-powered analytics that turn every customer interaction into actionable intelligence.
Founded in a dealership in 2008, CallRevu was created by the industry, for the industry. We deliver the tools dealerships need to drive revenue, improve operations, and deliver exceptional customer experiences.
In a world where customer expectations evolve faster than ever, organisations are rethinking how they manage and leverage data. Legacy, monolithic Customer Data Platforms (CDPs) are increasingly challenged by rigidity, slow adaptability, and regulatory pressures. In this episode of Tech Transformed, Christina Stathopoulos, Founder of Dare to Data, speaks with Joe Pulickal, Director of Product Management at Uniphore, about the shift to composable CDPs and what it means for modern marketing technology.
Moving Away from Monolithic CDPsOrganisations are moving away from rigid, all-in-one CDPs as regulations around data privacy, consent, and cross-border data flows intensify. Joe explains that companies can no longer rely on systems that lock them into a single architecture or make compliance retrofitting difficult. Data governance, consent management, and data sovereignty have become critical considerations in every technology decision, forcing leaders to rethink the underlying structure of their CDPs.
Challenges in Composable SystemsWhile composable CDPs offer flexibility, they introduce new challenges. Organisations must define ownership and accountability within modular systems to prevent fragmentation and ensure consistent data quality. Leadership must consider how compute, storage, and access are distributed across modules while maintaining compliance and security standards. Joe notes that without clarity on ownership, organisations risk operational inefficiency and weakened governance.
Flexibility and Modularity in Data ManagementThe core advantage of composable architectures lies in modularity. By decoupling components from data ingestion to activation, organisations gain the freedom to innovate without being constrained by a monolithic platform. Joe emphasises: “You need flexibility in where data lives, how compute happens, ultimately doubling down on sovereignty, security, and that composable idea that initially started with data.” This approach allows teams to adopt new tools, scale selectively, and respond to changing business or regulatory requirements with agility.
Embracing First-Party Data StrategiesThe shift to first-party data strategies is essential in today’s marketing landscape. With third-party cookies being phased out and privacy regulations tightening, companies must rely on direct, trusted data from their customers. Composable CDPs provide the framework to centralise first-party data while giving teams the ability to personalise experiences, maintain compliance, and safeguard trust. Joe highlights that organisations need to view data not just as an asset, but as a responsibility, balancing customer value with ethical management.
Here are what leaders can do:
- Rethink data architecture: Move from monolithic to composable systems to gain flexibility, scalability, and regulatory alignment.
- Prioritise governance: Define ownership, consent management, and security practices across modular components.
- Focus on first-party data: Build direct customer relationships and leverage trusted data responsibly.
- Embrace modularity: Enable innovation, adaptability, and resilience in data management through composable design.
This episode offers practical insights for leaders navigating the transition from traditional CDPs to composable architectures. It highlights how thoughtful design, governance, and first-party data strategies empower organisations to act with agility, comply with regulations, and deliver better customer experiences.
For more information, book a demo with Uniphore.
Takeaways* Organisations are moving away from rigid monolithic CDPs due to regulatory pressures. * Composable architectures offer flexibility and modularity in data management. * The shift to first-party data strategies is essential in the current landscape. * Data governance and consent management are critical in modern marketing. * Organisations face challenges in defining ownership within composable systems. * Uniphore supports hybrid deployment options for data management. * AI integration is crucial for enhancing CDP functionalities. * Flexibility in architecture helps avoid vendor lock-in. * People and processes are as important as technology in CDP implementation. * Clear alignment on objectives is necessary for successful transitions.
Chapters00:00 The Shift from Monolithic CDPs to Composable Architectures
08:18 Understanding the Limitations of Monolithic CDPs
10:59 Rethinking First-Party Data Strategies
17:44 Challenges in Implementing Composable CDPs
21:18 Uniphore Role in Composable Marketing Intelligence
25:28 Future Considerations for CDP Ecosystems
About UniphoreUniphore is a B2B artificial intelligence (AI) company that provides a full-stack Business AI Cloud platform for enterprises to manage customer interactions, sales, marketing, and internal operations. Founded in 2008 and incubated at IIT Madras, Uniphore has dual headquarters in Palo Alto, California, and Chennai, India, and reached unicorn status with a $2.5 billion valuation in 2022. The platform is designed to be sovereign, composable, and secure, allowing businesses to connect diverse data sources, leverage AI models, and deploy AI agents across the enterprise. Uniphore’s offerings include Customer Service AI for agent guidance and analytics, Sales AI for real-time insights, Marketing AI with CDP capabilities, and People AI for HR automation.
As companies rethink how they provide customer experiences (CX), a new form of AI capability, agentic AI, is quickly changing how work is accomplished in contact centres.
In the recent episode of the Tech Transformed podcast, Dialpad Lead Product Manager Calvin Hohener sits down with host Jon Arnold, Principal at J Arnold & Associates. They discuss the transition from legacy chatbots to more autonomous agents capable of completing tasks and improving customer interactions.
The conversation highlights the importance of understanding the technology's impact on enterprise architecture, the need for clean data, and the strategic implications for C-level executives. Hohener emphasises the importance of starting with clear use cases and working closely with vendors to maximise the potential of AI in business operations.
From Legacy Chatbots to Agentic AIMost people have used chatbots and found them lacking. Hohener explains why: earlier conversational AI was based on retrieval-augmented generation (RAG). These systems could take user input, search a knowledge base or the internet, and provide an answer. This was helpful for customer service queries, but limited.
“Previous AI models could retrieve and return information, but now we’re moving into a new phase with agentic AI.” Agentic AI can take action rather than just providing information.
For AI agents to succeed, organisations must first organise their data. “How your internal knowledge is structured is crucial. Even if the data is unorganised, you need to know its location and ensure it’s clean,” stated Hohener.
Agentic systems depend on internal knowledge, including knowledge base articles, CRM notes, and process documentation. If this foundation is disordered, the agent’s output will not be reliable.
This isn’t about achieving ideal data cleanliness from the start; it’s about knowing what information exists, where it is, and whether it can be trusted. If an AI agent bases its decisions on outdated, conflicting, or incomplete content, it will struggle to perform tasks aptly, regardless of how sophisticated the model is. Enterprises need at least basic clarity about which systems hold which knowledge, who is responsible for them, and whether there is consistency across sources.
Hohener noted that organisations often overlook how quickly conflicting information can undermine an otherwise well-designed agent. A single outdated procedure or mismatched policy in a knowledge repository can lead an AI to produce incorrect results or halt during workflow execution.
Keeping internal content clean, deduplicated, and consistent gives the agent a reliable, valid source. This reliability becomes crucial when AI starts taking meaningful actions, not just providing answers.
By focusing on data readiness early, enterprises not only reduce deployment obstacles but also set the stage for scaling agentic AI across more complex processes. In many ways, preparing data isn’t just a technical task; it’s an organisational one.
How Human Agents Work with AI Agents?The Dialpad Lead Product Manager noted that human roles, too, will evolve with agentic AI entering the contact centre. For instance, human agents will take on more of an advisory role—reviewing conversation traces and helping adjust the models.”
Instead of just resolving customer issues, they will help refine and oversee AI workflows. This includes reviewing conversation logs, noting where an AI agent may have misinterpreted intent, and providing feedback to improve the models.
This mentor-mentee relationship between human and digital agents becomes crucial as organisations increase automation. Human agents bring domain knowledge, contextual judgment, and the ability to handle unique situations, all of which help the AI improve over time. In return, digital agents reduce the repetitive workload and allow humans to engage in higher-level thinking.
Takeaways* The time is now for adopting agentic AI solutions. * Agentic AI represents a significant shift in customer experience technology. * Legacy chatbots have limitations that agentic AI can overcome. * Real-world applications of agentic AI include mundane tasks like scheduling and verification. * Quantifying time savings is crucial for measuring ROI with AI. * AI agents can improve customer satisfaction metrics when implemented correctly. * Data organisation is essential for effective AI deployment. * Human agents will focus on more complex cases as AI handles routine tasks. * C-level executives should view AI as a strategic investment. * Collaboration with reputable vendors is key to successful AI implementation.
Chapters* 00:00 Introduction to Agentic AI * 05:10 Evolution Beyond Legacy Chatbots * 11:44 Real-World Applications of Agentic AI * 15:38 Impact on Enterprise Architecture * 21:41 Strategic Considerations for C-Level Executives
Client service teams are at a breaking point. Margins are shrinking, the demand keeps rising, and much of the day is consumed by work that doesn’t move the needle. As a result, skilled people often spend hours reconciling spreadsheets, re-entering the same data across multiple systems, and chasing updates, time that should be spent on the work clients actually pay for. Every hour lost to manual admin is an hour of revenue slipping away. In this day and age, that’s a hit no business can afford.
AI isn’t just a buzzword here; it’s a practical lever. It can cut through the repetitive tasks that slow teams down, surface the information they need instantly, and free them to focus on high-value work. The companies winning aren’t replacing staff; they’re removing the obstacles that keep people from doing their best. In a world where speed and accuracy matter more than ever, ignoring that shift isn’t optional.
In the latest episode of Tech Transformed, hosted by Christina Stathopolus, founder of Dare to Data, Daniel Mackey, CEO of Teamwork.com, discussed how AI is reshaping the daily operations of client service teams. From automating repetitive admin tasks to surfacing critical information faster, AI is giving teams the bandwidth to focus on the work that truly drives value for clients.
AI and Business Transformation in PracticeDuring the conversation, Mackey highlighted how AI is reshaping business operations, emphasising efficiency and productivity rather than job displacement. “AI has transformed our company,” he noted, pointing to tangible improvements across workflow and project management. Teams are now able to focus on strategic initiatives, leaving repetitive tasks to intelligent systems.
The Teamwork.com CEO also shared a recent example from a government agency that integrated AI into its processes. By automating routine administrative work, the agency experienced better resource allocation and improved project outcomes. “They’re more efficient, higher quality,” Mackey said. “AI allows them to focus on the bigger parts of the business.”
Rethinking Productivity and Client DeliveryOne of the challenges in the industry is that most AI features are added onto existing tools that weren’t designed for client services. Mackey discussed how TeamworkAI addresses this gap. Built into a platform designed specifically for managing client services end-to-end, TeamworkAI connects projects, people, and profits in one system.
By integrating AI directly into client delivery workflows, organisations can streamline project management, reduce manual reporting, and ensure that technology enhances rather than disrupts service delivery. This approach allows businesses to use technology strategically, rather than simply automating isolated tasks.
Technology and the Future of WorkThe discussion also touched on the broader impact of AI on traditional business models. Organisations that adopt AI thoughtfully can improve their internal processes, freeing employees from repetitive tasks and enabling them to contribute to higher-value projects. Mackey emphasised that the goal isn’t just automation, it’s profitable client delivery. AI can unlock both time and insight, allowing businesses to prioritise the most impactful work.
AI is redefining how businesses allocate resources, manage projects, and deliver value to clients. By eliminating repetitive work and connecting projects, people, and profits, technologies like TeamworkAI show how AI can drive efficiency, productivity, and business transformation without sacrificing the human element.
To discover how your team can leverage TeamworkAI to deliver seamless projects, smarter resourcing, and stronger profits, visit teamwork.com
Takeaways* Profitable client delivery now depends on AI – learn what actually works before investing in the wrong tools. * Efficiency gains from AI lead directly to better performance, improving output and reducing wasted effort. * AI and automation free up resources, allowing organisations to focus on strategic priorities. * Technology adoption reshapes business models, ensuring organisations remain competitive in a rapidly changing landscape. * AI integration is critical for competitiveness; without it, margins and business outcomes could be at risk.
Chapters-00:00 Introduction to Client Services and AI
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3:00 The Role of AI in Streamlining Workflows
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9:00 Centralising Data for Efficiency
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15:00 Maintaining Human-Centred Client Relationships
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21:00 Future of Technology in Client Services
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27:00 Takeaways for CTOs and CISOs
About Teamwork.comTeamwork.com is an AI-powered project and resource management platform designed to keep client projects running smoothly, simplify resource planning, and help businesses protect their margins.
Headquartered in Cork, Ireland, Teamwork.com employs more than 200 people worldwide, with additional hubs in Denver, Gdańsk, and Belfast. The company supports teams across industries with tools that make collaboration clearer, workflows more efficient, and delivery more predictable.
With the rapid evolution of Generative AI, customer experience (CX) is evolving rapidly, too. In a recent episode of the Tech Transformed podcast, Mike Gozzo, Chief Product and Technology Officer at Ada, sat down with host Christina Stathopoulos, Founder of Dare to Data. They talked about how generative AI is changing business-to-customer interactions.
“I view it not just as a business opportunity, but we are here to solve a problem that has existed as long as commerce has,” Gozzo said. He emphasised that AI's goal isn’t just efficiency. It is about building trust and clearly understanding customer needs to allow productive interactions.
Artificial intelligence, he noted, “has really enabled what used to be much more costly to happen at scale.” The Ada Chief Product and Technology Officer pointed out that the best customer experiences are highly personalised. Comparing it to arriving at a luxury hotel where the staff already knows your name, even on your first visit. He noted that modern AI aims to make such experiences, which were once only for a select few, common for everyone.
Looking to the future, Gozzo tells Stathopoulos he believes generative AI will foster more engagement between customers and brands. “If I consider the trend, I think we will have much more natural, personalised, and effortless interactions than ever before because of this technology.”
Gen AI’s impact on Customer Data When discussing operational challenges, especially regarding customer data management, the guest speaker stressed quality over quantity. Gozzo explained that in most AI set-ups, “the real value lies not in the data you’ve collected, but in the understanding of how your business runs, operates, and the people doing the tasks you want to automate.”
Governance, Human Orchestration & the Future of AIBeyond personalisation, AI should be implemented responsibly and monitored closely. “The first thing with any AI deployment is to avoid thinking of it as software you buy, deploy, and forget. They need ongoing monitoring, engagement, and maintenance,” Gozzo tells Stathopoulos.
He suggested thorough testing processes and collaboration with specialised companies like AIUC, which verify AI systems against common risks. “These tests need to happen quarterly or yearly because the underlying models change so rapidly,” he added.
In addition to regularly conducting AI checks, the human element is also critical. AI might automate up to 80% of routine tasks, but humans will still play a vital role. Gozzo described the human role as that of an orchestrator, managing teams that include both humans and AI systems and effectively delegating tasks between them.
Finally, Gozzo talked about AI's immediate impact on customer experience. “Our leading customers’ AI agents are outperforming humans. They deliver higher-quality customer service experiences, and customers prefer interacting with their AI.” The key measure, he said, is the positive effect on business growth and customer lifetime value.
The chief technology officer’s parting advice to IT decision makers is: “The people on your team know how to make AI work. Capture their insights. Don’t treat this as a technology project. The technologist will not dominate the next decade. This is about business leaders and experts doing the heavy lifting.”
At the core of generative and agentic AI, Gozzo reminded listeners, are humans—the operational leaders and domain experts who embed knowledge into AI systems and drive real change.
Takeaways* AI can transform customer experience from reactive to proactive. * Quality data is more important than large data sets. * Human insight is crucial for effective AI implementation. * Governance and continuous monitoring are essential for AI systems. * Collaboration between humans and AI is the future of work. * The role of human agents will shift from execution to management and delegation. * The most mature companies are moving beyond metrics like CSAT to measure AI’s impact of outcomes like customer lifetime value and retention. * Testing and validation processes are key to successful AI deployment. * AI can and is delivering better-than-human customer service. * The success of AI initiatives relies on operational leaders' insights.
Chapters* 00:00 Transforming Customer Experience with AI * 02:51 The Role of Data in AI Solutions * 05:48 Governance and Security in AI Deployment * 09:03 Human-AI Collaboration in Customer Service * 12:01 The Future of AI in Customer Experience
About AdaAda is the trusted AI-native customer service company, built to transform how enterprises engage with customers. Powered by the Ada ACX operating model—which unifies technology, methodology, and expertise—Ada deploys high-performing AI agents that deliver personalized, efficient interactions across every channel and language.
Since 2016, Ada has powered over 5.5 billion interactions for leading brands like Square, Peloton, Canva, and monday.com, delivering extraordinary experiences at scale through higher-quality, more efficient customer service.
With enterprise-grade trust, security, and compliance (SOC 2, GDPR, HIPAA, AIUC-1), Ada enables organizations to reduce cost-to-serve, elevate CSAT, and confidently scale AI-powered customer experience. Learn more at ada.cx.
The era of 3G is ending. For many industrial businesses, smart infrastructure systems, remote device management, and IoT connectivity rely on networks that are now being phased out globally. The question isn’t if—but when your operations could be disrupted.
In this episode of Tech Transformed, Trisha Pillay speaks with Jana Vidis, Business Development Manager at IFB, about the worldwide 3G sunset, what it means for enterprises, and how proactive planning can prevent costly disruptions. They explore the reasons behind the transition to 4G and 5G, the impact on various industries, and the strategies organisations can implement to assess their reliance on legacy devices.
Why the 3G Sunset Matters3G networks have powered connectivity for decades, offering wide coverage and reliability. But as global operators move to 4G and 5G, maintaining 3G is no longer sustainable. Carriers are discontinuing services, and support is dwindling, leaving legacy devices vulnerable to:
- Operational downtime
- Inconsistent performance
- Increased security risks
Jana emphasises:
“Have a good understanding of what devices you have. Work with IT partners to prepare for future changes. Plan your transition and act before disruption hits.”
Jana also stressed the importance of understanding current technology deployments, planning for transitions, and future-proofing investments to avoid disruptions. The conversation highlights the need for proactive measures in adapting to technological advancements and ensuring operational continuity.
A Global TimelineThe transition is already well underway across multiple regions:
- North America: AT&T, Verizon, and T-Mobile 3G networks discontinued in February 2022; Canada’s shutdown begins in early 2025.
- Europe: Most countries, including the UK, Germany, Hungary, and Greece, will complete shutdowns by the end of 2025.
- Asia: Japan phased out 3G in 2022, Singapore in July 2024, and India plans completion by the end of 2025.
- Africa: South Africa started in July 2025; other countries are slowing the transition.
- South America: Providers like Telefonica, Entel, and Claro completed shutdowns in 2022–2023.
- Middle East: Oman started shutting down in July 2024; Zain Bahrain in Q4 2022; Kuwait, Iran, and Jordan are following.
Industrial devices still using 3G must transition now to avoid operational disruption. From smart infrastructure to remote IoT systems, legacy devices left unaddressed can cause downtime, inconsistent performance, and increased security risks.
Takeaways* 3G networks are being phased out to enable 4G and 5G development. * Businesses must assess their reliance on 3G devices before shutdowns. * Legacy devices can cause operational disruptions if not addressed. * Understanding current technology deployments is crucial for businesses. * Proactive planning can mitigate risks associated with network changes. * Investing in infrastructure now can save costs in the future. * Collaboration with IT partners is essential for smooth transitions. * Testing new devices before rollout is a best practice. * The demand for faster connectivity is driving technological advancements. * Future-proofing technology investments is key to long-term success.
Chapters00:00 The Global Shift from 3G Networks
02:48 Understanding the Impact on Businesses
05:44 Assessing Reliance on 3G Devices
08:57 Operational Changes and Disruptions
12:02 Strategies for Transitioning to New Technologies
14:55 Future-Proofing Connectivity Decisions
17:44 Key Takeaways and Final Thoughts
About Jana VidisJana Vidis is a cybersecurity and technology expert passionate about helping businesses protect their operations and make technology work smarter. At IFB, she delivers tailored solutions, supports clients, and drives growth through strategic business development.
A champion for women in tech, Jana leads Women in Tech Aberdeen, promoting diversity, inclusion, and empowerment in the North East of Scotland. Her expertise spans cybersecurity, disaster recovery, resilience planning, connectivity, hosted voice, and cloud solutions.
Tech leaders are often led to believe that they have “full-stack observability.” The MELT framework—metrics, events, logs, and traces—became the industry standard for visibility. However, Robert Cowart, CEO and Co-Founder of ElastiFlow, believes that this MELT framework leaves a critical gap.
In the latest episode of the Tech Transformed podcast, host Dana Gardner, President and Principal Analyst at Interabor Solutions, sits down with Cowart to discuss network observability and its vitality in achieving full-stack observability.
The speakers discuss the limitations of legacy observability tools that focus on MELT and how this leaves a significant and dangerous blind spot. Cowart emphasises the need for teams to integrate network data enriched with application context to enhance troubleshooting and security measures.
What’s Beyond MELT?Cowart explains that when it comes to the MELT framework, meaning “metrics, events, logs, and traces, think about the things that are being monitored or observed with that information. This is alluded to servers and applications.
“Organisations need to understand their compute infrastructure and the applications they are running on. All of those servers are connected to networks, and those applications communicate over the networks, and users consume those services again over the network,” he added.
“What we see among our growing customer base is that there's a real gap in the full-stack story that has been told in the market for the last 10 years, and that is the network.”
The lack of insights results in a constant blind spot that delays problem-solving, hides user-experience issues, and leaves organizations vulnerable to security threats. Cowart notes that while performance monitoring tools can identify when an application call to a database is slow, they often don’t explain why.
“Was the database slow, or was the network path between them rerouted and causing delays?” he questions. “If you don’t see the network, you can’t find the root cause.”
The outcome is longer troubleshooting cycles, isolated operations teams, and an expensive “blame game” among DevOps, NetOps, and SecOps.
Elastiflow’s approaches it differently. They focus on observability to network connectivity—understanding who is communicating with whom and how that communication behaves. This data not only speeds up performance insights but also acts as a “motion detector” within the organization.
Monitoring east-west, north-south, and cloud VPC flow logs helps organizations spot unusual patterns that indicate internal threats or compromised systems used for launching external attacks.
“Security teams are often good at defending the perimeter,” Cowart says. “But once something gets inside, visibility fades. Connectivity data fills that gap.”
Isolated Monitoring to Unified Experience Cowart believes that observability can’t just be about green lights and red lights, or whether a switch is on or off. It has to stress the experience, not only the user’s but also how one application interacts with another.
“The biggest shift organizations need to make,” the ElastiFlow CEO advises, “is to move from infrastructure health to usage experience. What really counts is whether the service being delivered is performing as it should.”
A unified experience can be achieved if leaders disband conventional barriers between teams. Imagine a Venn diagram where DevOps, NetOps, and SecOps overlap—each relying on network data as a common source of truth. The network becomes the central point that connects performance, reliability, and security around shared goals as per Cowart.
This philosophy supports ElastiFlow’s latest innovation – integrating network flow data directly into OpenTelemetry traces. Rather than treating network analytics as a separate console, ElastiFlow now includes connectivity information as part of the same trace that developers and SREs use to monitor applications.
“It’s the first time anyone has done this,” Cowart points out. “An engineer can now see within their observability platform not just an HTTP call but also the related network session, latency, and context—all in one view.”
By embedding the “fifth pillar” of observability—network flows— ElastiFlow aims to prepare organizations for future challenges. With Kubernetes, hybrid cloud, and microservices making the network more abstract yet increasingly essential, visibility at this level is no longer optional; it’s strategic.
“As infrastructure becomes self-healing and redundant,” Cowart concludes, “leaders need to concentrate less on isolated device health and more on the experience being delivered. That’s where the business value lies, and that’s where the network finally becomes clear.”
Takeaways* Legacy observability tools often overlook network connectivity. * The MELT framework leaves a critical gap – network flow data. * Network blind spots lead to extended troubleshooting cycles. * XOps (NetOps, DevOps, SecOps) data siloshinder effective problem resolution. * Security threats exploit the lack of network visibility, especially in east-west traffic. * Network flow data is essential for comprehensive observability. * Integrating application context enhances network data utility. * Collaboration between IT teams is necessary for effective observability.
Chapters* 00:00 Introduction to Network Observability * 06:04 The Blind Spot in Traditional Observability * 12:08 Security Implications of Network Observability * 18:03 Integrating Network Data with Application Context * 24:08 Future of Comprehensive Observability
Enterprises are discovering that the first wave of cloud adoption didn’t simplify operations. It created flexibility, but it also introduced fragmentation, rising costs, and skills gaps that now make AI adoption harder to manage.
In this episode of Tech Transformed, analyst and host Dana Gardner speaks with two leaders from across the IBM portfolio: Maria Bracho, CTO for the Americas at Red Hat, and Tyler Lynch, Field CTO for the HashiCorp product suite.
They discuss how organisations can move from scattered cloud operations to a unified, automated model that supports AI securely and at scale. The conversation covers the pressures leaders face today, the role of automation, and the skills and operating model changes required as AI becomes core to enterprise strategy.
What you’ll learn
- Why tool sprawl and shrinking teams are increasing operational risk
- How AI amplifies gaps in data, security, and processes
- What skills and operating model changes CIOs must prioritise
- Why hybrid cloud is essential for multi-model AI workloads
- The growing importance of automation in cloud and AI delivery
- How poor data hygiene can rapidly increase AI costs
- Practical steps for building secure, reliable AI operations
Key insights from the discussion
Cloud complexity is accelerating
Most organisations now run “a sprawl of tool sets and environments,” Bracho notes, often without the people or standardized processes to manage them. While cloud created opportunities, the operational overhead has increased.
AI raises the stakes
Training, tuning, and inference often run in different environments, each with separate performance and security requirements. Bracho describes AI as “the killer workload,” reinforcing the need for robust hybrid architectures.
Skills gaps slow progress
Lynch highlights the disconnect between AI teams and production engineering teams. Without alignment, model deployment becomes slow and risky — echoing findings from the HashiCorp 2025 Cloud Complexity Report, where most organizations say platform and security teams are not working in sync.
AI exposes underlying weaknesses
“AI is not going to solve complexity; it will amplify what you already have,” Bracho says. But with structured processes and automation, AI can reduce operator workload and help teams adopt best practices faster.
Automation is becoming essential
The Cloud Complexity Report shows that more than half of enterprises see automation as key to unlocking cloud innovation. With the foundations already laid, AI can accelerate progress by improving consistency and reducing manual effort.
Modernization is continuous
Both guests emphasise that AI success depends on long-term investment in people, operating rhythms, and security. Consulting can help organizations start strong, but lasting results come from internal alignment and disciplined execution.
Episode chapters
00:00 Navigating cloud complexity
08:11 Skills and operating model challenges
15:13 Automation for cloud and AI productivity
21:48 How consulting accelerates AI readiness
24:10 Final guidance for CIOs
About the guests
Maria Bracho
CTO, Americas at Red Hat. Maria advises enterprise customers on hybrid cloud architectures, platform strategy, and AI-enabled operations across large-scale environments.
Connect on LinkedIn
Tyler Lynch
Field CTO for the HashiCorp product suite within the IBM portfolio. Tyler works with organisations to modernise infrastructure, security, and automation practices that support cloud and AI workloads.
Connect on LinkedIn
About HashiCorp
HashiCorp is the Infrastructure Cloud company, helping organisations automate hybrid and multicloud environments with Infrastructure Lifecycle Management and Security Lifecycle Management. Offerings include managed services on the HashiCorp Cloud Platform (HCP), self-hosted enterprise products, and source-available tools.
Visit hashicorp.com
About Red Hat
Red Hat delivers enterprise open-source solutions, including Red Hat OpenShift and Red Hat Enterprise Linux, enabling organisations to build and manage hybrid cloud environments with speed, reliability, and consistency.
Visit redhat.com
About IBM
IBM provides hybrid cloud, AI, and consulting expertise that brings together Red Hat, HashiCorp, and other portfolio capabilities. IBM helps organisations modernise applications, streamline operations, strengthen security, and prepare for AI at scale.
Vist ibm.com
The semiconductor industry is at an inflection point. As systems become more intelligent, connected, and software-defined, chip design is growing too complex for humans alone. Advances in electronic design automation are reshaping how silicon is built and verified, enabling faster, smarter, and more reliable innovation from data centers to edge devices.
How AI Is Changing EDA and Chip DesignIn the latest episode of Tech Transformed, host John Santaferraro speaks with Dr. Thomas Andersen, Vice President of AI and Silicon Innovation at Synopsys, about the real-world impact of AI in chip design. Together, they explore how AI and automation are redefining EDA, how generative AI is accelerating design efficiency, and what the Synopsys acquisition of Ansys means for the future of simulation and system-level integration.
As Dr. Andersen explains, “AI is transforming EDA. Synopsys leads in silicon design, and the Ansys acquisition expands our capabilities across multiphysics simulation and system optimization.”
From Silicon to SystemsThe integration of complex hardware and software has become one of the greatest challenges in semiconductor and OEM innovation. Traditional sequential development, where software waits for hardware, often causes delays and missed targets. Advances in EDA tools and virtual prototyping now enable engineers to initiate software design months before silicon is finalised, thereby accelerating bring-up and enhancing collaboration across the supply chain.
“Generative AI enables more efficient design,” says Andersen. “AI reshapes engineering workflows, but human expertise remains essential.”
The result is faster time-to-market, enhanced design verification, and greater overall system reliability.
Listen to the full conversation on the Tech Transformed podcast to discover how Synopsys is advancing electronic design automation, improving engineering workflows and chip design from silicon to systems.
For more insights follow Synopsys:
- X: @Synopsys
- Instagram: @synopsyslife
- Facebook: https://www.facebook.com/Synopsys/
- LinkedIn: https://www.linkedin.com/company/synopsys/
Takeaways* AI is transforming EDA and chip design by automating complex processes. * Synopsys is a leader in silicon-to-systems design, providing critical software for chipmakers. * The acquisition of Ansys expands Synopsys' capabilities beyond EDA. * Generative AI is enabling more efficient and adaptable chip design. * AI-powered observability is reshaping engineering workflows. * The complexity of chip design has increased, requiring advanced tools and automation. * Human expertise remains essential in chip design, despite advances in automation. * EDA tools simulate chip designs, reducing the need for physical prototypes. * Agent engineers are the future, automating tasks traditionally done by humans. * The integration of AI in EDA is making the process faster, smarter, and more collaborative.
Chapters* 00:00:00 Introduction to EDA and AI * 00:03:00 Synopsys and Its Role in Chip Design * 00:09:00 The Impact of AI on EDA * 00:15:00 Generative AI and Automation * 00:21:00 Ansys Acquisition and Future Prospects
About SynopsysSynopsys, Inc. (Nasdaq: SNPS) is the leader in engineering solutions from silicon to systems, enabling customers to rapidly innovate AI-powered products. We deliver industry-leading silicon design, IP, simulation and analysis solutions, and design services. We partner closely with our customers across a wide range of industries to maximize their R&D capability and productivity, powering innovation today that ignites the ingenuity of tomorrow. Learn more at www.synopsys.com.
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Driving Enterprise Innovation with AI and Strong CI/CD FoundationsAs enterprises push to deliver software faster and more efficiently, continuous integration and continuous delivery (CI/CD) pipelines have become central to modern engineering. With increasing complexity in builds, tools, and environments, the challenge is no longer just speed, but it’s also about maintaining flow, consistency, and confidence in every release.
In this episode of Tech Transformed, host Dana Gardner joins Arpad Kun, VP of Engineering and Infrastructure at Bitrise, to explore how solid CI/CD foundations can drive innovation and enable enterprises to harness AI in more practical, impactful ways. Drawing on findings from the Bitrise Mobile DevOps Insights Report, Kuhn shares how teams are optimising mobile delivery pipelines to accelerate development and support intelligent automation at scale.
Complexity of Continuous Integration“Continuous integration pipelines are becoming more complex,” says Kuhn. “Build times are decreasing despite increasing complexity.” Faster compute and caching solutions are helping offset these pressures, but only when integrated into a cohesive CI/CD platform that can handle the rising demands of modern software delivery.
A mature CI/CD environment creates stability and predictability. When developers trust their pipelines, they iterate faster and with less friction. As Kuhn notes, “A robust CI/CD platform reduces anxiety around releases.” Frequent, smaller iterations deliver faster feedback, shorten release cycles, and often improve app ratings—especially in the fast-paced world of mobile and cross-platform development.
AI Ambitions with Engineering RealityIt’s easy to become swept up in the potential of AI without considering whether existing foundations can support it. Many development environments are not yet equipped to handle the iterative, data-intensive nature of AI-powered software engineering. Without scalable CI/CD pipelines, teams risk encountering bottlenecks that can cancel out the potential benefits of AI.
To truly drive innovation, enterprises must align their AI ambitions with robust automation, strong observability, and disciplined engineering practices. A well-designed CI/CD platform allows teams to integrate AI responsibly, accelerating testing, improving deployment accuracy, and maintaining agility even as complexity grows.
Takeaways* Continuous integration pipelines are becoming more complex. * Build times are decreasing despite increasing complexity. * Faster computing and caching are key to improving delivery speed. * Flaky tests have increased significantly, causing inefficiencies. * Monitoring and isolating flaky tests can improve build success rates. * Maintaining flow for engineers is crucial for productivity. * A robust CI/CD platform reduces anxiety around releases. * Frequent iterations lead to faster feedback and improved app ratings. * Cross-platform development is on the rise, especially with React Native. * The future of software development will be influenced by AI.
For more insights, follow Bitrise:
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Chapters00:00 Introduction to Tech Transformed Podcast
01:08 The Complexity of Continuous Integration
04:24 Challenges of Increased Speed in Development
08:09 The Importance of Continuous Integration and Deployment
10:32 Building a Robust CI/CD Platform
14:25 The Impact of Release Frequency on Business
16:52 Types of Applications and Development Trends
18:47 Aligning Development with Business Goals
24:15 Preparing for the Future of Software Development
About BitriseBitrise is a top mobile CI/CD platform, streamlining build, test, and deployment for mobile apps. It offers a user-friendly interface, robust integrations, and scalable infrastructure to simplify development and ensure efficient delivery of high-quality apps.
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For years, observability sat quietly in the background of enterprise technology, an operational tool for engineers, something to keep the lights on and costs down. As systems became more intelligent and automated, observability has stepped into a far more strategic role. It now acts as the connective tissue between business intent and technical execution, helping organizations understand not only what is happening inside their systems, but why it’s happening and what it means.
This shift forms the core of a recent Tech Transformed podcast episode between host Dana Gardner and Pejman Tabassomi, Field CTO for EMEA at Datadog. Together, they explore how observability has changed into what Tabassomi calls the “nervous system of AI”, a framework that allows enterprises to translate complexity into clarity and automation into measurable outcomes.
Building AI LiteracyAI models make decisions that can affect everything from customer experiences to financial forecasting. It's important to understand that without observability, those decisions remain obscure.
“Visibility into how models behave is crucial,” Tabassomi notes. True observability allows teams to see beyond outputs and into the reasoning of their systems, even if a model is drifting, automation is adapting effectively, and results align with strategic goals. This transparency builds trust. It also ensures accountability, giving organizations the confidence to scale AI responsibly without losing sight of the outcomes that matter most.
Observability Observability is not merely about monitoring; it is about decision-making. It provides the insight required to manage complex systems, optimize outcomes, and act with agility. For organizations relying on AI and automation, observability becomes the differentiator between being merely efficient and achieving a sustainable competitive edge. In short, observability is no longer optional; it is central to translating technology into strategy and strategy into advantage.
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Takeaways* Observability has evolved from cost efficiency to a strategic role in AI. * Integration with automation ensures explainable and predictable outcomes. * Standards like OpenTelemetry unify observability efforts. * Observability enhances security and governance in AI applications. * Real-world examples show observability's impact on business processes. * Strategic steps for leaders to leverage observability are provided. * Observability provides visibility and governance for AI-driven businesses. * Automation and observability integration are crucial for business success. * Observability aids in enhancing security across AI applications.
Chapters00:00:00 Introduction to Observability and AI
00:03:00 The Evolution of Observability
00:06:00 Observability as a Governance Tool
00:09:00 Automation and Observability
00:12:00 Standardization and Open Telemetry
00:15:00 Security and Observability
00:18:00 Practical Applications and Case Studies
00:21:00 Strategic Steps for Leaders
00:24:00 Conclusion and Future Outlook
About DatadogDatadog is a SaaS platform that integrates and automates infrastructure monitoring, application performance monitoring, log management, real-user monitoring, and more—delivering unified, real-time observability and security across the entire technology stack. Used by organizations of all sizes and industries, Datadog enables digital transformation and cloud migration, fosters collaboration among development, operations, security, and business teams, accelerates time to market, reduces problem resolution time, and provides insight into user behavior and business performance.
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““Without healthy employees, you don’t have healthy customers. And without healthy customers, you don’t have a healthy bottom line.” — Kate Visconti, Founder and CEO, Five to Flow.
While artificial intelligence (AI) has hastened development and made enterprises more efficient, it also comes with more deadlines. The deadlines often merge into after-hours messaging. Burnout has become a default result of productivity, especially in the tech industry.
In this episode of the Tech Transformed podcast, Shubhangi Dua, Podcast Host, Producer and B2B Tech Journalist, speaks with Kate Visconti, Founder and CEO of Five to Flow, about the critical issues of burnout and disengagement in the workplace. They discuss the five core elements of change management, the financial implications of employee wellness, and strategies for enhancing productivity through flow optimisation.
Also Watch: Fixing the Gender Gap in STEM
The Wellness Wave Diagnostic to Help Fix Profit LeaksVisconti stresses the importance of creating a supportive work environment and implementing effective change management practices to improve organisational performance. The conversation also highlights the role of technology in productivity and the need for leaders to prioritise employee well-being to drive business success.
With an ambition to change the way organisations define true performance, VIsconti developed a system – a data-driven framework called The Wellness Wave. As per the official Five to Flow website, The Wellness Wave is “a proprietary diagnostic that measures sentiment and business performance across five core elements.”
Visconti sheds light on the original framework of the company. She says, “The original was adopted when we first kicked off as part of our consulting, and it's called the Wellness Wave diagnostic. It’s literally looking across the five core elements — people, culture, process, technology, and analytics.”
This framework helps companies identify and fix their profit leaks, which are the hidden financial losses caused by employee burnout, disengagement, and distraction.
In her conversation with Dua, host of the Tech Transformed podcast episode, Visconti shares how understanding human behaviour can lead to significant improvements in business performance.
According to Five to Flow’s global diagnostics, only 13 per cent of flow triggers work at their best. For tech leaders, that means most teams are functioning well below their potential.
Kate’s top tip is to create flow blocks. “It’s about designing uninterrupted time for peak focus. This is when your brain isn’t in a stress state. For me, it’s mornings with my coffee. For others, it might be in the afternoon. Communicate those times to your team and protect them like meetings.”
These flow blocks aren’t just productivity tricks; they show that focus is more important than frantic multitasking. “Multitasking is a fallacy,” Kate says. “You’re just rapidly switching tasks and burning through mental energy.”
This episode of the Tech Transformed podcast is a must-listen for CEOs, CIOs, and IT decision-makers who want to regain performance from burnout.
Tune in for a discussion that redefines productivity, from managing time to mastering flow.
Listen at em360tech.com/podcasts
Explore more at fivetoflow.com
Follow the conversation on X and LinkedIn: @EM360Tech
Takeaways* Burnout and disengagement are significant profit leaks for organisations. * Understanding the five core elements of change management is crucial for success. * Employee wellness directly impacts productivity and organisational performance. * Distraction management is a key area needing improvement in workplaces. * Creating flow blocks can enhance focus and productivity. * Multitasking is ineffective; task switching reduces overall efficiency. * Technology should be leveraged to support, not hinder, productivity. * The financial cost of burnout is staggering, reaching $8.9 trillion globally. * Quality of work is more important than quantity; focus on meaningful productivity. * Leaders must prioritise their own well-being to effectively support their teams.
Chapters* 00:00 Introduction to Tech Transformed Podcast * 01:05 Understanding Burnout and Disengagement * 02:33 The Five Core Elements of Change Management * 04:52 The Business Value of Employee Wellness * 08:05 Assessing Financial Impact of Burnout * 10:55 Strategies for Enhancing Focus and Productivity * 14:56 Flow Optimisation vs. Time Management * 19:08 Creating Flow Blocks for Peak Performance * 22:58 The Role of Technology in Productivity * 26:58 Implementing Change for Organisational Success * 30:12 Case Studies and Real-World Applications * 35:49 Key Takeaways for Leaders
“Cyber resilience isn’t just about protection, it’s about preparation.”
Every business in this day and age lives in the cloud. Our operations, data, and collaboration tools are powered by servers located invisibly around the world. But here’s the question we often overlook: what happens when the cloud falters?
In this episode of Tech Transformed, Trisha Pillay sits down with Jan Ursi, Vice President of Global Channels at Keepit, to uncover the real meaning of cyber resilience in a cloud-first world. Are you putting all your trust in hyperscale cloud providers? Think again. Trisha and Jan explore why relying solely on giants like Microsoft or Amazon can put your data at risk and how independent infrastructure gives organisations control, faster recovery, and true digital sovereignty.
Takeaways:* The importance of cyber resilience in a cloud-first world * How independent cloud infrastructure protects your SaaS applications * Common shared responsibility misconceptions that can cost organisations data * Strategies for quick recovery from ransomware and cyberattacks * Why digital sovereignty ensures control and compliance
Chapters:00:00 – Introduction to Cyber Resilience and Cloud Strategy
05:00 – The Importance of Independent Infrastructure
10:00 – Shared Responsibility and Misconceptions
15:00 – Digital Sovereignty and Compliance
20:00 – Practical Tips for CISOs and CIOs
22:00 – Conclusion
About Jan Ursi:Jan Ursi leads Keepit’s global partnerships, helping organisations embrace the AI-powered cyber resilience era. Keepit is the world’s only independent cloud dedicated to SaaS data protection, security, and recovery. Jan has previously built and scaled businesses at Rubrik, UiPath, Nutanix, Infoblox, and Juniper, shaping the future of enterprise cloud, hyper-automation, and data protection.
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"5G is becoming a great enabler for industries, enterprises, in-building connectivity and a variety of use cases, because now we can provide both the lowest latency and the highest bandwidth possible,” states Ganesh Shenbagaraman, Radisys Head of Standards, Regulatory Affairs & Ecosystems.
In the recent episode of the Tech Transformed podcast, Shubhangi Dua, Podcast Host, Producer, and Tech Journalist at EM360Tech, speaks to Shenbagaraman about 5G and edge computing and how they power private networks for various industries, from manufacturing, national security to space.
The Radisys’ Head of Standards believes in the idea of combining 5G with edge computing for transformative enterprise connectivity. If you’re a CEO, CIO, CTO, or CISO facing challenges of keeping up the pace with capacity, security and quality, this episode is for you. The speakers provide a guide on how to achieve next-gen private networks and prepare for the 6G future.
Real-Time ControlThe growing need for real-time applications, such as high-quality live video streams and small industrial sensors with instant responses, demands data processing to occur closer to the source than ever before. Alluding to the technical solution that provides near-zero latency and ensures data security, Shenbagaraman says:
"By placing the 5G User Plane Function (UPF) next to local radios, we achieve near-zero latency between wireless and application processing. This keeps sensitive data secure within the enterprise network."
Such a strategy has now become imperative in handling both high-volume and mission-critical low-latency data all at the same time. Radisys addresses key compliance and confidentiality issues by storing the data within a private network. Essentially, they create a safe security framework that yields near-zero latency to guarantee utmost data security.
Powering Edge Computing ApplicationsThe real-world benefit of this zero-latency setup is the power it gives to edge computing applications. As the user plane function is the network's final data exit point, positioning the processing application near it assures prompt perspicuity and action.
"The devices could be sending very domain-specific data,” said Shenbagaraman. “The user plane function immediately transfers it to the application, the edge application, where it can be processed in real time."
It reduces errors and improves the efficiency of tasks through the Radisys platform, with the results meeting all essential requirements, including compliance needs.
One such successful use case spotlighted in the podcast is the Radisys work with Lockheed Martin’s defence applications. "We enabled sophisticated use cases for Lockheed Martin by leveraging the underlying flexibility of 5G,” the Radisys speaker exemplified.
Radisys team customised 5G connectivity for the US defence sector. It incorporated temporary, ad-hoc networks in challenging terrains using Internet Access Backhaul. It also covered isolated, permanent private networks for locations such as maintenance hangars.
Intelligence comes from the RAN Intelligent Controller (RIC), Shenbagaraman explained on the podcast. These small, AI and machine learning-enabled network applications run directly on the RIC. The smart applications allow functions like prioritising mission-critical traffic in real time.
Takeaways* 5G enables low latency and high bandwidth for various applications. * Edge computing co-located with 5G can achieve near-zero latency. * Private networks ensure data security and compliance for enterprises. * RADIS provides solutions compatible with multiple hardware platforms. * Lockheed Martin's 5G MIL stack showcases practical applications of edge computing. * 5G technology is evolving and will continue into 6G. * RADISYS is positioned to play a key role in future connectivity solutions. * 5G can address the needs of industries like manufacturing and national security. * The integration of satellite communication with 5G expands connectivity options. * Enterprises can leverage RADISYS for secure and differentiated connectivity solutions.
Chapters* 00:00 Introduction to 5G and Edge Computing * 01:20 The Role of 5G in Various Industries * 04:26 Understanding Edge Computing and Zero Latency * 08:16 Private Networks and Their Importance * 12:19 Making Software Compatible with Hardware * 15:53 Use Case: Lockheed Martin and 5G MIL Stack * 20:19 Future of 5G, Satellite Communication, and Edge Computing * 24:52 Looking Ahead: The Role of RADISYS in 6G
Now that companies have begun leaping into AI applications and adopting agentic automation, new architectural challenges are bound to emerge. With every new technology comes high responsibility, consequences and challenges.
To help face and overcome some of these challenges, Temporal introduced the concept of “durable execution.” This concept has quickly become an integral part of building AI systems that are not just scalable but also reliable, observable and manageable.
In this episode of the Tech Transformed podcast, host Kevin Petrie, VP of Research at BARC, sits down with Samar Abbas, Co-founder and CEO of Temporal Technologies. They talk about durable execution and its critical role in driving AI innovation within enterprises.
They discuss Abbas’s extensive background in software resilience, the development of application architectures, and the importance of managing state and reliability in AI workflows. The conversation also touches on the collaboration between developers, data teams, and data scientists, emphasising how durable execution can enhance productivity and governance in AI initiatives.
Also Watch: Developer Productivity 5X to 10X: Is Durable Execution the Answer to AI Orchestration Challenges?
Chatbots to Autonomous Agents“AI agents are going to get more and more mission critical, more and more longer lived, and more asynchronous," Abbas tells Petrie. “They’ll require more human interaction, and you need a very stable foundation to build these kinds of application architectures.”
AI not just fuels chatbots today. Enterprises are increasingly experimenting with agentic workflows—autonomous AI agents that carry out complex background tasks independently. For example, agents can assign, solve, and submit software issues using GitHub pull requests.
Such a setup isn’t just a distant vision; the Temporal co-founder pointed to OpenAI’s Codex as a real-world case. With this approach, AI becomes a system that can handle hundreds of tasks at once, potentially achieving "100x orders of magnitude velocity," as Abbas described.
However, there are some architectural difficulties to stay mindful of. The AI agents are non-deterministic by nature and often depend on large language models (LLMs) like OpenAI’s GPT, Anthropic’s Claude, or Google’s Gemini. They reason based on probabilities, and they improvise. They often make decisions that are hard to trace or manage.
AI workflows as simple codeThis is where Temporal comes in. It becomes the executioner that keeps the system cohesive and in alignment. “What we are trying to solve with Temporal and durable execution more generally is that we tackle challenging distributed systems problems," said Abbas.
Rather than developers stressing over queues, retries, or building their own reliability layers, Temporal allows them to write their AI workflows as simple code. Temporal takes care of everything else—reliable state management, retrying failed tasks, orchestrating asynchronous services, and ensuring uptime regardless of what fails below the surface.
As agent-based architectures become more common, the demand for this kind of system-level orchestration will only increase.
Listen to the full conversation on the Tech Transformed podcast, and discover how Temporal is shaping the next era of durable, autonomous, AI-powered applications.
Learn More at Temporal.io
Takeaways* Durable execution is essential for maintaining software uptime. * Samar Abbas has over 25 years of experience in software development. * AI agents are becoming increasingly mission-critical in applications. * Organisations need a stable foundation for AI architectures. * Durable execution provides full visibility into AI decision-making. * The future of AI involves more autonomous agents performing tasks. * Context is crucial for maximising the value of AI models. * Durable execution helps manage scalability and reliability in AI workflows. * Cross-functional collaboration is key to successful AI initiatives. * Investing in durable execution can unlock higher productivity and quality.
Chapters* 00:00 Introduction to Durable Execution and AI Innovation * 07:06 Samar Abbas's Journey and Insights on Software Resilience * 12:54 The Role of Durable Execution in AI Workflows * 18:52 Cross-Functional Collaboration in AI Initiatives * 24:38 The Importance of Durable Execution for Business Leaders
For CISOs and technology leaders, AI is reshaping business process management and daily operations. It can automate routine tasks and analyse data, but the human element remains critical for workforce oversight, customer interactions, and strategic decision-making.
In this episode of Tech Transformed, Trisha Pillay talks with Anshuman Singh, CEO of HGS UK, about AI in the workplace. They discuss how AI can support employees, improve customer service, and require careful oversight. Singh also shares insights on preparing organisations for AI integration and trends leaders should watch in the coming years.
Questions or comments? Email info@em360tech.com or follow us on YouTube, Instagram, and Twitter @EM360Tech.
Takeaways* AI is reshaping workforce needs, not just replacing jobs. * Routine tasks are increasingly being automated by AI. * AI can free up capacity for more meaningful work. * The narrative around productivity is changing with AI. * AI will create new job opportunities, often better-paying. * Human oversight is crucial in AI decision-making. * AI can assist in customer service, enhancing empathy. * Organisations should not wait for perfect AI solutions. * Training and hands-on experience with AI are essential. * A psychological safety net is necessary for AI experimentation.
Chapters00:00 Introduction to AI and Human Element
03:03 AI's Impact on Workforce Dynamics
08:29 The Role of Human Oversight in AI
10:46 AI Innovations in Customer Service
16:34 Positioning for Growth in Business Process Management
20:01 Preparing the Workforce for AI Integration
25:35 Emerging Trends in AI and Workforce
29:19 Final Thoughts on AI and Ethics
AI-Powered Canvases: The Future of Visual Collaboration and InnovationAs hybrid and remote work become the standard, organizations are rethinking how teams brainstorm, align, and innovate. Traditional whiteboards and digital tools often fall short in keeping pace with today’s complex business challenges. This is where AI-powered canvases are transforming visual collaboration.
In this episode of Tech Transformed, Kevin Petrie, VP of Research at BARC, joins Elaina O’Mahoney, Chief Product Officer at Mural, to explore how AI collaboration tools are reshaping teamwork in off-site locations. From customer journey mapping to process design, AI-powered canvases give teams the ability to visualize ideas, surface insights faster, and make better decisions—while keeping human creativity at the centre.
AI-Powered Canvases, Visuals, and CollaborationA central theme in the conversation is the distinction between automation and augmentation. While AI can recommend activities, map processes, and identify participation patterns, decision-making remains a human responsibility.
As O’Mahoney explains:
“In the Mural canvas experience, we’re looking to draw out the ability of a skilled facilitator and give it to participants without them having to learn that skill over the years.”
This balance ensures that while AI-powered canvases streamline collaboration, teams still rely on human judgment, creativity, and contextual knowledge. One of the most powerful contributions is in AI-driven visuals, which can translate raw data or unstructured input into clear diagrams, journey maps, or process flows. These visuals not only accelerate understanding but also help teams spot gaps and opportunities more effectively.
For example:
- In customer journey mapping, AI can quickly generate visual flows that highlight pain points and opportunities that would take much longer to uncover manually.
- In manufacturing, AI-powered canvases can create dynamic visuals of workflows, showing how new technologies might disrupt established processes.
The Role of Visual Tools in Hybrid WorkIn blended work environments, teams often lack the in-person cues that guide effective collaboration. Visual canvases bring those cues into the digital workspace, showing where ideas are concentrated, highlighting gaps in participation, and enabling alignment across dispersed teams. By combining intuitive design with AI-driven support, platforms like Mural help organisations adapt to the demands of hybrid work while keeping human creativity at the centre.
Takeaways* AI is reshaping visual collaboration in distributed teams. * Visual elements enhance understanding and decision-making. * AI can augment workflows but requires human oversight. * There is no universal playbook for AI integration in businesses. * Hybrid work necessitates effective digital collaboration tools. * AI can help visualize complex customer experiences. * Human intuition and creativity remain essential in AI applications. * Training and guidance are crucial for effective AI use. * Collaboration tools must adapt to diverse work environments. * AI should be seen as a partner in the creative process.
Chapters00:00 The Evolution of Visual Collaboration
05:15 Augmenting vs Automating: The Role of AI
10:36 Navigating AI Integration in Business
12:44 Hybrid Work and Team Collaboration
16:08 AI's Role in Visualizing Customer Experiences
17:30 Emphasizing Human-AI Collaboration
About MuralMural is a visual collaboration platform that enhances teamwork and productivity. It provides an interactive space for teams to ideate, align, and execute strategies. The platform combines intuitive visual tools with strong security measures to help companies increase efficiency and tackle challenges effectively. Mural offers a variety of features, including a visual work platform with tools like tables, mind maps, and diagrams. Its AI tools assist in structuring working sessions, generating ideas, and automating tasks such as clustering sticky notes.
The issue is data fragmentation, where untrustworthy data is siloed across different databases, SaaS applications, warehouses, and on-premise systems,” Vladimir Jandreski, Chief Product Officer at Ververica, tells Christina Stathopoulos, the Founder of Dare to Data.
“Simply, there is no single view of the truth that exists. With governance and data quality checks, these are often inconsistent, AI systems end up consuming incomplete or conflicting signals,” he added, setting the stage for the podcast.
In this episode of the Don't Panic, It's Just Data podcast, Stathopoulos speaks with Jandreski about the vital role of unified streaming data platforms in facilitating real-time AI.
They discuss the difficulties businesses encounter when implementing AI, the significance of going beyond batch processing, and the skills necessary for a successful streaming data platform. Applications in the real world, especially in e-commerce and fraud detection, show how real-time data can revolutionise AI strategies.
Your AI Could Be a Step Behind Jandreski says that most organisations continue to be engineered on batch-first data systems. That means, they still process information in chunks—often hours or even days later. “It's fine for reporting, but it means your AI is always going to be one step behind.”
However, “the unified streaming platform flips that model from data at rest to data in motion.” A unified platform will “continuously capture the pulse” of the business and feed it directly to AI for automated real-time decision making.
Challenges of Agentic AI Considering that the world is moving toward the era of agentic AI, there are some key challenges that still need to be addressed. Agentic AI means autonomous agents make real-time decisions, maintain memory, use tools and collaborate among themselves. Because they act on their own decisions, regulating them is necessary.
Building agents is not the main challenge, but the real challenge is “actually giving them the right infrastructure.” Jandreski highlights. Alluding to an example of AI prototyping frameworks such as Longchain or Lama Index, he further explained that those frameworks work for demos.
In reality, however, they can’t support a long-running system trigger workflows that demand high availability, fault tolerance, and deep integration with the enterprise data. This is because enterprises have multiple systems, and many of them are not connected. This way, the data forms into silos.
When data is in silos, a unified streaming data platform becomes the key solution. “It provides a real-time event-driven contextual runtime where AI agents need to move from the lab experiments to production reality.”
Takeaways* Unified streaming data platforms are essential for real-time AI. * Batch processing creates lag, hindering AI effectiveness. * Data fragmentation leads to unreliable AI decisions. * A unified platform ensures data is fresh and trustworthy. * Real-time AI requires a robust data infrastructure. * Organisations must move beyond legacy batch systems. * Governance and data quality are critical for AI success. * Real-world applications demonstrate the value of streaming data. * E-commerce and finance are key industries for real-time AI. * AI strategies need a solid foundation to scale.
Chapters* 00:00 Introduction to Unified Streaming Data Platforms * 03:10 Key Blockers in AI Implementation * 06:13 The Importance of Unified Streaming Data Platforms * 08:48 Capabilities of a Unified Streaming Data Platform * 11:54 Real-World Applications of Real-Time AI * 15:04 Final Takeaways for IT Decision Makers
About VervericaVerverica, the original creators of Apache Flink®, empowers businesses with high-performance data streaming and processing solutions. Streamlining operations, developer efficiency, and enabling customers to solve real-time use cases reliably and securely. Ververica’s advanced Streaming Data Platform, powered by its cloud native VERA engine, revolutionises Apache Flink®, making it easy for organisations to harness data insights at scale. With Ververica, customers can meet any business SLA, leveraging advanced data streaming and processing capabilities in real-time or on the lakehouse. Ververica enables businesses to connect, process, govern, and analyse data across infinite use cases, with flexible deployment options, including public cloud, private cloud, or on-premise environments. Discover more at ververica.com.
"The tools we make are observability tools today. But it can never be the goal of our business to provide observability. The goal of our business as a vendor and as a partner with our customers is to give them understandability,” stated Nic Benders, the Chief Technical Strategist at New Relic.
In this episode of the Don't Panic It's Just Data podcast, host Christina Stathopoulos, the Founder of Dare to Data, speaks with Benders about where observability is headed in IT systems. They discuss how AI is transforming observability into a more comprehensive understanding of complex systems, moving beyond traditional monitoring to achieve true understandability.
Benders explained the importance of merging various data types to provide a complete picture of system performance and user experience. He believes AI can bridge the gap between mere observation of systems and a deeper understanding of their functionality. This could ultimately lead to enhanced incident response and operational efficiency.
With maturing technology, complexity is expected to grow, too. The straightforward act of “observing” those complexities is like watching a green light on a machine. This is not enough. The major challenge is to “understand” the inside operations of the machine. This is the difference between simply seeing the data and knowing the "why."
Observability to UnderstandabilityAs per Benders, the term observability "leaves a lot to be desired." While it’s the industry’s common label, it only describes seeing a system. The real goal, he argues, is to understand it.
Alluding to an analogy, the technical strategist asks Stathopoulos to imagine a nuclear power plant full of a million blinking lights and screens. “You can have all the observability available, but if you're not an expert, you won't grasp what’s actually happening,” says Benders.
Typically, software has been developed by a single person who knows every inch of it. However, today, technology has become more perplexing. AI, alongside teamwork and collaboration, provides the tools to solve this problem. An engineer might manage code they didn’t write, making a dashboard full of charts unhelpful. Understandability means moving beyond raw data to give context and meaning.
Ultimately, Benders advises IT leaders to embrace change. The tech industry is constantly changing and advancing. Instead of fearing new tools, organizations should focus on what they need to grasp the unknown. As he puts it, "a lot of unknown is coming over the next few decades."
Takeaways* Observability is not enough; understanding is crucial. * AI can enhance the understanding of complex systems. * The shift from observing to understanding is essential for modern IT. * AI presents both challenges and opportunities in software development. * New interfaces powered by AI can improve user interaction with data. * AI can help reduce incident response times significantly. * Collaboration with AI is becoming the norm in software development. * Real-world applications show measurable benefits of AI in observability. * IT decision-makers must prepare for ongoing changes in technology. * Understanding the unknown is key to navigating future challenges.
Chapters* 00:00 Introduction to Observability and Understandability * 05:00 The Role of AI in Modern IT * 10:02 AI's Impact on Observability Solutions * 14:58 Real-World Applications of AI in Observability * 19:52 Key Takeaways for IT Decision Makers
About New Relic The New Relic Intelligent Observability Platform helps businesses eliminate interruptions in digital experiences. New Relic is the only AI-strengthened platform to unify and pair telemetry data to provide clarity over your entire digital estate. We move your problem-solving past proactive to predictive by processing the right data at the right time to maximize value and control costs.
That’s why businesses around the world—including Adidas Runtastic, American Red Cross, Domino’s, GoTo Group, Ryanair, Topgolf, and William Hill—run on New Relic to drive innovation, improve reliability, and deliver exceptional customer experiences to fuel growth. Visit: www.newrelic.com.
The phrase “AI agent” still brings to mind chatbots handling customer queries. Fast forward to today - AI agents are far more versatile, representing a new generation of systems capable of perceiving, reasoning, and acting autonomously. These bots are beginning to reshape how enterprises operate, not just in customer service but across software development, data analytics, and operational workflows.
In this episode of Tech Transformed, Dare To Data Founder Christina Stathopoulos explores the rapid rise of AI agents with Ben Gilman, CEO of Dualboot Partners. Together, they unpack how AI agents differ from traditional automation and what this shift means for software development, enterprise operations, and the future of productivity.
AI Agents vs. Traditional AutomationUnlike traditional automation, which follows strict, deterministic rules, AI agents can adapt to changing inputs, analyze complex data sets, and make autonomous decisions within defined parameters. This allows them to tackle tasks that were previously too intricate or time-consuming for automated systems. Dualboot Partners helps organizations harness these AI agents, integrating them into workflows to deliver real business value through a combination of product, design, and engineering expertise.
“The biggest difference with an AI agent, between a standard tool, is that the agent can perceive information and reason about it, providing context and insights you don’t normally get in an algorithm.” — Ben Gilman, CEO, Dual Boot Partners.
The Future of AI in EnterpriseOrganisations face several hurdles when integrating AI agents, including defining clear use cases, understanding the probabilistic nature of AI reasoning, and incorporating agents into existing processes and workflows. Despite the challenges, the potential payoff is substantial. AI agents can boost productivity, improve decision-making, and make enterprises more agile. As these systems mature, humans and AI are increasingly collaborating as true partners, reshaping what the workplace and work itself look like.
Takeaways:* AI Agents vs. Traditional Automation: AI agents can perceive and reason, offering more context and adaptability compared to deterministic systems. * Real-World Applications: Examples include virtual vet agents and data analytics tools that enhance productivity and decision-making. * Challenges in Adoption: Organizations face hurdles in defining specific use cases and integrating AI agents effectively. * Future of AI in Tech: AI agents are expected to significantly boost productivity and innovation in software development and enterprise operations, with AI-first approaches like Dualboot's "DB90" driving structured adoption and accelerating modernization.
Chapters0:00 - 3:00: Introduction to AI Agents
3:01 - 6:00: Differences from Traditional Automation
6:01 - 12:00: Real-World Applications and Examples
12:01 - 18:00: Challenges in Adoption
18:01 - 22:00: Future Impact on Tech and Operations
22:01 - 24:00: Conclusion and Final Thoughts
About Dualboot PartnersDualboot Partners is a product-led digital transformation company that builds powerful software designed to drive business results. With a proven AI-driven process, Dualboot combines product strategy, design, and engineering to help organizations modernize systems, accelerate delivery, and create scalable solutions. The company’s diverse team partners with clients across healthcare, financial services, technology, manufacturing, consumer markets, and more. Dualboot is recognized for technical excellence, clear communication, and a focus on outcomes that strengthen the bottom line.
In a time when the world is run by data and real-time actions, edge computing is quickly becoming a must-have in enterprise technology. In the recent episode of the Tech Transformed podcast, hosted by Shubhangi Dua, a Podcast Producer and B2B Tech Journalist, discusses the complexities of this distributed future with guest Dmitry Panenkov, Founder and CEO of emma.
The conversation dives into how latency is the driving force behind edge adoption. Applications like autonomous vehicles and real-time analytics cannot afford to wait on a round trip to a centralised data centre. They need to compute where the data is generated.
Rather than viewing edge as a rival to the cloud, the discussion highlights it as a natural extension. Edge environments bring speed, resilience and data control, all necessary capabilities for modern applications.
Adopting Edge ComputingFor organisations looking to adopt edge computing, this episode lays out a practical step-by-step approach. The skills necessary in multi-cloud environments – automation, infrastructure as code, and observability – translate well to edge deployments. These capabilities are essential for managing the unique challenges of edge devices, which may be disconnected, have lower power, or be located in hard-to-reach areas. Without this level of operational maturity, Panenkov warns of a "zombie apocalypse" of unmanaged devices.
Simplifying ComplexityManaging different APIs, SDKs, and vendor lock-ins across a distributed network can be a challenging task, and this is where platforms like emma become crucial.
Alluding to emma’s mission, Panenkov explains, "We're building a unified platform that simplifies the way people interact with different cloud and computer environments, whether these are in a public setting or private data centres or even at the edge."
Overall, emma creates a unified API layer and user interface, which simplifies the complexity. It helps businesses manage, automate, and scale their workloads from a singular perspective and reduces the burden on IT teams. They also reduce the need for a large team of highly skilled professionals leads to substantial cost savings.
emma’s customers have experienced that their cloud bills went down significantly and updates could be rolled out much faster using the platform.
Takeaways* Edge computing is becoming a reality for more organisations. * Latency-sensitive applications drive the need for edge computing. * Real-time analytics and industry automation benefit from edge computing. * Edge computing enhances resilience, cost efficiency, and data sovereignty. * Integrating edge into cloud strategies requires automation and observability. * Maturity in operational practices, like automation and observability, is essential for edge readiness. * Standardisation of APIs and devices is crucial for future edge solutions. * The market demand will drive the evolution of edge computing platforms.
Chapters* 00:00 Introduction to Edge Computing * 02:28 Driving Forces Behind Edge Computing * 04:30 Integrating Edge into Cloud Strategies * 06:41 The Role of Android in Edge Computing * 08:38 Preparing for Edge Computing Challenges * 11:30 Elevator Pitch for Emma * 13:09 Managing Complexities in Edge Computing * 15:30 Building Operational Maturity for Edge * 17:54 Use Case: Autonomous Vehicles * 21:07 Future of Platforms in Edge Computing * 23:44 Edge Computing in Different Scenarios
"The real challenge that many manufacturers have dealt with for a long time and will keep facing is the shift from mass manufacturing to mass customisation," stated Daniel Joseph Barry, VP of Product Marketing at Configit.
In a world that has moved from mass manufacturing to mass customisation, makers of complex products like cars and medical devices face a hidden problem. For more than a century, since the time of Henry Ford, manufacturers have worked in a separate, mass-production mindset. This method in the recent industrial scenario has caused a lot of friction and frustration.
In this episode of the Tech Transformed podcast, Christina Stathopoulos, Dare To Data Founder, talks with Daniel Joseph Barry, VP of Product Marketing at Configit. They talk about Configuration Lifecycle Management (CLM) and its importance in tackling the challenges that manufacturers of complex products face recurrently.
The speakers discuss the move from mass manufacturing to mass customisation, the various choices available to consumers, and the need to connect sales and engineering teams. Barry emphasises the value of working together to tackle these challenges. He points out that using CLM can make processes easier and enhance customer experiences (CX).
What is Configuration Lifecycle Management (CLM)According to Barry, Configuration Lifecycle Management (CLM) is an approach that involves managing product configurations throughout their lifecycle. He describes it as an extension of Product Lifecycle Management (PLM) that focuses specifically on configurations.
In today's highly bespoke world, customers are buying configurations of products instead of just the products themselves. The answer isn't to work harder within existing teams but to adopt a new, collaborative approach. This is where Configuration Lifecycle Management (CLM) comes in.
CLM creates a single, shared source of truth for all product configuration information. It combines data from engineering, sales, and manufacturing. Configit’s patented Virtual Tabulation® (VT™) technology pre-computes all the different options, so there’s no longer a need for slow, real-time calculations.
Barry says, "It's just a lookup, so it's lightning fast.” This represents a prominent shift that removes the delays and dead ends, frustrating customers and sales staff. Such a centralised system makes sure that every department uses the same, verified information, stopping errors from happening later on.
One such company, and Configit’s customer, Vestas, a wind power company, automated its configuration process for complex wind turbines that have 160,000 options. By adopting a CLM approach, they cut the time to configure a solution from 60 minutes to just five.
Tune into the podcast for more information on the transformational impact of Configuration Lifecycle Management (CLM).
Takeaways* Manufacturers are transitioning from mass manufacturing to mass customisation. * Customisation leads to complexity and challenges in manufacturing. * Siloed systems create inefficiencies and reliance on experienced employees. * Configuration Lifecycle Management (CLM) can automate and streamline processes. * Aligning sales and engineering is crucial for successful product delivery. * Digital threads and AI are becoming essential in manufacturing. * A cross-functional approach is necessary to tackle modern manufacturing challenges. * Understanding product configurations is key to meeting customer demands. * Companies must adapt to avoid being left behind in the industry. * The future of manufacturing relies on integrated solutions and data management.
Chapters* 00:00 Introduction to Configuration Lifecycle Management * 02:47 Challenges in Manufacturing Complex Products * 07:55 The Impact of Customisation on Manufacturing * 14:33 The Role of Heroes in Manufacturing * 18:05 Aligning Sales and Engineering * 26:11 The Benefits of Configuration Lifecycle Management * 35:49 Conclusion and Key Takeaways
About ConfigitConfigit builds configuration solutions for manufacturing companies to master the challenges of getting configurable products to market faster, and to sell, manufacture, and service them more effectively.
Trusted by the world’s largest manufacturing companies for their mission-critical functions, Configit’s advanced configuration platform, built on Virtual Tabulation® technology, handles the most complex products in the world.
As global industries face mounting pressure to operate more efficiently and sustainably, many are turning to the combined power of artificial intelligence (AI) and the Internet of Things (IoT). From optimising energy usage to enabling real-time decision-making, these technologies are reshaping how businesses think about infrastructure, impact, and innovation. But the road to adoption isn’t without its challenges, from data literacy to greenwashing.
In this episode of Tech Transformed, Em360Tech host Trisha Pillay talks with Akanksha Sharma, Senior Director at the GSMA Foundation, about how these emerging technologies are creating tangible value, especially for small and medium-sized enterprises (SMEs) and industries with legacy systems like utilities.
IOT and AISharma highlights that the 2020s will be remembered as the decade when IoT experiences exponential growth, supported by data from GSMA Intelligence projecting over 37 billion IoT connections worldwide by 2030, more than doubling the number recorded in 2021. She notes that, unlike previous technological waves, AI adoption is accelerating rapidly, moving from niche awareness to mainstream use within just a few years.
When discussing climate action and carbon markets, Sharma stresses the need for transparent, data-backed verification mechanisms. She warns against superficial greenwashing practices and advocates for AI systems that prioritise accuracy and ethical standards to ensure genuine environmental benefits.
Takeaways* Data-driven infrastructure can turn sustainability into reality. * AI and IoT are set to scale in the 2020s. * Small and medium enterprises face unique operational challenges. * Digital solutions can enhance the accuracy of carbon credits. * Greenwashing misleads consumers about environmental benefits. * Digital literacy is a major barrier to technology adoption. * Start with the 'why' when adopting new technologies. * Ethics in AI must be prioritised to avoid negative consequences. * The world is changing due to climate change and technology. * Collaboration is key to effective climate action.
Chapters:00:00 – Transforming Sustainability with Data-Driven Infrastructure
03:05 – The Role of AI and IoT in Enterprises
09:10 – Challenges in Operational Efficiency and Sustainability
13:42 – Real-World Impact of AI and IoT
16:57 – Carbon Markets and Digital Solutions
21:08 – Understanding Greenwashing
23:30 – Barriers to Technology Adoption
26:17 – Key Takeaways and Predictions
About Akanksha SharmaAkanksha Sharma leads the ClimateTech and Digital Utilities programmes at GSMA, where she drives innovation at the intersection of mobile technology and sustainability. Since joining GSMA in 2012, she has specialised in leveraging mobile and digital solutions for social impact, with extensive experience in research and data-driven insights through her roles at GSMA Intelligence and Mobile for Development’s Central Insights Unit.
Before GSMA, Akanksha worked as a Power and Utilities Analyst at GlobalData in India, bringing deep sector knowledge to her current focus on transforming utility services through digital technologies. She holds an MBA from IBS Hyderabad and a Bachelor of Science degree in Psychology from Rajasthan University, India.
Many companies spend a lot on data technology, but often forget about the importance of data and AI literacy. Without the right skills, even the best platforms can fail to deliver results. Teams need to understand how to work with data and AI to make any strategy successful.
In this episode of Tech Transformed, EM360Tech’s Trisha Pillay chats with Greg Freeman, the founder of Data Literacy Academy about why knowing data and AI matters for anyone building a digital strategy.
Data and AI LiteracyFreeman points out that many data strategies end up as technical documents rather than actionable roadmaps. He explains that organisations often spend heavily on infrastructure, expecting better tools to solve their problems but without employees who understand how to work with data and why it matters, these investments rarely deliver results.
Freeman explains that data strategies often fail because only a small portion of employees less than 20 per cent are truly enthusiastic about data. Most strategies are designed with this minority in mind, creating an echo chamber that leaves the majority behind. As a result, data stays siloed, and business decisions don’t improve.
The Data Literacy Academy founder stresses that unless organisations engage the 80 per cent of employees who aren’t already invested, their strategies are unlikely to succeed. When the focus is on tools rather than people, adoption falls behind.
Takeaways* Data and AI literacy are key to turning strategy into value. * Tools alone don’t work; people need confidence and context. * Focus on engaging the data-hesitant majority, not just the enthusiasts. * Cultural change, not just technical change, is what drives ROI
Chapters* 00:00 – Introduction * 02:07 – Beyond the Tech Stack * 04:41 – Why Strategies Fail * 08:41 – Literacy Barriers * 12:08 – Success in the Real World * 17:17 – Building Lasting Literacy * 22:20 – AI Needs Literacy Too * 26:33 – Final Takeaways
About Greg FreemanGreg Freeman is the founder and CEO of Data Literacy Academy, where he works with CDOs, CIOs, and business leaders to drive real cultural change around data. His mission is to help organisations tackle data illiteracy by building confidence and capability from the ground up, especially for employees who feel disengaged or anxious about data.
With a background in sales leadership and tech startups, Greg brings both strategic insight and real-world experience.
"As agentic AI spreads across industries,” states Rishi Rana, the Chief Executive Officer at Cyara. “Everybody is curious to understand how that is going to transform customer experience across all the channels?"
In this episode of the Tech Transformed podcast, Shubhangi Dua, the Host and Podcast Producer at EM360Tech, talks with Rishi Rana, the CEO of Cyara, about how agentic AI is changing customer experience (CX).
They look at how AI has developed from simple chatbots to advanced systems that can understand and predict customer needs. Rana spotlights the need for ongoing testing and monitoring to make sure AI solutions work well and follow the regulations.
They also discuss the obstacles businesses encounter when implementing AI, the importance of good data, and the future of AI agents in improving customer interactions.
Agentic AI Transforming Customer Experience (CX)Customer experience (CX) is changing quickly and significantly, thanks to the rise of agentic AI. These advanced systems go beyond the basic chatbots of the past.
While such a change may offer a future equipped with a smart, proactive customer journey, it doesn't come without its challenges. These obstacles require organisations to thoughtfully plan and carefully execute strategies.
For years, chatbots provided a basic type of automated customer support. However, Rana explains that the evolution of AI is pushing boundaries. "AI in customer experience (CX) is changing from a basic level of chatbots that have been present for the last five or 10 years. Now they are turning into fully agentic systems that operate across voice, digital and human-assisted channels," said Rana.
Moving Beyond Basic ChatbotsChatbots’ lucrative development lies in the strengths of Large Language Models (LLMs) like Google's Gemini, Meta's Llama, and OpenAI's ChatGPT. This is because the AI-backing models are facilitating "voice bots" and other AI agents to move beyond simple response automation to intelligent orchestration.
Intelligent orchestration results in anticipating user needs, adjusting in real-time, and guiding customers to hybrid solutions where AI and human agents work together. Ultimately, the goal is to greatly improve the customer experience (CX). Studies suggest that 86 per cent of people are willing to pay more for the same service, no matter what it is, when the customer experience is better.
Advancements don’t come without a price. Rana believes the lack of proper guardrails is a cause for concern. "AI is great, but you need to have guardrails and ensure the intent behind the questions and the objective behind the customer interaction is getting answered."
This requires ongoing testing and monitoring across all channels to ensure consistency and avoid problems like hallucinations, misuse, or bias. These issues can result in major financial losses and damage to reputation. For instance, Rishi Rana mentioned that over "$10 billion in violations and liabilities due to incorrect information given to customers" occurred in 2024 alone.
To successfully execute agentic AI, enterprises must shift left with AI by starting testing of AI agents early. This means focusing on continuous testing and observability instead of relying on one-time quality checks. This proactive approach is key to identifying AI misbehaviour quickly, before customers notice it.
Cyara, with its AI trust suite, leads this effort by validating LLM-based bots and spotting issues like hallucinations and misuse. Their Pulse 360 provides real-time customer experience visibility across 120+ countries and over 360+ carriers, showcasing a wide reach.
Takeaways* Agentic AI is revolutionising customer interactions across various channels. * The evolution from basic chatbots to intelligent systems is crucial for better CX. * Continuous testing and monitoring are essential for AI success. * Enterprises must ensure compliance with regulations while implementing AI. * Understanding customer intent is key to effective AI solutions. * Friction points in customer interactions can lead to dissatisfaction. * AI must provide a seamless experience across all channels. * Data quality is critical in the customer experience lifecycle. * Companies need to proactively address AI misbehaviour to prevent issues. * The future of AI in CX involves integrating with existing workflows and systems.
Chapters* 00:00 Transforming Customer Experience with Agentic AI * 01:43 Evolving Beyond Basic Chatbots * 05:04 Key Elements of a Great CX Platform * 06:41 Understanding Customer and Enterprise Perspectives * 08:25 Identifying Friction Points in Customer Interactions * 10:14 Implementing Guardrails for AI in CX * 11:02 The Importance of Continuous Testing and Monitoring * 13:51 Ensuring Scalability and Compliance in AI Solutions * 15:45 The Future of AI Agents in Customer Experience * 18:18 Integrating AI into Existing Workflows * 22:22 Key Takeaways for CIOs and IT Decision Makers
About CyaraCyara is the global leader in AI-powered customer experience assurance, committed to eradicating bad CX. As the only unified platform for continuous testing and monitoring across voice, digital, messaging, and conversational AI channels, Cyara empowers hundreds of the world’s leading brands to optimise more than a quarter of a billion customer interactions every year. From full customer journey visibility to AI governance and compliance, Cyara ensures every touchpoint works flawlessly, helping businesses deliver secure, friction-free, and high-quality CX at scale.
"If you are not using it and don't understand it, you are losing big time because you reinvent that wheel of durable execution yourself, and it's hard," reasons Maxim Fateev, Co-Founder and CTO of Temporal Technologies.
In a recent episode of the Tech Transformed podcast, Fateev explored the concept of durable execution. This approach not only improves software reliability but is also becoming essential for the next generation of AI agents and orchestration.
What is Durable Execution?Durable execution, a concept trademarked by Temporal Technologies, changes how developers build reliable applications. "The idea is simple–we preserve the full state of code execution all the time," he explained.
Imagine a function that makes a series of API calls. If the process running that function crashes, even days later, "we can bring that function back in exactly the same state, still blocked on the same API call with all the variables and state there, and deliver the response. Then it will continue to the next line of code."
From a programming point of view, the function actually “never crashed. It just seamlessly waited for three days, blocked on that API call, and then continued execution," says Fateev.
This ability to provide "crashless execution" changes how developers approach building reliable software. It allows functions to run for long periods, even a year, without interruption or data loss.
Temporal's Role in OpenAI's Image Generation Alluding to Temporal’s use case, Fateev referenced their contribution to OpenAI’s image generation code. He stated, "Every time you generate the image using OpenAI, it uses Temporal behind the scenes."
"Image generation is orchestration. It's not just like one API call. There are a lot of API calls which need to happen to generate an image, and Temporal’s tech guarantees execution."
While a strong tool for AI, durable execution has many uses beyond that. Fateev notes that Temporal has also been used for "driving large-scale operations with an added productivity advantage, and it’s also for a startup with two people with a small-scale solution.”
From infrastructure automation, like HashiCorp Cloud, and data handling to key business tasks such as customer onboarding and instant payments, including UPI in India and similar systems in Brazil, Temporal shows its worth in various industries.
"Every Snapchat story is an important workflow,” Fateev tells Dua. Leading AI companies like Replit, Abridge, and OpenAI are using Temporal to power their workflows.” The main idea stays the same: "Nearly every time you need to run any business logic reliably, it works well."
Takeaways* Durable execution is a new paradigm that enhances software reliability. * It can significantly increase developer productivity by 5X to 10X. * The concept allows for crashless execution of business applications. * AI agents face reliability challenges that durable execution can address. * Temporal's architecture ensures data is encrypted and secure. * Open-source solutions provide a competitive advantage and prevent vendor lock-in. * Temporal is the only production-ready solution for durable execution. * The technology is used by major companies like OpenAI, with potential updates like Netflix, Snapchat * Temporal can orchestrate complex workflows, including AI and business processes. * The system is applicable in various industries, including financial services, retail, logistics, and more.
Chapters00:00 Introduction to Durable Execution
03:07 The Concept of Durable Execution
06:00 AI Agents and Reliability Challenges
09:07 Cybersecurity and Data Protection
11:53 Open Source Advantage of Temporal
14:57 Temporal's Unique Position in the Market
18:12 Real-World Applications of Temporal
About Temporal TechnologiesTemporal is changing how modern software is built through its open-source Durable Execution platform. By guaranteeing the execution of complex workflows even in the face of system failures, Temporal allows developers to focus entirely on business logic rather than infrastructure complexities—increasing developer velocity. Its polyglot capabilities allow seamless orchestration across multiple programming languages, making it ideal for both traditional enterprise applications and next-generation AI workloads. Temporal Cloud, the company's managed service backed by the originators of the project, has been adopted by thousands of leading enterprises. Learn more at www.temporal.io.
Enterprise data management is undergoing a fundamental transformation. The traditional data stack built on rigid pipelines, static workflows, and human-led interventions is reaching its breaking point. As data volume, velocity, and variety continue to explode, a new approach is taking shape: agentic data management.
In this episode of Tech Transformed, EM360Tech’s Trisha Pillay sits down with Jay Mishra, Chief Product and Technology Officer at Astera, to explore why agentic systems powered by autonomous AI agents, Large Language Models (LLMs), and semantic search are rapidly being recognised as the next generation of enterprise data architecture.
The conversation explores the drivers behind this shift, real-world applications, the impact on data professionals, challenges faced by agentic platforms, and the future of data stacks. Jay emphasises the importance of starting small and measuring ROI to successfully implement agentic solutions.
What is Agentic Data Management?At its core, agentic data management is the application of intelligent, autonomous agents that can perceive, decide, and act across complex data environments. Unlike traditional automation, which follows predefined scripts, agentic AI is adaptive and self-directed. These agents are capable of learning from user behaviour, integrating with different systems, and adjusting to changes in context, all without human prompts.
As Jay explains, "An agentic system is one that has the agency to make decisions, solve problems, and orchestrate actions based on real-time data and context, not just on training data.
Takeaways* Agentic data management is the next evolutionary step in data architecture. * Agents are autonomous and can make decisions on the fly. * The demand for agentic solutions is increasing due to data volume and AI strategy needs. * Maturity of foundation models enables near-human reasoning capabilities. * Real-world applications of agentic AI include insurance claim processing. * Data engineers will focus on policy and guardrail creation rather than coding. * Governance, debt and hallucinations are significant challenges in agentic platforms. * The future of data stacks will include declarative control plans and enhanced memory layers. * Analysts will play a crucial role in defining policies for agentic systems. * Starting small and demonstrating ROI is key to successful agentic implementation.
Chapters00:00 Introduction to Agentic Data Management
02:58 Understanding Agentic Data Management
06:58 Drivers of Change in Data Management
10:03 Real-World Applications of Agentic AI
14:15 Impact on Data Engineers and Analysts
16:43 Challenges and Limitations of Agentic Data Platforms
20:03 Future of Data Stacks
23:31 Final Thoughts on Agentic Data Management
About Jay MishraJay Mishra is the Chief Product and Technology Officer at Astera Software, with over two decades of experience in data architecture and data-centric software innovation. He has led the design and development of transformative solutions for major enterprises, including Wells Fargo, Raymond James, and Farmers Mutual.
Known for his strategic insight, technical leadership, and passion for empowering organisations, Jay has consistently delivered intelligent, scalable solutions that drive operational excellence and financial success.
For more information, please visit: https://em360tech.com/. Follow our LinkedIn for daily tech insights and YouTube @EM360TechInterviews
"There's a lot of hype with the AI agents and their productivity and potential outcomes. AI Agents are quite amazing, says Eric Paulsen, EMEA Field CTO at Coder.
In this episode of the Tech Transformed podcast, Shubhangi Dua, Podcast Host and Producer at EM360Tech, talks to Paulsen about the constantly advancing role of AI agents in development environments.
Paulsen explains how AI agents can help developers by handling simpler tasks, almost like having assistants or junior developers to assist them. Not only would this boost productivity and time efficiency, but the technology will also ensure human oversight.
The conversation further explores how AI fits into cloud development environments, especially in regulated areas like finance, where security and scalability matter most. Paulsen stresses the value of internal AI models and points out Coder's unique role in offering infrastructure-neutral solutions that meet various enterprise needs.
AI Agents Are More Than Just Code WritersWhen people hear "agentic AI" or "coding agents," there's often a misconception about fully autonomous coders. However, Paulsen clarifies, "That's a far stretch from where we currently have been, which is with just AI-assisted IDE extensions such as GitHub, Copilot, Amazon Q Developer and systems of that nature."
Coder focuses on agentic solutions that have a human developer in the loop, emphasising Paulsen. “Think of an AI agent as a junior engineer working alongside you,” Paulsen explains.
"If anything, it’s improving the output of the human engineer by having an autonomous or artificial or AI process. In the same development environment, working on other tasks that might not necessarily be as complex," he adds. This means developers can offload simple tasks like bug fixes or dependency updates, freeing them to focus on more complex features.
How to Scale AI Agents Securely in Enterprises?For large financial institutions that have hundreds and even thousands of software engineers, deploying AI agents at scale requires a consistent and secure approach. Cloud development environments provide the best way to deliver and package these agents for developers.
The main concern for enterprises is ensuring data security in addition to stopping AI agents from "running wild on a laptop." Paulsen stresses the need for agents to work within an "isolated compute," with "boundaries around those agents inside of that isolated compute."
Such a secure environment provides guardrails to synchronise and boost productivity between humans and AI while preventing sensitive data breaches or "hallucinations" from the AI.
Additionally, financial institutions are now increasingly developing their own internal AI models. Paulsen mentions, "What these institutions need is an AI agent that is trained on the internal dataset and internal LLM that is built within the firm so that it can make those decisions and return the relevant output to the data scientist or software engineer." This move towards self-hosted LLMs and internal AI infrastructure is essential for adopting enterprise-grade AI.
The ultimate message is that cloud development environments should provide the framework where AI agents are running inside an enterprise’s infrastructure. “AI agents have access to the data, and they're observed and governed by a set of security standards that you have internally,” says the EMEA Field CTO at Coder.
TakeawaysAI agents can assist developers by handling simpler tasks.
Human oversight is essential in AI-assisted coding.
Cloud development environments enable high-performance workloads.
Security is critical for AI agents in regulated sectors.
Internal AI models are necessary for financial services.
Coder offers infrastructure-neutral solutions for enterprises.
AI agents can automate maintenance tasks for platform engineers.
Scalability of AI agents is vital for large organisations.
Enterprises need to consider their internal data for AI agents.
Deployment of AI agents must be secure and efficient.
Chapters00:00 Introduction to AI Agents in Development
02:12 Understanding Agentic AI and Its Role
06:24 Cloud Development Environments and AI Integration
08:47 Ensuring Security and Productivity with AI Agents
11:12 Scaling AI Agents in Regulated Environments
13:10 The Importance of High-Performance Developments
15:52 Internal AI Models in Financial Services
17:47 Coder's Unique Position in the Market
19:27 Key Takeaway for Decision Makers
For more information, please visit: https://em360tech.com/ Follow our LinkedIn for daily tech insights: https://www.linkedin.com/company/2403360/admin/dashboard/ and YouTube @EM360TechInterviews
Are we heading for a future where AI knows everything but won’t bother explaining it to us?
Advancements in artificial intelligence are rapidly transforming the way industries operate and influencing the future of society as a whole. AI has become a force behind breakthrough technologies such as big data analytics, robotics, and the Internet of Things (IoT). The rise of generative AI has only accelerated its adoption and broadened its impact across multiple sectors.
Navigating the Displacement DilemmaIn this episode of Tech Transformed, host Trisha Pillay at EM360Tech sits down with Nigel Cannings, author and AI expert, to explore one of the most pressing questions of our time: what happens to human expertise in the age of rapid AI advancement?
Nigel Cannings warns that while technology promises efficiency and faster results, it also encourages dependency. Our patience has run thin, and in our rush for instant answers, we may be undermining the very systems that develop human expertise. “I’m kind of fascinated by the change we’ve seen in how we process information,” Cannings reflects.
He describes the displacement dilemma as the idea that tools meant to democratise knowledge could actually erode the skills and pathways that build true mastery. He worries about people losing jobs or being too dependent on technology to even start careers. “I’m really interested to talk to people who’ve been affected by the displacement dilemma, people who are losing their jobs, people who think they’re going to lose their jobs, people who can see the erosion of expertise and skills,” Cannings explains.
The Future of AIAs artificial intelligence evolves at breakneck speed, we face a harsh reality: the gap between human and AI intelligence could become so wide that we might not even understand the systems we build. Worse still, AI itself may have no incentive to help us understand it. At that point, it stops being just a tool and becomes an autonomous entity with its private reality.
In 2025, Chief AI Officers report an average AI ROI of 14 per cent, as many AI programs move beyond pilot programs to larger implementations at scale. This is proof that as AI continues to evolve at an unprecedented pace, understanding its implications is important, both for industries navigating these changes and for society adapting to a new technological landscape.
Takeaways* AI tools meant to democratize knowledge may erode human expertise. * The displacement dilemma highlights the need for future experts. * Information consumption is changing due to AI algorithms. * AI relies heavily on large GPU cards for processing. * Current AI models are prediction machines, not truly intelligent. * Future AI may have limited intelligence in specific areas. * The race in AI development is driven by financial incentives. * Legislation is crucial for addressing AI's potential harms. * Humans will always be needed in certain job roles.
Chapters00:00 Introduction to AI and Human Expertise
04:06 The Displacement Dilemma: Erosion of Expertise
06:59 Changing Information Consumption in the AI Era
10:07 Technical Aspects of AI: Data Centres and Encryption
15:42 Limitations of AI in Scientific Discovery
20:22 The Future of Superhuman AI
23:23 The Race in AI Development
28:18 Navigating the Future of AI Leadership
About Nigel CanningsNigel Cannings is a leading expert in speech technology and AI, specialising in applications within the legal and financial sectors. With over 20 years of experience, he holds more than a dozen patents in Natural Language Processing, Cryptography, AI, and Speech Processing. A former city lawyer, Nigel shifted his focus to technology, pioneering innovations such as the integration of GPU technology into speech recognition and advancing work in Explainable AI, AI Ethics, and Secure Search.
Based in London, Nigel is a respected thought leader exploring the evolving relationship between AI and human expertise.
"AI may be both the driver and the remedy for multi-cloud adoption," says Dmitry Panenkov, Founder & CEO of emma, alluding to the vast potential and possibilities Artificial Intelligence (AI) and multi-cloud strategies offer.
In this episode of the Tech Transformed podcast, Tom Croll, a Cybersecurity Industry Analyst and Tech Advisor at Lionfish, speaks to Panenkov. They talk about the intricacies of powering multi-cloud systems with AI, offering valuable insights for businesses aiming to tap into the full potential of both.
They also discuss data fragmentation, interoperability issues, and security concerns.
AI Adoption in Multi-CloudAddressing the key challenges of AI adoption in multi-cloud environments, Panenkov spotlights one of the most prominent issues – data fragmentation.
“AI thrives on unified data sets. But multi-cloud setups often lead to data silos across the different platforms,” the founder of emma, the cloud management platform, explained.
Data silos creates a disconnect which makes it increasingly challenging for AI models. It makes it harder for AI models to access and process the huge amounts of data needed to function efficiently.
Instead, Panenkov stresses the potential of AI to drive multi-cloud adoption by optimising workloads and automating policies.
In addition to data fragmentation, the lack of interoperability and tooling presents another challenge when integrating AI with multi-cloud. This is where Inconsistent APIs, a lack of standardisation, and variations in cloud-native tools create major friction. The difference is evident when building AI pipelines across diverse environments.
Panenkov also pointed out the impact of latency and performance. He says, "Even Kubernetes is sensitive to latency. When we talk about AI and inference, and I'm not even talking about the training, I'm saying that inference is also sensitive."
Without proper networking solutions, running AI workloads effectively in multi-cloud environments becomes next to impossible.
Of course, security and compliance are a looming challenge for all enterprises across varying industries. Managing data protection in different jurisdictions and environments adds layers of legal and operational complexity.
Despite these challenges, AI has significant advantages in multi-cloud systems that well surpass any challenges.
Intelligent Orchestration is the Key to Successful Multi-Cloud AdoptionThe main topic of the conversation was how AI can actually help overcome the complexities of multi-cloud adoption. As the founder of a cloud management platform, Panenkov believes that AI may be both the driver and the remedy for multi-cloud adoption.
For example, Panenkov describes how AI can orchestrate workload placement and resource allocation. “We can look into and predict the behaviour of the workload, and we can optimise the infrastructure for these workloads, and allocate resources, helping our customers to start scaling.”
The promise of portability offered by platforms like Kubernetes is often "undercut by vendor-specific customisations," noted Panenkov, and AI can address this through intelligent orchestration.
AI can enhance workload placement, resource allocation, and even latency routing.
Additionally, AI can automate policies, enforcing security, compliance, and cost rules across various clouds. This "simplification" is critical. Panenkov drew a parallel to the way unified interfaces abstract complexity for users, stating, "All these AI agents have to abstract, evade the complexity for the developers and operators alike."
The impact on business is significant: faster product delivery, accelerated innovation, and the ability to leverage "best of breed" tools without heavy vendor lock-in. This leads to higher agility in scaling and adapting applications to market needs more quickly.
Takeaways* AI thrives on unified data sets. * Data fragmentation leads to silos in multi-cloud environments. * Kubernetes can complicate multi-cloud strategies due to latency issues. * Edge computing adds complexity but offers low-latency benefits. * AI can optimise workload placement and resource allocation. * AI helps enforce security policies across multiple clouds. * A multi-cloud strategy can reshape how organisations innovate. * Organisations can mitigate risks by avoiding vendor lock-in. * Building intelligent abstraction layers is crucial for flexibility. * Leaders should focus on orchestration and not force-fit clouds.
Chapters00:00 Introduction to AI and Multi-Cloud Challenges
02:31 Key Challenges in Multi-Cloud AI Adoption
11:43 AI as a Driver for Multi-Cloud Adoption
16:33 Impact of Multi-Cloud on Innovation and Risk Management
23:00 Final Thoughts and Advice for Leaders
About Emmaemma helps organisations use real multi-cloud options and unlimited computing power to get the most from their cloud and AI efforts. With support from various providers, including hyperscale and EU-regional, and environments such as on-prem, private, and public, emma enables organisations to reach their business goals now and in the future.
Unlike solutions that focus on just certain parts, emma takes a complete approach to cloud management. By combining AI-driven performance, cost, and network management with tools for optimisation and governance, emma delivers a smart platform that makes cloud operations easier and boosts efficiency.
"Certainly an exciting time for data centers, private and public alike, isn't it?" This opening remark from Tom Croll of Lionfish Tech Advisors set the stage for a compelling discussion with Ryan Mallory, President and COO of Flexential, on the recent episode of the Tech Transformed podcast.
The speakers discuss the current AI scenario's impact on data centers, high-density computing, and cloud infrastructure. This is where Flexential comes in. Mallory stresses the importance of trust and verification in AI deployment, especially regarding security and data privacy, which Flexential has established a reputation for.
“How to adapt to the AI boom?” is one question everyone’s asking, Mallory says. From a service provider perspective, it's a "proverbial gold rush" for powered land. This is essential for building the relevant AI infrastructure that will serve as early entry points.
Flexential's survey reveals that a staggering "90% of people surveyed are contemplating an AI strategy." The number spotlights the widespread interest and impending demand. “This isn't a short-term trend,” says Mallory. He also projects a "12-year" development cycle for AI infrastructure, emphasizing the long-term commitment required from the industry.
Scaling Up for AIThe unprecedented growth in AI demands specialized infrastructure, especially concerning the sustainable use of AI and running data centers, and strong strategies for scalability, reliability, and cost-effectiveness.
Flexential is uniquely positioned to meet this challenge. "We've been developing high-performance compute facilities for over 10 years," he states. Their "Gen 4 and Gen 5 sites can cool 50 kilowatts per cabinet air-cooled."
This information has allowed them to readily support the requirements of H100 and H200 type deployments, not just for service providers, but also for ramping deployments in the healthcare and financial sectors.
Looking ahead, the data center industry is preparing for even higher-density racks and the widespread adoption of liquid cooling. While "all of our sites are liquid-cooled ready," Mallory says, thorough airflow studies and CFD analysis show liquid cooling is genuinely necessary.
Flexential’s air-cooled solutions are already handling "high-dense pods for some of the companies that have recently gone public and other companies that are out there that you hear about in this AI service provider realm,” Mallory added.
Takeaways* 90% of surveyed companies are considering an AI strategy. * The AI industry is experiencing a gold rush for infrastructure. * Data centers must adapt to high-density computing demands. * Liquid cooling is essential for high-performance AI deployments. * AI regulations are shaping how data centers operate. * Trust but verify is crucial for AI deployment. * AI democratization is vital for businesses of all sizes. * Flexential is focused on providing scalable AI infrastructure. * Security policies are essential for protecting sensitive data. * AI can enhance productivity, but it requires human oversight.
Chapters00:00 The Impact of AI on Data Centers
02:51 Infrastructure Challenges and Solutions
05:59 Navigating AI Regulations and Security
08:59 Democratization of AI for Businesses
12:03 Key Takeaways for CIOs
About FlexentialFlexential enhances organizational operations by providing customized hybrid IT solutions through its FlexAnywhere platform. This platform offers integrated colocation, cloud, connectivity, data protection, and managed and professional services. Backed by three million square feet of data center space across 19 highly connected markets, Flexential helps customers navigate complex IT journeys.
The FlexAnywhere solutions empower customers to address their most intricate hybrid IT infrastructure needs, including reliability, performance, agility, scalability, and seamless application and user interconnection.
Takeaways* #AI #analysts are crucial for integrating AI into business processes. * Organisations need to rethink their data management strategies for AI. * AI #data clearinghouse concepts help manage data access and security. * Cross-functional collaboration is essential for successful AI integration. * AI can enhance employee effectiveness rather than replace jobs. * The future of work will see AI analysts in various business functions. * Companies must adapt quickly to remain competitive in the AI landscape.
SummaryThis episode of the #TechTransformedPodcast explores the role of AI Analysts. Host Keyari Page is joined by guest speaker Andy MacMillan, CEO of Alteryx.
We learn that the term AI Analyst refers to an emerging role of #professionals who help organisations rethink their processes, workflows, and employee capabilities through the use of AI.
This new role bridges the gap between AI systems and tangible #businessoutcomes. In the podcast, we also cover the importance of managing data for AI through an “AI data clearing house”. This helps business analysts prepare data for AI projects.
Through this system, analysts and business owners are able to ensure that compliance and security measures are met.
Tune in for insights on how AI is reshaping roles, boosting efficiency, and transforming customer experiences in the evolving business landscape.
For more tech insights visit: em360tech.com
"The concept of Zero Ticket IT is that instead of reacting to the ticket and trying to solve the ticket, you go directly to the source of the issue." This statement by Sean Heuer, CEO of Resolve Systems, sets the stage for this episode of the Tech Transformed podcast.
Shubhangi Dua, podcast host and producer at EM360Tech, , sits down with Heuer to unpack the ambitious yet achievable vision of Zero Ticket IT and how both agentic AI and intelligent automation are poised to change IT operations.
Traditional IT ticketing systems, with their reactive nature and reliance on human intervention, are facing an overdue overhaul. Heuer shares a path towards a more efficient, proactive, and ultimately frictionless IT experience.
What is Zero Ticket IT?Zero Ticket IT shifts the focus from reacting to individual tickets to directly addressing the source of the issue. As Heuer explains, a major portion (roughly 70 per cent) of IT tickets originate from employee requests and range from password resets to connectivity problems. Another substantial chunk comes from machine alerts, often leading to "alert storms" where a single underlying issue triggers a cascade of notifications.
For instance, imagine an AI-powered conversational interface that can understand an employee's problem. Now this problem can be resolved using a vast knowledge base and service catalog.
"There's no reason for a human to intervene if you locked your account. If you need to reset your password. There's no reason for a human to have to handle that. It should happen instantaneously," Heuer elaborates. This self-service approach immediately reduces ticket volume by a significant margin.
AI Automation to Resolve Substantial IT RequestsAutomation can also solve challenges head-on by integrating AI operations (AIOps) solutions to analyse countless machine alerts, thereby identifying correlations and spotting the root cause.
"Instead of getting a thousand incidents you have to manage, you get one incident," Heuer states, allowing for precise and rapid resolution.
Heuer highlights that by implementing these two layers — direct interfaces for employees and intelligent automation for machine alerts — organisations can achieve a 60 per cent to 70 per cent reduction in total ticket volume..
Some Resolve Systems customers have even seen up to an 80 per cent reduction, with Heuer noting: "We have a telco customer that's gotten to 80 per cent reduction of incidents in their network and infrastructure. We have a retail company that has gotten to 75 per cent reduction. Auto-remediation is the solution for all employee requests."
Heuer envisions a future where the core role of an IT technician evolves from reactive ticket-solving to proactively managing and optimizing AI and automation systems. The focus will be on identifying patterns, improving knowledge articles, and developing new automations.
The Resolve System CEO said that IT organisations must shift their focus from traditional metrics like agent utilisation and first-touch resolution to employee productivity and digital employee experience.
Forrester Research suggests that for every 1,000 employees, companies can lose $1.5 million to $3 million in productivity due to IT-related downtime.
"IT's job isn't to work tickets. Its job is to make the business productive, to keep it productive," Heuer says.
"Start now. Stop waiting, stop with the FUD, stop with the experimenting. Instead, apply AI to a problem. This is real. This isn't a future fantasy world but it’s something you could do today, right now,” the CEO added.
To learn more about Resolve Systems and their work in this space, visit resolve.io and follow them on social media: Resolve Systems LinkedIn and Resolve Systems YouTube.
Takeaways* Zero Ticket IT aims to solve IT issues at the source. * Agentic AI can significantly reduce ticket volume. * The focus of IT should shift from ticket management to employee productivity. * AI can help eliminate human error in IT operations. * Education and transparency are crucial for building trust in AI. * Employee experience directly impacts productivity and engagement. * IT organisations should measure success through employee productivity metrics. * Automation can lead to significant cost savings for businesses. * The future of IT roles will involve managing AI and automation. * AI's impact on the workforce raises important economic questions.
Chapters00:00 Introduction to Zero Ticket IT
06:52 Understanding Agentic AI and Automation
13:50 Shifting Focus: From Tickets to Employee Productivity
18:55 Challenges and Trust in AI
26:00 Future Skills for IT Teams
30:59 The Future of Work and AI
About Resolve SystemsResolve is redefining IT and network operations with an agentic automation and orchestration platform built for a Zero Ticket future. Our AI agents don’t just assist—they autonomously detect, diagnose, and resolve incidents before they impact the business. By transforming reactive, manual workflows into proactive, self-healing systems, Resolve slashes ticket and alert noise by up to 90 per cent, reduces MTTR from hours to minutes, and empowers IT teams to scale without increasing headcount.
Trusted by some of the largest global enterprises, Resolve empowers IT teams to move from reactive firefighting to proactive transformation. Learn more at resolve.io
Are you a CIO, CTO, CISO, or IT decision maker in the restaurant or retail industry, grappling with rising costs and tariffs to keep up with the rapid pace of technological change? The pressure to create high-quality solutions with AI while managing existing infrastructure can be challenging.
In this episode of the Tech Transformed Podcast, Shubhangi Dua, podcast host and producer at EM360Tech sits down with Keith Szot, SVP Chief Evangelist at Esper, to talk about how enterprises can extend the lifespan of their current edge devices. They also discuss how such enterprises can easily integrate Edge AI solutions without a complete hardware overhaul.
"Starting out with IT Ops is a tough endeavor. If you are running revenue producing key business operating systems that are out in the field, it's not an easy job,” stated Szot. “With everything that's going on these days, it's not getting any easier. Now, considering tariffs, the impact of AI in terms of how you look at your hardware refresh cycle, it's really tough.”
‘Android is the key’Specifically alluding to edge devices in restaurant and retail, Szot reflecting on the limitations of traditional operating systems says Android is the key. "If you look at the ISV and the solution provider community, the best and latest solutions for these markets are built on Android.”
“You look at enterprise developers, if you're developing in-house, arguably it's a lot easier to find an Android developer and build a team to focus on creating Android applications than it is in Windows,” he added. “Android is the biggest developer ecosystem in the world in the history of humankind.
Unlike operating systems tied to rapid consumer hardware upgrades, Android offers the flexibility of an open-source project. It allows for greater control over updates and longevity.
Szot believes that the Android UX is more intuitive. He says that people use phones all the time. “And even if you're an iOS user, the paradigm, if you go to Android, still has a familiarity where the bar to understand how to use the software in the device arguably is lower." This minimises training needs and improves operational efficiency.
In a nutshell, the conversation touches on extending hardware lifecycles for edge devices in the restaurant and retail industry, primarily through the Android flip, to enable the integration of AI at the edge and prepare for future trends like robotics and 5G.
Key Takeaways * Extending hardware lifecycles is crucial for cost management. * Android is becoming the preferred OS for enterprise solutions. * AI can enhance customer experiences in retail environments. * Robust hardware design is essential for longevity. * Transitioning from Windows to Android can save costs. * Edge AI allows for on-premise processing without latency issues. * Physical AI will revolutionize the retail and restaurant sectors. * Quantum computing poses both opportunities and challenges for security. * Device management is key to maintaining operational efficiency. * Innovative hardware designs will create new customer experiences.
Chapters00:00 Introduction to Edge Devices and AI
03:12 Extending Hardware Lifecycles in Retail
06:06 Transitioning from Windows to Android
08:56 Practical Applications of Edge AI
11:47 AI Integration in Restaurant Kiosks
14:55 Managing Existing Hardware with Software Solutions
18:01 The Role of Edge AI in Future Technologies
20:51 Physical AI and Robotics in Retail
24:03 Future Trends: Quantum Computing and Device Management
27:07 Innovations in Hardware for Enhanced Experiences
30:14 Key Takeaways for IT Decision Makers
About EsperFounded in 2017, Esper is a company known for its modern device management platform, going beyond traditional MDM to power exceptional device experiences with a focus on automation. They aim to redefine how businesses manage their company-managed hardware, particularly Android devices, driving towards a DevOps future.
Esper's core offerings provide advanced automation and unmatched operational efficiency, eliminating re-provisioning and enabling exception-based management. Their powerful and scalable platform features kiosk mode, remote control, software deployment, and device grouping, with tailored industry solutions for sectors like healthcare, retail, hospitality, and logistics. They also maintain strong partnerships with key players such as Zebra, Lenovo, and Intel.
The ability to effectively manage and optimise data is key in an organisation today. But with the sheer volume and complexity of enterprise data, traditional methods are struggling to keep up with the change. This is where the agentic AI approach has swooped in to transform how organisations handle their most valuable resource.
"The promise of AI and agentic AI is that we're now building very meaningful automation into the platform such that these teams of 10 are now able to basically actually capture all of the metadata about all of the data cataloged across their entire company," stated Corey Keyser, the head of artificial intelligence (AI) at Ataccama.
In this episode of the Tech Transformed podcast, Shubhangi Dua, a B2B tech journalist and Podcast host at EM360Tech speaks with Keyser from Ataccama, about agentic AI, data quality, and data governance.
They explore how intelligent automation is shaping enterprise data management, the role of AI in improving data quality, and the importance of trust in AI systems. Additionally, Keyser shares significant insights on Ataccama's unique approach to data governance, practical applications of their AI agent, and how they are keeping pace with the constantly changing AI regulations.
While the speed and efficiency of AI are undeniable, the question of trust remains. Keyser addressed this directly: "The short answer is you can never fully trust these automations, right?
“That's why it's really critical to always have data stewards that we will serve. We will always have data engineers that we will serve. We're just looking to improve their productivity. We always assume that there will be humans in the loop who are verifying the tasks orchestrated by AI agents."
Ataccama's One AI Agent exemplifies the practical application of these principles. Keyser added that the AI agent can go and create data quality rules in bulk. “Go through the evaluation and testing of those quality rules in bulk, and then also assign the rules in bulk. Something that would take potentially weeks, can now actually kind of take hours depending on the person."
Takeaways* Agentic AI is about dynamic planning and semi-autonomous task execution. * Data governance involves cataloging and managing organisational data. * Data quality assessment is crucial for ensuring high trust in data. * AI can significantly speed up the creation of data quality rules. * Human oversight is essential in AI-driven automation processes. * Atacama's AI agent improves productivity for data management teams. * Regulatory compliance is a growing concern for AI applications. * User experience is key to successful AI integration in organisations. * The relationship between data and AI is symbiotic and essential. * Organisations must adapt to evolving AI regulations and standards.
Chapters00:00 Introduction to Agentic AI and Data Governance
02:41 Understanding Data Quality and Governance
06:30 The Role of AI in Data Management
11:14 Practical Applications of One AI Agent
15:46 Differentiating Atacama in the AI Landscape
19:37 Case Studies of Transformation
20:05 Integrating Data Quality and Governance
22:07 Navigating Regulatory Changes
24:19 Enhancing User Experience with AI
25:29 Key Takeaway for CIOs
“Before starting a new AI project, it is really worthwhile defining the business priority first,” asserts Joanna Hodgson, the UK and Ireland regional leader at Red Hat.
“What specific problem are you trying to solve with AI? Do we need a general purpose AI application or would a more focused model be better? How will we manage security, compliance and governance of that model? This process can help to reveal where AI adoption makes sense and where it doesn't," she added.
In this episode of the Tech Transformed podcast, host Shubhangi Dua, podcast producer at EM360Tech speaks with Hodgson, a seasoned business and technical leader with over 25 years of experience at IBM and Red Hat. They talk about the challenges of scaling AI projects, the importance of open source in compliance with GDPR, and the geopolitical aspects of AI innovation.
They also discuss the role of small language models (SLMs) in enterprise applications and the collaboration between IBM and Red Hat in advancing AI technology. Joanna emphasises the need for a strategic approach to AI and the importance of data quality for sustainable business practices. While large language models (LLMs) dominate headlines, SLMs offer a cost-effective and efficient alternative for specific tasks.
The podcast answers key questions, like ‘how do businesses balance ethical considerations, moral obligations, and even patriotism with the drive for AI advancement?’ Hodgson shares her perspective on how open source can facilitate this balance, ensuring AI works for everyone, not just those with the deepest pockets.
Hodgson also provides her vision on the future of AI. It comprises interconnected small AI models, agentic AI, and a world where AI frees up teams to create personal connections and exceptional customer experiences.
Takeaways* Curiosity is a strength in technology. * AI is becoming embedded in existing applications. * Regulatory compliance is crucial for AI systems. * Open source can enhance trust and transparency. * Small language models are efficient for specific tasks. * AI should free teams to create personal connections. * A strategic AI platform is essential for businesses. * Data quality is key for sustainable business success. * Collaboration in open source accelerates innovation. * AI can be used for both good and bad outcomes.
Chapters00:00 Introduction to the Tech Transform Podcast
01:35 Pivotal Moments in Joanna's Career
05:12 Challenges in Scaling AI Projects
09:15 Open Source and GDPR Compliance
13:11 Regulatory Compliance and Data Security
17:30 Geopolitical Aspects of AI Innovation
22:31 Collaboration Between IBM and Red Hat
23:58 Understanding Small Language Models
29:54 Future Trends in AI and Sustainability
About Red HatRed Hat is a leading provider of enterprise open source solutions, using a community-powered approach to deliver high-performing Linux, hybrid cloud, edge, and Kubernetes technologies. The company is known for Enterprise Linux.
They offer a wide range of hybrid cloud platforms and open source technologies—including AI, virtualisation, edge, app development, and automation solutions. The hybrid cloud solutions are built to run their customers’ most important, most complex projects—from the datacenter to clouds to the edge. Their open ecosystem of partners and communities aim to ensure existing investments stay protected, providing unmatched freedom and choices to change, flex, reinvent, or stay the course.
What is Open Source Software (OSS)?Open source software (OSS) refers to the source code of software that is relatively liberally available for use, modification, and distribution. The source code knowledge is accessible with few restrictions.
Enterprise open source software is supported by a vendor, usually via a subscription fee. For example, the vendor stabilises and quality-assures the software, certifies it works with an ecosystem of hardware and software, secures it and provides technical support.
OSS is a driver of collaborative development of AI models, fostering transparency, team-backed innovations. This often results in highly adaptable and cost-effective solutions. The open nature allows for peer review, potentially leading to enhanced security and reliability, making it a cornerstone of modern technology.
Takeaways
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Satellitecommunications are essential for remote field teams.
- They provide safety and tracking for workers in isolated areas.
- Disaster preparedness involves proactive planning and communication.
- User-friendly #technology is crucial for effective utilisation.
- Reliable communication impacts day-to-day operations positively.
- Employers show care for employee safety through #satellitetechnology investment.
Summary
In this episode of #TechTransformed, Jonathan Care discusses the importance of satellite communications for field teams. He is joined by Mark O'Connell, EMEA & Asia Pacific General Manager at Globalstar, and Grace Finn, Senior Account Manager at Peoplesafe. Together, they explore how satellite technology enhances safety, disaster preparedness, and operational efficiency for remote, field workers.
We learn the differences between satellite and cell communication. O’Connell emphasises the importance of satellite communication, stating that due to field workers, there is a requirement to not be reliant on cellphone towers.
O’Connell further clarifies that field teams who are working remotely, and are away from terrestrial communications, need access to constant communication.
Finn also expresses the importance of field worker safety, sharing: “If the unforeseen does happen, they’re protected.” She emphasises that organisations should invest in satellite communications to ensure their teams' wellbeing & security.
Tune in to learn the user-friendly aspects of the technology, its features for challenging environments, and the critical role it plays in ensuring reliable communication.
For the latest tech insights and content visit: EM360Tech.com
"Having the insight and being able to stitch together your technical resources and business decisions together, is the prime place where observability can add value to you,” stated Manesh Tailor, EMEA Field CTO at New Relic.
In this episode of the Tech Transformed podcast, Kevin Petrie, Vice President of Research at BARC, speaks with Manesh Tailor about the intersection of artificial intelligence (AI) and observability, and how this is positively changing business operations.
Tailor emphasises how intelligent observability has changed beyond simple monitoring to provide real-time insights into customer experience and the entire technology stack. This enables informed decisions across engineering, operations, and business domains, directly linking technical performance to strategic business outcomes.
He also discusses the different stages observability has been through and where it's leading to now. The current wave, Observability 3.0, takes advantage of AI to predict issues and even enable self-healing systems.
New Relic has embraced this two-way street, using AI within its platform. This was in an ambition to help users and "AI monitoring" to track the performance of language models alongside traditional metrics. Such a platform provides a holistic view of system health and the cost implications of AI deployments.
Alluding to the management of AI-powered applications, Tailor says collaboration is key between application and data science teams. Not only does it provide real time data but as a result leads to efficient decision making.
Futuristically, the speedy proliferation of AI agents has both pros and cons for observability. This is where New Relic comes in. It addresses the challenges by constructing a platform-centric "AI orchestrator" with a growing library of AI-native agents.
In essence, as AI-powered applications become increasingly integral to business operations, intelligent observability is no longer optional.
Takeaways* Observability is crucial for understanding unknowns in systems. * AI enhances observability by providing predictive insights. * The evolution of observability includes intelligent monitoring. * Collaboration between technical and business teams is essential. * Cost efficiency is a key focus in modern observability. * Real-time data is vital for effective decision-making. * Self-healing systems represent the future of observability. * AI and observability must work in tandem for success. * The complexity of systems is increasing, requiring better tools. * Observability is applicable across all organizational levels.
Chapters00:00 Introduction to AI and Observability
03:10 Defining Observability and Its Evolution
05:49 The Role of AI in Observability
08:46 Navigating AI-Driven Applications
11:52 Target Users and Community for Observability
14:57 Collaboration Across Teams
17:55 Challenges and Opportunities in Observability
20:47 The Future of Observability and AI
23:54 Key Takeaways for CIOs and IT Leaders
About New RelicThe New Relic Intelligent Observability Platform empowers businesses to proactively eliminate disruptions in their digital experiences. As the only AI-enhanced platform that unifies and correlates telemetry data, New Relic provides comprehensive clarity across your entire digital landscape.
By processing the optimal data at the right moment, we shift your problem-solving capabilities beyond proactive measures to a predictive stance, maximizing value and controlling expenditures. This is why global enterprises like Adidas Runtastic, American Red Cross, Domino’s, GoTo Group, Ryanair, Topgolf, and William Hill rely on New Relic to fuel innovation, enhance reliability, and deliver outstanding customer experiences that drive growth.
Takeaways
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AIagents are #autonomous entities that can perceive and act.
- Human oversight is essential in the initial stages of AI implementation.
- Data quality and trust are critical for effective AI agents.
- Guardrails must be integrated into the design of AI agents.
- Modularity in design allows for flexibility and adaptability.
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AI should be embedded in data management processes.
- Collaboration between data and application teams is vital.
Summary
In this episode of #TechTransformed, Kevin Petrie, VP of Research at BARC, and Ann Maya, EMEA CTO at Boomi, discuss the transformative potential of AI agents and intelligent automation in business. They explore the definition of agents, their role in automating processes, and the importance of human oversight.
Maya introduces us into the world of AI agents stating that, at its core, it’s an autonomous entity within #AIsystems that can perceive its environment. This creates a deep dive into how they evolved from traditional automation to “observe, think, and act” in novel and autonomous ways.
Maya addresses AI skepticism by acknowledging its growing autonomy while underscoring the current necessity of human oversight. She also highlights data's crucial influence on an agent's perception and decisions, emphasising the need for quality, trustworthy data in effective AI.
Moreover, Maya and Petrie explore AI's practical implications, pointing to Google's agent-to-agent protocol as vital for managing language model interactions and enabling effective communication across diverse agents within complex systems.
For the latest tech insights visit: EM360Tech.com
"If AI has proven anything, it will change pretty rapidly. Understanding its limitations and not asking too much of it is significant. What’s successful is prototyping tools," said Rob Whiteley, CEO of Coder. "Such tools where AI can create an application, while not the world's most graceful code but will get you to working prototype pretty quickly. That would probably take me days or weeks of research as a developer, but now I have a working prototype so I can socialise it."
In this episode of the Tech Transformed podcast, Dana Gardner, a thought leader, speaks with Rob Whiteley, CEO of Coder, about the transformative impact of agentic AI on software development. They discuss how AI is changing the roles of developers, the cultural shifts required in development teams, and the integration of AI agents in cloud development environments.
Agentic AI is seemingly set up for favourable outcomes. Or is it? Agentic AI is believed to shake-up enterprise IT, offering a productivity boost similar to the iPhone's impact.
This isn't about replacing developers but amplifying their output tenfold. It aims to allow the implementation of rapidly created solutions and iteration that has been unimaginable in the past. This shift requires valuing "soft skills" like communication and collaboration over pure coding proficiency, as developers guide AI "pair programmers."
The synergy of AI agents, human intellect, and Cloud Development Environments (CDEs) is key. CDEs provide secure, governed, and scalable platforms for this collaboration, allowing developers to focus on business logic and innovation while AI handles the coding groundwork. This requires a move from rigid "gates" in development processes to flexible "guardrails" within CDEs. Such a move fosters innovation with built-in control and security.
Flexibility and choice are vital in this constantly advancing AI space. CDEs enable organisations to select the best AI agents for specific tasks, avoiding vendor lock-in by expressing the development environment as code. This leads to practical applications like faster prototyping, enhanced code development, and automated testing, significantly boosting code output. Furthermore, agentic AI democratises development, empowering non-engineers to build solutions.
Preparing for this future requires proactive experimentation through AI labs, engaging early adopters, and viewing AI as an augmentation of human skills. Watch the podcast for more insights on CDEs and the impact of AI agents on enterprise cloud development.
TakeawaysAgentic AI is a transformative technology for software development.
The role of developers is shifting from hard skills to soft skills.
AI agents can significantly increase productivity in coding tasks.
Organizations need to rethink their development strategies to integrate AI.
Cloud development environments are essential for safely using AI agents.
Choosing the right AI agent is crucial for effective development.
Security and governance are critical when integrating AI into development.
AI can empower non-developers to create applications.
Guardrails are more effective than gates in managing AI development.
Organisations should experiment with AI to find the best fit for their needs.
Chapters00:00 Introduction to Agentic AI and Developer Roles
03:20 Transformative Impact of AI on Development
06:50 Cultural Shifts in Development Teams
10:30 Integrating AI Agents in Cloud Development Environments
12:49 Choosing the Right AI Agents
15:21 Security and Governance in AI Development
17:29 Coder's Role in the AI Development Landscape
20:14 Expanding Development Beyond Traditional Roles
23:27 Guardrails vs. Gates in Development
26:56 Practical Applications of AI in Code Generation
29:58 Acquiring AI Agents for Development
32:34 Preparing for the Future of Development with AI
About CoderCoder is a remote-first company with products used by many of the world’s largest enterprises. Coder provides an enterprise platform and open source tools that make it easier than ever to configure, secure, and manage software development environments.
Leave hardware limitations behind and welcome accelerated code execution, providing you and your developers with unmatched efficiency and elevated productivity. This enables an organisation to innovate rapidly and maintain a competitive edge.
Takeaways
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Customersuccess is about helping customers get value from products.
- The perception of customer success is shifting from a cost centre to a revenue generator.
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AI can enhance customer success by providing predictive insights and automating processes.
- Customer success teams are uniquely positioned to identify upsell and cross-sell opportunities.
- Collaboration between customer success and sales teams is essential for maximising revenue.
- The integration of AI tools can streamline customer success operations.
Summary
Ever wonder how to transform existing customers into your company’s most powerful growth engine? According to Gainsight’s Chief Revenue Officer, Marilee Bear, it starts with one deceptively simple principle: “helping customers get value from your product.”
This #TechTransformed episode features Christina Stathopoulos, Founder of Dare to Data, in conversation with Marilee about the dynamic role of customer success – a powerful avenue for building deeper customer bonds, boosting retention rates, and ultimately achieving significant revenue gains.
Tune in to learn how to unlock the potential of customer success as a catalyst for cross-selling and upselling opportunities. Explore how to equip your customer success teams with commercial acumen and harness their potential as a secret weapon for business growth.
Whether you're a #CRO looking to optimise revenue or a business leader navigating the AI revolution, this episode offers invaluable insights into the future of customer success.
For the latest tech insights visit: EM360Tech.com
Takeaways
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AgenticAI systems can string tasks together for efficiency.
- Real-world applications include supply chain optimisation and knowledge worker augmentation.
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Dataquality is crucial for effective AI implementation.
- Education and understanding of AI's potential are essential for organisations.
- Governance is key to ethical AI deployment.
- Leadership is critical in adopting AI technologies.
- AI will create new job opportunities, not just displace existing ones.
Summary
Jeff DeVerter, Field Chief Technology Officer at Pythian, describes agentic AI as “little workers that are going to go off and all do a job. You're now a manager of these AIs that are going to go off and do some work and come back and give you that work product.”
In this episode of the #TechTransformed podcast, Christina Stathopoulos, Founder at Dare to Data, and Jeff DeVerter explore this concept, revealing how agentic systems are re-shaping real-world business scenarios.
Imagine these agentic AIs as powerful “personal assistants” when empowering leaders to manage data, streamline workflows and drive commercial acumen.
The discussion goes beyond the possibilities addressing how to prepare your data infrastructure, navigate ethical considerations, and understand AI’s impact on employees, delivering crucial takeaways for CIOs.
For the latest tech insights visit: EM360Tech.com
From the integrities of the human workforce embracing enhancing soft skills over hard skills in the enterprise tech space to the adoption of artificial intelligence (AI) agents in customer service, this conversation covers it all.
In this episode of the Tech Transformed podcast, Shubhangi Dua speaks with Nikhil Nandagopal, co-founder and CPO of Appsmith, about the metamorphological impact of AI agents in the workplace. He particularly emphasises the need for organisations to hone in on the advancing capabilities of agentic AI while still maintaining a focus on human collaboration and security.
Takeaways
- AI agents are autonomous entities designed to achieve specific goals.
- The centralisation of data through AI agents simplifies workflows.
- Conversational interfaces are becoming the norm for accessing information.
- Humans remain integral to AI workflows, acting as moderators.
- Job roles will evolve, requiring new skills and adaptability.
- Critical thinking is essential when interacting with AI outputs.
- Cybersecurity is a major concern with centralised AI systems.
- Self-hosting AI solutions can mitigate cybersecurity risks.
- The future of work will reward soft skills over hard skills
Chapters
00:00 Introduction to AI Agents and Their Impact
03:34 The Shift Towards Conversational Interfaces
05:07 Assisted Workflows and Human-AI Collaboration
10:05 Job Market Evolution in the Age of AI
13:23 Critical Thinking in the Age of AI
15:29 Cybersecurity Concerns with AI
20:31 Preparing for Cyber Threats in AI Systems
22:51 The Future of AI Agents in the Workplace
In this episode of the Tech Transformed Podcast, Jon Arnold, Principal of J Arnold Associates speaks with Nikola Mrksic, CEO of PolyAI, discussing all things AI, specifically in contact centres. From the benefits of automation to the emergence of the most trending subject of the year – Agentic AI.
Mrksic particularly spotlights some underutilised capabilities of AI such as how it can manage up to 90% of repetitive duties, allowing human agents to concentrate on other complex tasks. The conversation also explores the transition from basic service to a broader, more holistic customer experience, necessitating the need for rapid adaptation and experimentation.
AI in contact centers isn't just about cutting costs. This conversation shows how it can truly make a difference – giving agents the tools to shine, providing customers with better, more quality experiences, and even letting AI take care of tasks behind the scenes securely, so humans can focus on what truly matters.
Takeaways
- AI is a dominant force shaping technology today.
- Contact centers have a high volume of repetitive tasks suitable for AI.
- AI can automate up to 90% of tasks in contact centers.
- The role of AI is not just cost-cutting but improving service quality.
- Agentic AI can perform tasks on behalf of users asynchronously.
- Customer experience is now a key focus beyond just service.
- Companies must adapt quickly to avoid falling behind competitors.
- Failing fast and experimenting is crucial for success with AI.
- AI can provide insights that traditional methods miss.
- Investing in AI should be about solving problems, not just keeping up with trends.
Chapters
00:00 Introduction to AI in Contact Centers
02:01 Benefits of AI in Contact Centers
07:37 Transforming Customer Experience with AI
15:42 Understanding Agentic AI
21:27 The Shift from Customer Service to Customer Experience
30:25 Advice for Business and CX Leaders
The world is changing faster than ever. Businesses are drowning in data, yet struggling to extract the insights they need to stay ahead. Artificial intelligence (AI) holds the key, but traditional AI models are too slow, too static, and too disconnected from the real world. This is where real-time AI comes in.
Real-time AI empowers businesses to make decisions in milliseconds, reacting to changing conditions and seizing fleeting opportunities. It's about more than just analysing historical data; it's about understanding the present and predicting the future, all in the blink of an eye.
Imagine a world where customer service agents have access to the most up-to-the-minute information, resolving issues before they escalate. Envision supply chains that dynamically adjust to disruptions, ensuring products are always available. Envision marketing campaigns that personalise experiences in real time, maximising engagement and driving conversions.
But real-time AI isn't just about speed; it's also about accuracy. The time to embrace real-time AI is now. Businesses that fail to adapt risk falling behind in an increasingly competitive world. By harnessing the power of real-time data and intelligent agents, enterprises can tap into new levels of performance, innovation, and growth.
In this episode, Shubhangi Dua, an editor and tech journalist at EM360Tech, speaks to Madhukar Kumar, the Chief Marketing Officer at SingleStore, about the transformative potential of real-time AI for enterprises.
Takeaways
- Real-time AI is essential for modern enterprises.
- The evolution from generative AI to real-time AI is significant.
- Data accuracy and freshness are critical for AI success.
- AI agents will collaborate to enhance business processes.
- Enterprises must manage data silos to improve efficiency.
- Smaller companies can leverage AI to create innovative solutions.
- Data governance is crucial for protecting sensitive information.
- Real-time AI can significantly improve user experience.
- AI will enable professionals to focus on higher-value tasks.
- Harnessing data effectively will be a key differentiator for businesses.
Chapters
00:00 Introduction to Real-Time AI and Its Importance
03:03 The Evolution of AI: From Generative to Real-Time
05:54 Real-Time AI in Enterprises: Advantages and Examples
11:01 The Future of AI Agents and Their Collaboration
16:47 Preparing Enterprises for AI: Data Management and Security
20:47 Business Advantages of Real-Time AI and Future Opportunities
In this conversation, Ryan Worobel shares his extensive experience in the technology sector, discussing the evolution from traditional monitoring to observability. He highlights the cultural and technical challenges organizations face during this transition, emphasizing the importance of collaboration and data management. Ryan also explores the role of AI in enhancing IT operations, advocating for a balance between automation and human expertise. He provides insights on implementing AI in organizations, the risks and opportunities associated with it, and the necessity of understanding company culture for successful adoption.
Key Takeaways
- Observability requires a cultural shift towards collaboration.
- Data management is crucial to avoid overwhelming teams.
- AI is transforming IT from reactive to proactive approaches.
- Organizations must start small when implementing AI.
- Understanding company culture is key to AI adoption.
- Uptime is essential; downtime is no longer acceptable.
- AI should supplement human expertise, not replace it.
- Effective data sorting can reduce noise in decision-making.
- Innovation is necessary to maintain a competitive edge.
- Organizations need to establish governance around AI usage.
Chapters
00:00 Introduction to Ryan Worobel and His Journey
07:37 Proactive vs Reactive Approaches in IT
13:31 Implementing AI in Organizations
19:31 Conclusion and How to Connect with Ryan
In this conversation, Sam Page explores the evolving landscape of digital experiences, emphasizing the shift from the information age to the experience age, driven by advancements in AI.
Learn about importance of creating meaningful digital interactions, the challenges posed by biases in AI, and the need for transparency and education in navigating these technologies. Sam introduces a framework for brands to understand, connect, and serve their audiences effectively, highlighting the potential of AI to enhance consumer experiences while addressing concerns about job displacement and data biases.
Key Takeaways
- The digital experience is rapidly changing with AI at the forefront.
- Brands must prioritize meaningful digital experiences to connect with consumers.
- The shift from the information age to the experience age is significant.
- AI can create unique experiences tailored to individual needs.
- Concerns about AI include job displacement and biases in data.
- Transparency and trust are crucial in AI adoption.
- Education about AI should start from a young age.
- Brands can leverage AI to enhance customer connections.
- Spotify's DJ feature exemplifies effective AI use in consumer engagement.
- Understanding, connecting, and serving are key components for brands in the AI era.
Chapters
00:00 The Evolution of Digital Experience
04:01 Transitioning from Information Age to Experience Age
08:03 Addressing AI Concerns and Biases
14:11 Navigating AI: Understand, Connect, and Serve
In this conversation, Phillip Mortimer discusses the transformative impact of AI on private markets, emphasizing the unique challenges posed by non-standardized data and the importance of balancing quantitative and qualitative insights in investment decisions. He highlights the significance of data privacy in AI applications and the evolving role of generative AI in automating workflows. Mortimer also addresses concerns about the future of AI, arguing against the notion of reaching an inflection point in returns due to existing limitations.
Key Takeaways
- AI is essential for navigating the complexities of private markets.
- Data scarcity and non-standardization make AI a necessity in finance.
- Human intuition remains crucial in investment decision-making.
- AI can enhance productivity but should not replace human judgment.
- Generative AI poses new data privacy challenges that must be addressed.
- Last mile SaaS can still thrive despite the rise of generalized AI.
- The future of AI is promising, with ongoing advancements in technology.
- Type 2 thinking in AI is a key area for development.
- Investors must consider the return on intelligence, not just ROI.
- AI's role in finance is to augment human capabilities, not replace them.
Chapters
00:00 Introduction to AI in Private Markets
02:56 The Role of AI in Data Analysis
06:00 Balancing Quantitative and Qualitative Insights
08:50 Data Privacy Concerns in AI
11:54 Generative AI and Last Mile SaaS
14:59 Future of AI and Investment Returns
In this conversation, Michel Spruijt discusses the integration of AI and robotics in various industries, emphasizing the importance of balancing automation with human oversight. He highlights the challenges of designing multifunctional AI systems and the critical role of data interpretation in ensuring ethical use. Michel also shares insights on how organizations can adapt to AI, the significance of curiosity in career development, and the evolving job landscape due to technological advancements.
Key Takeaways
- AI and robotics are transforming industries, including cleaning.
- The balance between automation and human oversight is crucial.
- Data interpretation is more important than just data collection.
- Organizations should start small with AI investments.
- Curiosity is key to identifying unique opportunities in careers.
- AI will create new jobs while automating others.
- Human oversight is essential for ethical AI use.
- Staying curious can lead to career growth and innovation.
- AI should complement human work, not replace it.
- Understanding AI's capabilities can enhance productivity.
Chapters
00:00 Introduction to AI and Robotics in Industry
03:00 The Balance of Automation and Human Oversight
05:56 Challenges in Designing Multifunctional AI Systems
08:48 Data Interpretation and Ethical Considerations
12:07 Adapting Organizations to AI
16:58 Identifying Unique Opportunities in AI Roles
James Smith discusses his extensive background in business intelligence and analytics, emphasizing the critical importance of adopting generative AI in organizations. He highlights the risks of delaying adoption, the transformational potential of AI, and the need for alignment between AI and business strategies. James also addresses the importance of measuring the impact of AI, ensuring ethical use, and leveraging AI to anticipate future trends. He concludes by sharing insights on how businesses can effectively implement generative AI to gain a competitive edge.
Key takeaways
- Generative AI adoption is crucial for maintaining competitive advantage.
- Organizations that delay AI adoption risk losing market share.
- AI can transform the role of data teams in organizations.
- Effective communication is essential during AI implementation.
- Aligning AI strategy with business goals is critical for success.
- Measuring ROI is more important than just tracking user adoption.
- Keeping humans in the decision-making loop is vital for ethical AI use.
- Generative AI can empower all employees, not just a few.
- Organizations should test AI solutions against complex use cases.
Chapters
00:00 Introduction to James Smith and His Background
03:12 The Importance of Generative AI Adoption
06:05 Transformational Potential of Generative AI in Organizations
08:54 Measuring the Impact of Generative AI
11:54 Aligning AI Strategy with Business Goals
15:05 Addressing Bias and Ensuring Ethical AI Use
18:09 Leveraging Generative AI for Future Trends
23:51 Conclusion and How to Connect with James Smith
The rise of artificial intelligence (AI) is transforming industries, and customer success is no exception. Current trends show a rapid increase in AI adoption. This is driven by the potential to personalise interactions, automate routine tasks, and gain valuable insights from customer data among other solutions.
However, the transition requires careful consideration of how AI can blend with existing customer success practices. The goal is to ultimately develop a combination of AI capabilities and human empathy, leading to more satisfying and effective customer experiences.
This is where natural language processing (NLP) comes in. The power of NLP can be leveraged to understand customer queries and sentiment analysis to determine their emotional state.
In this episode, Kevin Petrie, VP of Research at BARC, speaks to Kate Neal, Senior Director of Customer Success at Gainsight, about the evolving role of AI in customer success.
Takeaways
- AI adoption in customer success is accelerating despite some hesitations.
- Gainsight provides a comprehensive customer operating system, “powered by AI”.
- Natural language processing can significantly enhance customer sentiment analysis.
- Human oversight is crucial in AI applications to ensure accuracy.
- Data quality is essential for effective AI implementation.
- AI can help reduce the administrative burden on customer success teams.
- Collaboration between data and AI teams is necessary for success.
- Understanding AI's capabilities is key for customer success leaders.
- AI is not a replacement for human jobs but a tool to enhance them.
Chapters
00:00 Introduction to AI in Customer Success
03:44 Gainsight's Role in Customer Success
07:11 AI Adoption Trends in Customer Service
10:51 Use Cases of AI in Customer Success
15:12 Natural Language Processing and Customer Sentiment
19:48 Human Oversight in AI Applications
22:06 Collaboration Between Data and AI Teams
23:59 Getting Started with AI in Customer Service
Azfar Aslam, VP & Chief Technology Officer, Europe at Nokia discusses the evolving landscape of telecommunications, focusing on the integration of AI and quantum computing. He highlights the challenges of implementing AI in network management, the importance of quantum safe cryptography, and the need for reliability in technology. The discussion also touches on the competitive nature of the industry and the ethical considerations of AI, particularly in ensuring fairness and avoiding biases in decision-making.
Key Takeaways
- AI is transforming telecommunications but comes with challenges.
- Focus on solving big problems rather than getting lost in technology.
- AI-powered maintenance can prevent outages and improve reliability.
- Quantum computing has the potential to revolutionize network security.
- Organizations must prepare for the transition to quantum-safe cryptography.
- Reliability and trust are critical in adopting new technologies.
- Competition in telecommunications is fierce, requiring constant innovation.
- AI systems must be designed to avoid biases and ensure fairness.
- Traceability in AI decision-making is essential for accountability.
- The balance between technology and economics will drive future innovations.
Chapters
00:00 Introduction to AI in Telecommunications
02:48 Challenges of AI Implementation
06:11 The Role of Quantum Computing
12:01 Quantum Safe Cryptography
15:10 The Future of Quantum in Telecommunications
17:58 Competition and Reliability in Tech
20:54 Ensuring Fairness in AI Systems
Hear Matt Yates explore the transformative role of AI in contact centers, discussing technologies like natural language processing and sentiment analysis. They delve into the balance between AI efficiency and the irreplaceable human touch in customer service, highlighting the importance of transparency, training, and continuous improvement in AI integration.
Key Takeaways
- AI is revolutionizing contact centers and customer interactions.
- Natural language processing is key to understanding customer sentiment.
- Human agents are essential for nuanced customer interactions.
- AI models are not 100% accurate and can introduce bias.
- Transparency in AI decision-making is crucial for customer trust.
- Organizations should balance AI efficiency with human emotional intelligence.
- Predictive analytics can enhance customer loyalty and service.
- Continuous training is necessary for both agents and AI systems.
- Implementing AI should be done gradually to avoid disruption.
- Data-driven decision-making is vital for successful AI integration.
Chapters
00:00 Introduction to AI in Contact Centers
06:02 The Role of Human Agents in AI-Driven Environments
11:49 Ensuring Transparency and Accountability in AI
17:53 Using Predictive Analytics for Customer Loyalty
Hear Wilson Chen discuss the complexities of AI in data analysis, particularly focusing on the challenges of bias, misinformation, and the importance of human expertise in interpreting AI-driven insights.
Wilson shares insights from his experience as the founder of Permutable AI , a startup that builds real-time LLM engines, and emphasizes the need for a balanced view in understanding geopolitical trends and market intelligence. The discussion also highlights the critical checks necessary to ensure the accuracy and reliability of AI-generated information.
Key Takeaways
- AI systems can amplify existing biases in data.
- A balanced view of information is crucial for accuracy.
- Human expertise is essential in interpreting AI outputs.
- Organizations must critically assess AI-driven insights.
- Real-time data analysis can enhance decision-making.
- Misinformation can spread if AI is not properly regulated.
- Ethical considerations are vital in AI usage.
- The integrity of sources impacts AI reliability.
- AI can simplify complex geopolitical dynamics.
- Permutable.ai aims to provide actionable insights for businesses.
Chapters
00:00 Introduction to AI and Data Analysis
05:01 Addressing Bias in AI Systems
09:55 The Role of Human Expertise in AI
14:53 Trusting AI-Driven Market Intelligence
20:01 Conclusion and Future Insights
AI is catalysing the evolution of low-code platforms and reshaping the landscape of low-code development tools. These new technologies can provide a strategic advantage in streamlining internal operations. By leveraging AI effectively organisations are able to deliver truly personalised, adaptive, and intuitive interactions.
However, organizations face challenges adopting these new technologies and risks like AI hallucinations need to be mitigated to ensure reliable outcomes.
In this episode, Paulina Rios-Maya, Head of Industry Relations at EM360Tech, speaks with Nikhil Nandagopal, Co-founder and CPO of Appsmith, about the transformative impact of AI on low-code platforms and application development.
Key takeaways
- Low-code platforms are revolutionizing application development.
- AI tools can generate code but require careful review.
- Routine tasks can be automated, but decision-making still needs human input.
- AI adoption comes with challenges like hallucinations and misinformation.
- Organizations must adapt their culture and processes for AI success.
- Developers need skills in data modeling and security for AI applications.
- AI can simplify user interfaces and enhance user experience.
- Interconnected applications will rely on AI to bridge data gaps.
- Most AI projects fail due to underestimating necessary changes.
- Enterprises face more challenges in AI adoption compared to SMBs.
Chapters
00:00 - Introduction to AI and Low-Code Platforms
02:59 - The Role of AI in Automating Tasks
05:51 - Challenges and Risks of AI Adoption
09:08 - Essential Skills for Developers in AI
12:01 - Future of Interconnected Applications
14:50 - Realities vs. Hype of AI in Enterprises
When it comes to the IT enterprise, the integration of AI is proving to be a transformative force. Modern IT departments face mounting challenges, from managing complex infrastructures and resolving system inefficiencies to ensuring robust cybersecurity and meeting escalating user demands.
AI offers a solution by automating routine tasks, streamlining processes, and enabling predictive analytics that anticipate issues before they arise. This not only enhances operational efficiency but also frees IT teams to focus on more strategic initiatives, driving innovation and value creation across the organisation.
However, adopting AI in enterprise IT systems comes with its own challenges, including ensuring data privacy, overcoming resistance to change, and maintaining the right balance between automation and human oversight. Effective AI integration requires a thoughtful approach—one that leverages AI’s capabilities while retaining human control to ensure accountability and ethical decision-making.
In this episode, Kevin Petrie, VP of Research at BARC, speaks to David Campbell, VP of Product at GoTo, about the challenges faced by modern IT departments, the role of practical AI in addressing these challenges, and the importance of balancing automation with human oversight.
Key Takeaways:
- AI can modernise IT systems without disrupting operations.
- AI helps identify inefficiencies and provides actionable insights.
- Human oversight is crucial in AI-driven IT processes.
- AI can automate tasks and flag critical issues proactively.
- Security is a top priority for IT departments.
- Data quality is essential for effective AI strategies.
- AI can streamline knowledge sharing across IT teams.
- AI can enhance help desk workflows and reduce resolution times.
Chapters:
00:00 - Introduction to AI in Enterprise IT
02:06 - Challenges in Modern IT Systems
04:33 - The Role of AI in IT Modernization
06:57 - Balancing AI Automation and Human Oversight
10:13 - AI's Impact on IT Security
12:34 - Ensuring Data Quality for AI
16:23 - Top AI Use Cases in IT Management
Today, organisations that thrive are those that foster a culture of curiosity. Encouraging curiosity empowers teams to question the status quo, explore innovative solutions, and stay ahead of emerging trends. By promoting an environment where employees feel encouraged to ask "what's next?" and seek learning opportunities, companies can adapt more swiftly to technological advancements and market shifts. This mindset drives innovation and cultivates resilience, enabling organisations to turn challenges into opportunities.
Preparing for future technological trends requires more than just adopting the latest tools—it demands a workforce that is curious and agile. A culture of curiosity fuels engagement, cross-disciplinary collaboration, and creative problem-solving, all of which are critical for navigating the complexities of technologies like AI, blockchain, and quantum computing.
By investing in curiosity through training, open communication, and a safe space for experimentation, organisations can build a future-ready workforce that embraces change and drives sustainable growth.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Andrew Grill, author of Digitally Curious: Your Guide to Navigating the Future of AI and All Things Tech, about the future of work and the integration of AI.
Key Takeaways:
- Digital curiosity empowers individuals to understand technology better.
- Leaders play a crucial role in fostering a culture of curiosity.
- Ethics in AI involves data privacy, transparency, and fairness.
- Curiosity leads to digital fluency, which is essential for the future.
- Organisations should encourage experimentation with new technologies.
- Understanding technology is vital for effective leadership.
- The future workforce will require continuous upskilling and adaptability.
Chapters:
00:00 - Introduction to Digital Curiosity
03:00 - The Importance of Digital Curiosity in Technology
05:50 - Overcoming Barriers to Technology Engagement
09:13 - Ethics and Responsibility in AI
12:05 - Cultivating a Culture of Curiosity in Organizations
14:58 - Future Technological Shifts and AI Integration
The world of IT Finance is shifting, driven by the transition from traditional capital expenditure (CapEx) models to operational expenditure (OpEx) in cloud-based environments. This evolution not only enables businesses to scale their resources dynamically while optimizing costs, but also introduces new complexities in forecasting, budgeting, and resource allocation.
As organizations adopt cloud technologies, the ability to manage financial resources with precision becomes a cornerstone of competitive advantage. Augmented FinOps, a groundbreaking approach that merges traditional financial operations with AI-driven insights, transforms how companies navigate these challenges, empowering decision-makers with unparalleled visibility and control.
The applicationof AI in FinOps promises to amplify its potential by automating routine tasks, uncovering patterns in vast data sets, and providing predictive analytics to enhance strategic planning.
In this episode, Jon Arnold, Principal of J Arnold Associates, speaks with Kyle Campos, CTPO at CloudBolt, about Augmented FinOps and the role of AI and ML in automating cost management processes.
Key Takeaways:
- FinOps is a community-driven approach to managing cloud spend.
- The shift from CapEx to OpEx has transformed financial operations.
- Augmented FinOps combines AI with traditional FinOps practices.
- Organizations must measure the “insight to action” gap in their processes.
- Machine learning can automate and optimize cloud spending decisions.
- C-suite expectations often misalign with operational realities.
- Tracking metrics is vital for improving FinOps maturity.
- Investing in FinOps is about optimizing resources, not just cutting costs.
Chapters:
00:00 - Introduction to FinOps and Cloud Management
02:52 - The Shift from CapEx to OpEx in Cloud Spending
06:13 - The Role of AI in Financial Operations
08:56 - Understanding Augmented FinOps
12:13 - Best Practices for FinOps in the Age of AI
15:00 - Leveraging Machine Learning for Cost Optimization
18:13 - Insight to Action: Measuring FinOps Effectiveness
21:04 - Conclusion and Key Takeaways
CloudBolt is The Cloud ROI Company™. It is singularly focused on solving the most pressing problem with cloud today: increasing return on investment (ROI). With the introduction of Augmented FinOps capabilities, CloudBolt is leveraging AI/ML-informed insights and applying intelligent automation and orchestration proactively and retrospectively to make complete cloud lifecycle optimization a reality. CloudBolt enables organizations to realize the full potential of any cloud fabric by closing the “insight to action” gap. By streamlining, clarifying, and optimizing spend and control, CloudBolt helps organizations place value at the center of every cloud decision. For more information, visit www.cloudbolt.io.
As artificial intelligence continues to shape industries and society, the need for robust AI governance has never been more critical. At the forefront of this governance are privacy-enhancing technologies (PETs), which play a key role in ensuring that AI systems operate in a way that respects and protects individuals' data.
The European Union’s AI Act, one of the most ambitious regulatory frameworks for AI, sets clear standards for transparency, accountability, and risk management. Understanding the implications of this legislation is crucial for businesses looking to innovate responsibly while avoiding potential legal and ethical pitfalls.
Countries around the world are taking varied approaches to AI governance, with some prioritising privacy and ethical considerations while others focus on fostering technological innovation. This diversity presents challenges and opportunities for organisations striving to implement AI responsibly.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Dr Ellison Anne Williams CEO and founder of Enveil, about the need for model-centric security and the potential of PETs to mitigate risks associated with sensitive data in AI applications.
Key Takeaways:
- Privacy-enhancing technologies are crucial for data protection.
- The EU AI Act sets a precedent for global AI regulation.
- Organisations must start with the problems they aim to solve.
- Data sensitivity must be considered in AI model training.
- Privacy-enhancing technologies can facilitate cross-border data sharing.
- AI is a neutral tool that requires responsible governance.
- The implementation of privacy technologies is still evolving.
- Global standards for AI governance are necessary for ethical use.
Chapters:
00:00 - Introduction to AI Governance and Privacy
01:07 - Understanding AI Governance
03:51 - Privacy Enhancing Technologies Explained
08:28 - The Role of the EU AI Act
12:42 - Implementing Privacy Enhancing Technologies
17:20 - Harmonizing AI Governance with Privacy Technologies
In this episode, Paulina Rios Maya, Head of Industry Relations at EM360, speaks with Caroline Hicks, Senior Event Director of the AI Summit Global Series, about the upcoming AI Summit New York, which will take place December 11-12, 2024.
They discuss the event's focus on AI's practical applications across various sectors, the importance of ethical considerations in AI, and the collaborative efforts among different industries to harness AI technology responsibly.
The conversation highlights key discussions and innovations that will be showcased at the summit, emphasizing the transformative impact of AI on businesses and society
Register now and enjoy a 15% discount on Delegate Passes with code EM36015OFF via https://newyork.theaisummit.com/em360tech-reg.
Key Takeaways:
- AI is showcasing its practical impact across diverse sectors.
- The AI Summit New York focuses on ethical and responsible AI.
- Collaboration is key in the AI community.
- AI is transforming industries like healthcare and retail.
- The summit will address AI's challenges and responsibilities.
- Innovative applications of AI will be highlighted at the event.
- AI can foster inclusivity and equal opportunities.
- Real-world implementation stories will be shared by companies.
As AI reshapes industries and drives global innovation, the UK must urgently address its AI skills gap to remain competitive. Nations investing in AI education and training are gaining a clear advantage, leaving others at risk of falling behind. By equipping the workforce with essential AI expertise, the UK can strengthen its position as a leader in innovation and secure its economic future.
Developing AI skills isn’t just about maintaining a competitive edge—it’s about creating opportunities. This dual approach ensures that experts can drive technological advancements while a broad understanding of AI empowers diverse sectors to integrate its potential. Investing in education, upskilling, and industry partnerships will ensure the UK workforce is ready to meet the demands of an AI-driven world.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to James Kuht, CEO and Founder of Inversity, about integrating AI into education and the collaborative effort required from government and society to achieve this goal.
Key Takeaways:
- The UK has a strong AI talent pipeline concentrated in key areas.
- Specialist and generalist AI skills are both important.
- AI can significantly boost productivity in knowledge-based tasks.
- Teachers need training to effectively integrate AI into education.
- AI skills will be a baseline requirement for future jobs.
- Government and society must collaborate on AI education initiatives.
- AI has the potential to reduce economic inequality.
- Most jobs will evolve rather than disappear due to AI.
Chapters:
00:00 - The Importance of AI Skills for the UK
03:01 - James Kuht’s Journey in AI
05:57 - Building a Competitive AI Workforce
08:45 - Integrating AI into Education
12:07 - The Role of Government and Society in AI Education
15:01 - Addressing Inequality in AI Access
17:58 - Future-Proofing the Workforce with AI Skills
21:10 - The Impact of AI on Global Industries
AI operates in two primary environments: on-device and cloud-based. On-device AI processes data locally, ensuring privacy and speed by eliminating the need for internet connectivity. Cloud-based AI, on the other hand, leverages powerful remote servers to handle complex computations and large-scale data analysis, enabling more robust capabilities but often at the cost of latency and potential privacy concerns.
Apple Intelligence exemplifies the strengths of on-device AI, with innovations like Siri, Face ID, and real-time photo enhancements all designed to prioritise user privacy while delivering seamless, responsive experiences. Unlike cloud-based AI, which may send sensitive data to external servers for processing, Apple’s approach ensures that personal information stays on the user’s device and is protected by advanced encryption. This difference builds trust and empowers users with faster, more reliable interactions.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Karel Callens, CEO at Luzmo, about best practices for developers integrating AI into their products.
Key Takeaways:
- Apple Intelligence operates on-device but can access cloud resources.
- Developers must implement robust security measures for user data.
- Clear data policies enhance user trust in AI solutions.
- Opt-in and opt-out options empower users regarding their data.
- Education on AI usage is crucial for consumer confidence.
- Shared security standards can mitigate AI misuse.
- Regulation is necessary to keep pace with AI advancements.
- Big tech companies have a responsibility to ensure ethical AI use.
Chapters:
00:00 - Introduction to AI: On-Device vs Cloud-Based
02:54 - Understanding Apple Intelligence and Its Benefits
05:47 - Security Measures in AI Integration
09:03 - Building Trust Through Transparency and Regulation
11:50 - Best Practices for Developers in AI Implementation
15:04 - The Role of Education in AI Trust and Security
17:47 - The Future of AI: Regulation and Responsibility
AI Personas are the cornerstone of how these systems interact with users, delivering tailored and engaging experiences. These personas—crafted from user research, behavioural insights, and cultural contexts—help define an AI's tone, style, and decision-making approach. Whether it’s a friendly virtual assistant or a professional customer service bot, personas ensure that AI systems resonate with their audiences while maintaining a consistent identity.
However, developing personas for AI isn’t without its challenges. Ensuring that AI responses remain appropriate, ethical, and unbiased while preserving a unique persona requires careful consideration. From avoiding stereotypes to addressing edge cases, the process demands robust testing and a clear understanding of how diverse user interactions can unfold.
When personas fail to account for the complexity of real-world scenarios, the risk of inappropriate or harmful responses increases. By combining creative storytelling with ethical AI design principles, organisations can navigate these challenges and build AI systems that are engaging and responsible in their behaviour.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Cobus Greyling, Chief Evangelist at Kore.ai, about the influence of cultural norms and value systems on AI and strategies for maintaining control over AI behaviour.
Key Takeaways:
- Personas in AI shape user interactions and trust.
- Cultural norms influence AI decision-making processes.
- Balancing control and agency is crucial for effective AI.
- Adversarial attacks can undermine AI reliability.
- Transparency is essential for user confidence in AI.
- Organisations should not offload too much responsibility to AI.
- AI should enhance human creativity, not replace it.
- Proof of value is necessary for AI technology implementation.
Chapters:
00:00 - Introduction to AI Personas and Their Impact
02:34 - The Role of Personas in AI Behavior
05:51 - Challenges in Ensuring Appropriate AI Responses
09:07 - Cultural Norms and Value Systems in AI
10:30 - Balancing Control and Agency in AI
14:14 - Strategies for Maintaining Control Over AI Behavior
21:24 - The Importance of Responsibility in AI Usage
Low-code and no-code platforms are revolutionising application development by empowering technical and non-technical users to quickly and efficiently build powerful applications. These platforms provide intuitive visual interfaces and pre-built templates that enable users to create complex workflows, automate processes, and deploy applications without writing extensive lines of code.
By simplifying development, low-code and no-code tools open up software creation to a wider range of contributors, from professional developers looking to accelerate delivery times to business users aiming to solve specific problems independently. This democratisation of development reduces the demand for IT resources and fosters a culture of innovation and agility within organisations.
The impact of low-code and no-code technology extends beyond just speed and accessibility; it’s transforming how businesses adapt to change and scale their digital solutions. These platforms allow companies to quickly respond to evolving customer needs, regulatory requirements, and competitive pressures without the lengthy timelines associated with traditional development cycles.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Michael West, Analyst at Lionfish Tech Advisors about LCNC platforms and their benefits.
Key Takeaways:
- Low-code and no-code platforms enable business solutions without coding.
- These platforms broaden the developer base to include non-technical users.
- Choosing the right platform involves considering functionality, standards, and vendor viability.
- Low-code platforms can handle enterprise-level applications effectively.
- AI integration is transforming how applications are developed.
- Democratisation of development addresses the shortage of professional developers.
- The market for low-code and no-code platforms is rapidly evolving.
- Future trends will focus on AI capabilities and user experience.
Chapters:
00:00 Introduction to Low-Code and No-Code Platforms
02:59 The Evolution of Development Roles
05:49 Key Considerations for Adopting LCNC Tools
09:04 Democratizing Development and Innovation
11:59 Future Trends in Low-Code and No-Code Markets
The intersection of cryptography and GPU programming has changed the face of secure data processing, making methods for encryption and decryption much faster and more efficient than ever imagined. Cryptography is the science of encrypting data with intricate algorithms initially designed to operate on very intensive computational powers. GPU programming provides the ability to utilise parallel processing of graphics processing units in cryptographic processes so they perform with unmatched speed.
While continuously evolving, GPUs are furnishing the computational muscle to execute ever-higher-level cryptographic algorithms without performance penalties. Developers now fully avail of the power of GPU parallelism to perform several thousand encryption tasks simultaneously, which is difficult for traditional CPUs to keep up with. This efficiency is critical in this growing data and rising cyber threat era, where organisations need rapid encryption and robust security.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Agnes Leroy, Senior Software Engineer at Zama, about the significance of encryption in high-stakes industries, the role of women in tech and the importance of mentorship in overcoming barriers in the industry.
Key Takeaways:
- GPUs have evolved from graphics rendering to critical roles in data security.
- Fully homomorphic encryption allows computations on encrypted data.
- Quantum-resistant methods are crucial for future-proofing encryption.
- High-stakes industries require robust encryption to protect sensitive data.
- Diverse environments in tech foster innovation and collaboration.
- The future of encryption technology is exciting and unpredictable.
Chapters:
00:00 - Introduction to Cryptography and GPU Programming
01:08 - The Evolution of GPUs in Data Security
03:33 - Challenges in Traditional vs Modern Encryption
05:50 - Quantum Resistance in Encryption Techniques
07:40 - The Future of GPUs in Data Privacy
08:38 - Importance of Encryption in High-Stakes Industries
10:00 - Potential Applications of Fully Homomorphic Encryption
11:42 - Women in Tech: Overcoming Barriers
15:33 - Conclusion and Resources
LLMs and AI have increasingly become major contributors to transforming content creation today. Understanding and using prompt skills appropriately can help organisations optimise AI to generate high-quality content efficiently.
While AI offers multiple benefits, it's important to acknowledge the potential risks associated with its implementation. Organisations are advised to carefully consider factors such as data privacy, bias, and the ethical implications of AI-generated content.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Prof. Yash Shreshta, Assistant Professor at the University of Laussane, about prompt engineering and its benefits.
Key Takeaways
- Prompts are commands given to AI to perform tasks.
- Prompt engineering allows users to communicate effectively with AI.
- Iterative processes improve the quality of AI outputs.
- Understanding LLM limitations is crucial for effective use.
- Collaboration can enhance the creative process with AI.
- The role of prompt engineering is rapidly evolving with AI advancements.
- Data privacy is a significant risk when using LLMs.
- Over-reliance on AI can lead to skill degradation.
- Organisations should integrate human creativity with AI.
- Regular training on prompt engineering is essential for maximising LLM benefits.
Chapters
00:00 Introduction to Prompt Engineering and AI
01:30 Understanding Prompt Engineering
04:15 The Importance of Prompt Engineering Skills
06:37 Best Practices for Effective Prompts
08:31 The Evolving Role of Prompt Engineering
11:20 Risks and Challenges of AI in Organizations
13:15 The Future of Creativity with AI
The fraud division has witnessed a dramatic transformation in the age of artificial intelligence (AI). As technology advances, so do the methods employed by fraudsters. Modern criminals use sophisticated techniques, such as deep learning and natural language processing, to deceive individuals and organisations alike. Such techniques allow them to mimic human behaviour, manipulate data, and exploit vulnerabilities in security systems.
That’s why organisations are embracing AI's strengths to combat these evolving threats. AI-driven solutions can provide real-time detection of fraudulent activities, analyse vast amounts of data to identify patterns and anomalies, and automate response processes.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Xavier Sheikrojan, Senior Risk Intelligence Manager at Signifyd, about AI fraud.
Key Takeaways:
- Fraudsters have evolved from individuals to organised criminal enterprises.
- AI enables fraudsters to scale their attacks rapidly and strategically.
- Phishing attacks have become more sophisticated with AI-generated content.
- Synthetic identities can be created easily, complicating fraud prevention.
- Opportunistic fraud is impulsive, while proactive fraud is well-planned.
- Businesses often fail to act post-breach due to resource constraints.
- Inaction after a breach can lead to repeated attacks by fraudsters.
- AI must be used to combat AI-driven fraud effectively.
- Balancing fraud detection with customer experience is crucial for businesses.
Chapters:
00:00 Introduction to AI and Fraud
01:32 The Evolution of Cybercrime
05:43 AI's Role in Modern Fraud Techniques
09:55 Opportunistic vs. Proactive Fraud
12:44 Business Inaction and Its Consequences
15:59 Combating AI-Driven Fraud with AI
As AI technologies become more integrated into business operations, they bring opportunities and challenges. AI’s ability to process vast amounts of data can enhance decision-making but also raise concerns about data privacy, security, and regulatory compliance.
Ensuring that AI-driven systems adhere to data protection laws, such as GDPR and CCPA, is critical to avoid breaches and penalties. Balancing innovation with strict compliance and robust data security measures is essential as organisations explore AI’s potential while protecting sensitive information.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Erin Nicholson, Global Head of Data Protection and AI Compliance at Thoughtworks, about the importance of compliance frameworks, best practices for transparency and accountability, and the need for collaboration among various teams to build trust in AI systems.
Key Takeaways:
- AI systems are powerful but require ethical and compliant design.
- Lack of standardisation in AI regulations poses significant challenges.
- AI models often need help with explainability and transparency.
- Compliance frameworks are essential for implementing AI in critical sectors.
- Documentation and audits are crucial for maintaining AI accountability.
- Baselining pre-AI processes helps build public trust in AI systems.
- Organisations should map regulations to the most stringent standards.
- Cross-functional collaboration is vital for effective AI compliance.
Chapters:
00:00 - Introduction to AI, Data Protection, and Compliance
02:08 - Challenges in AI Implementation and Compliance
05:56 - The Role of Compliance Frameworks in Critical Sectors
10:31 - Best Practices for Transparency and Accountability in AI
14:48 - Navigating Regional Regulations for AI Compliance
17:43 - Collaboration for Trustworthiness in AI Systems
As organisations increasingly migrate to cloud environments, they face a critical challenge: ensuring the security and privacy of their data.
Cloud technologies offer many benefits, including scalability, cost savings, and flexibility. However, they also introduce new risks, such as potential data breaches, unauthorised access, and compliance issues.
With sensitive data stored and processed off-premises, maintaining control and visibility over that data becomes more complex. As cyber threats continue to evolve, robust data protection strategies are essential to safeguarding information in the cloud.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Sergei Serdyuk, VP of Product Management at NAKIVO, about the factors driving cloud adoption, the importance of having a robust disaster recovery plan, best practices for data protection, and the challenges of ensuring compliance with regulations.
Key Takeaways:
- Cloud adoption is accelerated by low barriers to entry.
- Scalability in cloud environments is easier than on-premises.
- Data in the cloud is vulnerable and needs protection.
- The shared responsibility model places data protection on the user.
- A comprehensive disaster recovery plan is crucial for businesses.
- Regular testing of disaster recovery plans is essential.
- Data protection strategies must include regular reviews and updates.
- Compliance with data protection regulations is complex and varies by region.
- Balancing security and operational efficiency is a key challenge.
Chapters:
00:00 - Introduction to Cloud Technologies and Data Protection
01:26 - Factors Accelerating Cloud Adoption
03:48 - The Importance of Data Protection in the Cloud
06:39 - Developing a Comprehensive Disaster Recovery Plan
10:05 - Best Practices for Data Protection
13:31 - Ensuring Compliance in Cloud Environments
15:56 - The Role of Continuous Monitoring in Data Protection
18:19 - Balancing Security and Operational Efficiency
Managed Service Providers (MSPs) are evolving beyond traditional IT support, becoming strategic partners in driving business growth. By embracing AI technologies, MSPs are improving operational efficiency, streamlining service delivery, and offering smarter solutions to meet modern challenges.
As businesses navigate digital transformation, MSPs are crucial in optimising IT infrastructure, enhancing security, and providing tailored solutions that fuel innovation. With AI-powered tools, MSPs meet today's demands and help businesses stay competitive.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Jason Kemsley, Co-founder and CRO of Uptime, about the proactive strategies that MSPs can adopt using AI, the challenges they face in implementation, and the ethical considerations surrounding AI solutions.
Key Takeaways:
- MSPs are transitioning from traditional IT support to strategic partners.
- AI is enhancing operational efficiency but not replacing human roles.
- Proactive support is often neglected due to resource constraints.
- AI can help MSPs predict and prevent IT issues.
- Challenges in adopting AI include unrealistic expectations and lack of accountability.
- There is potential for MSPs to develop their own AI tools.
Chapters:
00:00 - Introduction to Managed Service Providers (MSPs)
02:03 - The Evolving Role of MSPs in Business Growth
04:00 - AI's Impact on Service Delivery Models
07:22 - Proactive Support Strategies with AI
10:16 - Challenges in Adopting AI for MSPs
12:40 - Ethics and Accountability in AI Solutions
Trusted AI ensures that people, data, and AI systems work together transparently to create real value. This requires a focus on performance, innovation, and cost-effectiveness, all while maintaining transparency. However, challenges such as misaligned business strategies and data readiness can undermine trust in AI systems.
To build trusted AI, it’s crucial to first trust the data. A robust data platform is essential for creating reliable and sustainable AI systems. Tools like Teradata’s ClearScape Analytics help address concerns about AI, including issues like generative AI hallucinations, by providing a solid foundation of trusted data and an open, connected architecture.
In this episode, Doug Laney, Analytics Strategy Innovation Fellow with West Monroe Partners, speaks to Vedat Akgun, VP of Data Science & AI and Steve Anderson, Senior Director of Data Science & AI at Teradata, about trusted AI.
Key Takeaways:
- Value creation, performance, innovation, and cost-effectiveness are crucial for achieving trusted AI.
- Trusting data is essential before building AI capabilities to avoid biases, inaccuracies, and ethical violations.
- A robust data platform is a foundation for creating trusted and sustainable AI systems.
- Generative AI raises concerns about hallucinations and fictitious data, highlighting the need for transparency and accountability.
- Teradata offers features and capabilities, such as ClearScape Analytics and an open and connected architecture, to address trust issues in AI.
Chapters:
00:00 - Introduction and Defining Trusted AI
01:33 - Value Creation and the Importance of Driving Business Value
03:27 - Transparency as a Principle of Trusted AI
09:00 - Trusting Data Before Building AI Capabilities
14:51 - The Role of a Robust Data Platform in Trusted AI
21:09 - Concerns about Trust in Generative AI
23:03 - Addressing Trust Issues with Teradata's Features and Capabilities
25:01 - Conclusion
Balancing transparency in AI systems with the need to protect sensitive data is crucial. Transparency helps build trust, ensures fairness, and meets regulatory requirements. However, it also poses challenges, such as the risk of exposing sensitive information, increasing security vulnerabilities, and navigating privacy concerns.
In this episode, Paulina Rios Maya, Head of Industry Relations, speaks to Juan Jose Lopez Murphy, Head of Data Science and Artificial Intelligence at Globant, to discuss the ethical implications of AI and the necessity of building trust with users.
Key Takeaways:
- Companies often prioritise speed over transparency, leading to ethical concerns.
- The balance between transparency and protecting competitive data is complex.
- AI misuse by malicious actors is a growing concern.
- Organisations must educate users on digital literacy to combat misinformation.
- Confidently wrong information is often more trusted than qualified uncertainty.
Chapters
00:00 - Introduction to AI Transparency
03:03 - Balancing Transparency and Data Protection
05:57 - Navigating AI Misuse and Security
09:05 - Building Trust Through Transparency
12:03 - Strategies for Effective AI Governance
As organisations adopt AI, data literacy has become more critical than ever. Understanding data—how it's collected, analysed, and used—is the foundation for leveraging AI effectively. Without strong data literacy, businesses risk making misguided decisions, misinterpreting AI outputs, and missing out on AI’s transformative benefits. By fostering a data-driven culture, teams can confidently navigate AI tools, interpret results, and drive smarter, more informed strategies.
Ready to boost your data literacy and embrace the future of AI?
Key Takeaways:
- Companies are optimistic about ROI from AI investments.
- Data literacy is crucial for effective AI implementation.
- Technical debt poses challenges for AI infrastructure.
- Data quality and governance are essential for AI success.
- Trust in AI systems is a growing concern.
- Organizations must start with clear business priorities.
- The Data Festival will provide practical insights for AI adoption.
DATA festival is where theory meets practice to create real, actionable knowledge. This event brings together #DATApeople eager to drive the realistic applications of AI in their fields.
Leaving the hype behind, we look at the actual progress made in applying (Gen)AI to real-world problems and delve into the foundations to understand what it takes to make AI work for you. We’ll discuss when, where and how AI is best applied, and explore how we can use data & AI to shape ourfuture.
Sign up now to secure your spot
Data labelling is a critical step in developing AI models, providing the foundation for accurate predictions and smart decision-making. Labelled data helps machine learning algorithms understand input data by assigning meaningful tags to raw data—such as images, text, or audio—ensuring that AI models can recognise patterns and make informed decisions.
AI models struggle to learn and perform tasks effectively without high-quality labelled data. Proper data labelling enhances model accuracy, reduces errors, and accelerates the time it takes to train AI systems. Whether you're working with natural language processing, image recognition, or predictive analytics, the success of your AI project hinges on the quality of your labelled data.
In this episode, Henry Chen, Co-founder and COO of Sapien, speaks to Paulina Rios Maya about the importance of data labelling in training AI models.
Key Takeaways:
- Data labelling converts raw data into structured data that machine learning models can recognise.
- Reducing bias and ensuring data quality are critical challenges in data labelling.
- Expert human feedback plays a crucial role in improving the accuracy of AI training data and refining AI models.
Chapters:
00:00 - Introduction and Background
01:07 - Data Labeling: Converting Raw Data into Useful Data
03:02 - Challenges in Data Labeling: Bias and Data Quality
07:46 - The Role of Expert Human Feedback
09:41 - Ethical Considerations and Compliance
11:09 - The Evolving Nature of AI Models and Continuous Improvement
14:50 - Strategies for Updating and Improving Training Data
17:12 - Conclusion
Traditional KYC processes are inadequate against modern fraud tactics. While KYC helps with initial identity checks, it doesn't cover evolving threats like AI-generated deepfakes or ongoing account takeovers.
Curious about how to protect your business from the latest threats like fake IDs, account takeovers, and AI-generated deep fakes? Tune in to our latest episode, where we dive into the essentials of full-cycle verification and real-time transaction monitoring. Find out how AI and machine learning can revolutionise your fraud detection efforts and why staying updated with regulatory changes is crucial for maintaining top-notch security.
In this episode of Tech Transformed, Alvaro Garcia, Transaction Monitoring Technical Manager at Sumsub, speaks to Paulina Rios Maya, Head of Industry, about the manifestations of identity fraud during the user journey stages and the need for comprehensive fraud prevention measures.
Key Takeaways:
- Identity fraud manifests at different user journey stages, including onboarding and transaction monitoring.
- Businesses must implement full-cycle verification and transaction monitoring solutions to detect and prevent fraud in real time.
- AI and machine learning are crucial in analyzing suspicious user behaviour and spotting complex fraud patterns.
- SumSub offers platform solutions that include KYC, business verification, transaction monitoring, and payment fraud protection.
Chapters: 00:00 - Introduction and Overview
00:35 - Identity Fraud in the User Journey
02:01 - Types of Fraud and Fraud Prevention
04:20 - Real-Time Monitoring and Enhancing Systems
05:46 - Common Types of Fraud Faced by Financial Institutions
08:40 - The Challenge of AI-Generated Deepfakes
10:04 - Beyond KYC: Additional Measures for Fraud Prevention
12:29 - Prevention Measures and Synthetic Identity Fraud
15:21 - Effective Fraud Prevention Solutions
17:45 - Assessing the Effectiveness of Fraud Prevention Strategies
19:08 - Staying Up to Date with Regulatory Requirements
21:31 - Conclusion
AI is revolutionising contact centres by automating routine tasks, reducing response times, and enhancing customer experience. AI is built to handle simple inquiries efficiently and at scale.
It helps contact centres close the gap between customer expectations and conventional customer service by enabling engagement through digital channels. AI-driven analytics improve decision-making by capturing and analysing data from customer interactions. Organisations can overcome challenges by starting small and gradually building trust in AI's capabilities.
In this episode, Paulina Rios Maya, Head of Industry Relations at EM360 speaks to Jon Arnold, Principal at J Arnold & Associates about the use of AI in contact centres.
Key Takeaways:
- AI is a transformative technology that rethinks customer engagement and addresses customer problems in contact centres.
- AI enables engagement through digital channels and helps contact centres close the gap between customer expectations and conventional customer service.
- AI-driven analytics improve decision-making by capturing and analysing data from customer interactions.
- Organisations can overcome challenges by starting small and gradually building trust in AI's capabilities.
- AI helps protect privacy and mitigate fraud in contact centres.
Chapters:
00:00 - Introduction and Overview
01:06 - The Transformational Power of AI in Contact Centers
03:00 - Automating Routine Tasks and Enhancing Customer Experience
06:24 - Engaging Customers through Digital Channels
11:09 - Improving Decision-Making with AI-Driven Analytics
15:28 - Overcoming Challenges and Building Trust in AI
17:23 - Protecting Privacy and Mitigating Fraud in Contact Centers
Join us in this exciting episode of Tech Transformed, where we talk to Kelly Vero, a pioneering game developer, digital leader, and visionary in the metaverse. With a career spanning 30 years and a resume that includes contributions to legendary franchises like Tomb Raider and Halo 3, Kelly brings a wealth of knowledge and experience to the table.
Kelly’s unique journey in the tech world is nothing short of extraordinary. From joining the military to learn about ballistics for Halo 3 to founding the award-winning startup NAK3D, she has always pushed the boundaries of what’s possible.
Kelly Vero speaks to Paulina Rios Maya about the hurdles of being a woman in the tech industry, the principles of gamification, and the overhyped trends in AI and NFTs. They discuss what’s genuinely beneficial versus what’s just noise.
Key Takeaways:
- The gaming industry offers opportunities for problem-solving and creativity.
- Role models can come from everyday people who inspire and support others.
- Gamification is about creating an engaging user experience that encourages return and contribution.
- The tech industry has seen beneficial changes in globalized platforms and a focus on quantum solutions.
Chapters:
00:00 - Introduction and Background
02:28 - The Gaming Industry and Problem Solving
07:36 - Challenges and Role Models in the Tech Industry
11:54 - The Principles and Ethical Considerations of Gamification
18:30 - Beneficial Changes and Overhype in the Tech Industry
20:25 - Creating Digital Objects and the NFT Standard
23:45 - Introducing NAK3D: Bringing Non-Designers into Design
Strategic choices with significant implications mark Latin America's approach to AI. Many countries in the region have adopted AI technologies and frameworks developed by leading tech nations, focusing on imitation rather than innovation. This strategy enables rapid deployment and utilisation of advanced AI solutions, bridging the technological gap and fostering economic growth.
However, reliance on external innovations raises questions about the region's long-term competitiveness and ability to contribute original advancements to the global AI landscape.
In this podcast, Alejandro Leal, Analyst at KuppingerCole, speaks to Paulina Rios Maya, Head of Industry Relations, about how socio-economic factors, including limited research funding, infrastructural challenges, and the need for quick technological catch-up drive this pattern of imitation. While this approach has led to swift AI adoption, it underscores a dependence on foreign technologies and expertise.
Key Takeaways:
- Trust, ethics, and legal considerations are essential challenges in integrating AI into the security infrastructure.
- Public-private partnerships and regional cooperation are crucial for advancing AI technology in the region.
- Interoperability and alignment with international and regional standards are key areas of focus to ensure the ethical use of AI in Latin America.
Chapters:
00:00 - Introduction: AI in Latin America
00:58 - Key Initiatives in the Security Sector in Mexico
05:12 - Mexico's Evolution in National Security
07:33 - Challenges in Integrating AI into Security Infrastructure
12:40 - Comparison with Other Latin American Countries
19:26 - The Role of Public-Private Partnerships
22:51 - Focus on Interoperability and Alignment with Standards
23:46 - Conclusion: Ethical Use of AI in Latin America
AI fraud is not just a concern, it's a pressing issue. As artificial intelligence technologies advance, fraudsters are developing increasingly sophisticated methods to exploit these systems. Typical forms of AI fraud include deepfakes, which use AI to create convincing fake images, audio, or videos for disinformation, blackmail, or identity theft, and advanced phishing schemes that leverage AI to craft highly personalized and deceptive messages. Addressing and understanding AI fraud is not just crucial, it's urgent for individuals, businesses, and governments to protect against these evolving threats.
Join Alejandro Leal and Pavel Goldman-Kaleidin, Head of AI and Machine Learning at Sumsub, as they delve into the growing issue of AI fraud.
Themes:
- AI fraud
- Deepfakes
- Global trends
- Regulation
Chapters:
00:00 - Introduction and Background
01:13 - Understanding AI Fraud
02:11 - Examples of AI-Driven Fraud
08:02 - Global Trends in AI-Driven Fraud
13:55 - Preventing AI-Driven Fraud
18:11 - The Future Evolution of AI Fraud
22:38 - Conclusion and Final Thoughts
While generative AI and large language models often receive inflated acclaim, their true value is found in harnessing intelligence and data-driven insights.
Despite the hype, AI has its shortcomings, such as large language models sometimes being solutions looking for problems and challenges in understanding its impact on advertising and making savvy investment decisions.
In this podcast, Dana Gardner, President & Principal Analyst of Interarbor Solutions, and Paulina Rios Maya, Head of Industry Relations at EM360Tech, discuss why AI should be seen as a transformational technology rather than just another automation tool.
Key Takeaways
- AI should be viewed as a transformational technology that can refactor our actions rather than just an automation tool.
- Large language models may be a solution in search of a problem, and their high costs and sustainability impacts should be considered.
- Making informed decisions about AI investments requires considering the potential benefits and costs.
Chapters
00:00 - The Current State of AI Development
02:17 - Viewing AI as a Transformational Technology
03:45 - The Limitations of Large Language Models
05:40 - The Impact of AI on Advertising
06:37 - Navigating the Complexities of AI Investments
Infosecurity Europe is a cornerstone event in the cybersecurity industry. It brings together a diverse array of cybersecurity services and professionals for three days of unparalleled learning, exploration, and networking. At its essence, the event is committed to delivering indispensable value to its attendees through meticulously crafted themes and discussions.
This year's focus revolves around resilience, artificial intelligence, legislation and compliance, leadership and culture, and emerging threats. With a comprehensive program featuring keynote speakers, strategic talks, insightful case studies, state-of-the-art technology showcases, dynamic startup exhibitions, and immersive security workshops, Infosecurity Europe offers a comprehensive immersion into the dynamic landscape of cybersecurity.
Pioneering new approaches, the event introduces QR-based tools for seamless content collection and unveils a digital meetings platform to foster enhanced connectivity and collaboration. By participating in Infosecurity Europe, cybersecurity professionals equip themselves with the tools, knowledge, and connections vital for continuous growth, networking, and industry advancements.
In this episode of the EM360 Podcast, Paulina Rios Maya, Head of Industry Relations at EM360Tech, speaks to Victoria Aitken, Conference Manager and Nicole Mills, Senior Exhibition Director, to discuss:
- Cybersecurity Trends
- Security events
- Infosecurity Europe
Register here to attend Infosecurity Europe | 4–6 June 2024
Chapters00:00 - Introduction and Overview of Infosecurity Europe
01:33 - Key Themes and Topics at Infosecurity Europe
14:04 - New Approaches and Tools
16:21 - Women in Cyber and Analyst Sessions
Ever wonder how search engines understand the difference between "apple," the fruit, and the tech company? It's all thanks to knowledge graphs! These robust and scalable databases map real-world entities and link them together based on their relationships.
Imagine a giant web of information where everything is connected and easy to find. Knowledge graphs are revolutionizing how computers understand and process information, making it richer and more relevant to our needs.
Ontotext is a leading provider of knowledge graph technology, offering a powerful platform to build, manage, and utilise knowledge graphs for your specific needs. Whether you're looking to enhance search capabilities, improve data analysis, or unlock new insights, Ontotext can help you leverage the power of connected information.
In this episode of the EM360 Podcast, George Firican, Founder of LightsOnData, speaks to Sumit Pal, Strategic Technology Director at Ontotext, to discuss:
- Knowledge Graphs
- Use Cases
- Ontotext GraphDB
- Integration of AI
- Industry best practices
Gone are the days of merely safeguarding school computers! Censornet, a rising star in the tech industry, has undergone a remarkable transformation. From its roots as an internet security provider for educators, it has emerged as a trailblazing force in digital risk management.
Today, Censornet offers a comprehensive suite of tools designed to confront the dynamic challenges of the digital landscape, ensuring a safer and more secure online environment for all. This evolution stems from recognising that traditional threats are no longer the sole concern. With the proliferation of Shadow IT, unauthorised applications and devices, and the rise of insider threats, organisations face a complex array of risks.
In this episode of the EM360 Podcast, Jonathan Care, Advisor at Lionfish Tech Advisors, speaks to Gareth Lockwood, VP of Product at Censornet, to discuss:
- Inspiration behind Censornet
- Censornet’s Capabilities
- Censornet’s Clients
- Shadow-IT
- Prevention of future vulnerabilities with AI and Censornet
The traditional data warehousing landscape is changing. The concept of private data cloud offers a compelling alternative to both cloud PaaS and traditional data warehousing. Imagine a secure, dedicated environment for your data, existing entirely within your organisation's control.
Yellowbrick, a leader in private data cloud solutions, empowers businesses to leverage their data on their terms. Their Bring Your Own Cloud (BYOC) approach offers unmatched flexibility and control. You can deploy Yellowbrick anywhere your data needs to be—public cloud, private cloud, or even the network edge. This ensures compliance with regulations and keeps your data exactly where you want it and can bring down costs.
In this episode of the EM360 Podcast, Wayne Eckerson, President of Eckerson Group, speaks to Mark Cusack, Chief Technology Officer of Yellowbrick, to discuss:
- The need for hybrid multi-cloud data platforms
- How Yellowbrick differentiates
- The future of private data cloud
- Why Yellowbrick?
Amid the ever-evolving landscape of cyber threats, organisations are constantly challenged to ensure security. Conventional security methods are failing to keep up with the escalating volume and sophistication of attacks. By implementing Managed Detection and Response (MDR) with automation, Security Operations Centers (SOCs) can optimise workflows, augment analyst capabilities, and significantly enhance the organisation's overall cybersecurity defences.
Palo Alto Networks offers comprehensive MDR services, leveraging its threat intelligence and cutting-edge technology expertise. Unit 42, its esteemed threat intelligence team, is crucial in providing valuable insights into emerging threats and trends, empowering organisations to stay ahead of malicious actors.
In this episode of the EM360 Podcast, Richard Stiennon, Chief Research Analyst at IT-Harvest, speaks to Ophir Karako, Software Engineer (Unit 42) at Palo Alto Networks, to discuss:
- Palo Alto’s MDR Services
- Operational Automation
- Data Enrichment
- Threat Response
- Job security for SOC Analysts
Interested in learning more about XSOAR and Palo Alto Networks? You can find some additional resources below:
- Enloe Medical Center Strengthens Its Security Posture and Improves Efficiency With Unit 42 MDR
- Unit 42 Managed Detection and Response Service Datasheet
- A Practical Guide to Deploying SecOps Automation
Chapters00:00 - Introduction and Background
00:57 - MDR Services at Palo Alto Networks
03:20 - Automation in Operations
04:16 - Automating Data Enrichment
05:13 - Intellectual Property Playbooks and Scripts
05:41 - Customized Reports for Customers
06:10 - Automated Threat Response
07:08 - Insights and Lessons Learned from Automation
07:37 - Benefits of Automation for SOC Analysts
08:06 - Collaboration with Product Experts
09:04 - Treating Automation as a CI/CD Process
10:01 - The Future of Automation in Cybersecurity
12:51 - Automation and Job Security for SOC Analysts
14:20 - Cortex XSOAR: Security Orchestration, Automation, and Response Platform
15:46 - Unit 42 MDR Service
16:16 - Conclusion
The data analysis landscape is on the precipice of a paradigm shift. Generative AI (GenAI) promises revolutionary insights, but traditional systems struggle to feed its insatiable appetite for well-structured data. Imagine GenAI as a high-powered engine – it needs meticulously organised fuel to reach its full potential.
In this episode of the EM360 Podcast, Analyst Christina Stathopoulos guides Deborah Leff (CRO at SQream) and Jason Hardy (CTO, AI at Hitachi Vantara) as they dissect:
- The Bottlenecks of Traditional Systems
- Unlocking GPU Potential
- Fueling Insights with Structured Data
- Faster Time to Insights
This episode goes beyond theory, exploring real-world examples (like a company querying a staggering 64 quadrillion rows) It showcases the potential for SQream and Hitachi Vantara to empower organisations to make data-driven decisions with unprecedented speed and accuracy.
The SolarWinds breach exposed vulnerabilities within DevSecOps practices, sending shockwaves through the tech world.
The U.S. Securities and Exchange Commission (SEC) indictment against SolarWinds further emphasised the gravity of the situation, alleging the company misled investors by failing to disclose these vulnerabilities and the subsequent breach adequately.
This lack of transparency raises crucial questions about accountability and risk management in the mobile app development landscape, pushing organisations to re-evaluate their DevSecOps practices and prioritise robust security measures throughout the entire development lifecycle.
In this episode of the EM360 Podcast, Head of Podcast Production Paulina Rios Maya speaks to Richard Stiennon, Chief Research Analyst at IT-Harvest, and Tom Tovar, CEO and Co-Creator of Appdome, to discuss:
- The SolarWinds indictment
- The U.S. SEC 4-day rule
- The impact on DevSecOps practices
- BYOD and VPN security
- The evolving role of cybersecurity
- Building cyber resilience
The fight against cybercrime is a never-ending battle. Firewalls and antivirus software, our traditional defences, are like trusty shields—good against basic attacks but not enough. Advanced attackers can slip through the cracks, exploiting new weaknesses or mimicking harmless traffic. Thus, businesses are exposed and face potential data breaches, financial ruin, and damaged reputations.
That's where Advanced Threat Intelligence (ATI) comes in – a game-changer in the cybersecurity arsenal. Unlike our old shields, ATI offers real-time intel on the latest threats, how attackers operate, and their ever-evolving tactics.
Recognising the limitations of traditional security solutions, Radware goes beyond basic shields. Imagine a high-powered watchtower constantly scanning the digital horizon, identifying threats before they strike.
In this episode of the EM360 Podcast, Analyst Jonathan Care speaks to Arik Atar, Senior Threat Intelligence Researcher at Radware, to discuss:
- The Current Threat Landscape
- Modern Attacker Tactics
- Romance Scams & Pig Butchering
- The Radware Advantage
Cloud-native is the new gold rush for businesses seeking speed, efficiency, and innovation. But are you getting the most out of your investment? Legacy troubleshooting and observability tools can be hidden anchors, dragging down your developers' productivity.
The result? You're not reaping the full benefits of cloud-native, and your competitors are leaving you in the dust.
Chronosphere, a leader in modern observability, can empower your developers and unlock the true potential of cloud-native. Buckle up and get ready to discover how observability can become your secret weapon for unleashing developer agility and innovation.
In this episode of the EM360 Podcast, VP of Research at Eckerson Group, Kevin Petrie speaks to Ian Smith, Field CTO at Chronosphere, to discuss:
- Observability
- Cloud-native software developers
- Developer inefficiency
- The Chronosphere solution
- Data pipeline best practices
SaaS applications are the backbone of digital enterprises around the world. But with so many SaaS businesses out there, simply having a feature-rich product is no longer enough to keep your users happy and grow your business.
In an increasingly crowded SaaS market, a smooth, intuitive user experience is what sets SaaS products apart. Businesses not only need to craft an exceptional user experience (UX) but also a User Interface (UI) design that makes your UX as seamless as possible.
But what does an effective UX and UI design even look like today? And how are emerging technologies like AI and machine learning transforming what users expect from a SaaS UX and UI design?
In this episode of the EM360 podcast, Matt Harris speaks to Jatin Leuva, CEO and UX Strategist at Tcules, to discuss:
- The current state of UX/UI design
- The challenges companies face in implementing solid UX/UI design
- The emerging trends and technologies impacting the UX/UI space.
The cloud revolutionised how businesses operate, but managing dynamic, complex environments presents new and unique challenges.
While digital transformation has brought significant benefits, the reality is that organisations now require innovative solutions to effectively navigate intricate, hybrid, multi-cloud environments.
Evolven Software, driven by a mission to simplify complexity and mitigate risk, empowers large organisations to overcome the challenges of governing extensive hybrid ecosystems. By harnessing the power of AI/ML, Evolven enables a more secure, streamlined, and efficient cloud journey with fewer outages or compliance gaps.
In this episode of the EM360 Podcast, industry veteran Tom Croll, advisor at Lionfish Tech Advisors, speaks to Sasha Gilenson, Founder and CEO of Evolven Software, to discuss:
- The current state of enterprise cloud architectures and the challenges in managing hybrid multi-cloud environments.
- Why managing risk in hybrid multi-cloud environments demands a new paradigm.
- The unique challenges large organizations face in maintaining visibility, control, and governance across their landscapes.
- How Evolven's AI/ML-driven solution empowers enterprises to overcome this complexity, enhance security, and optimize performance.
Intelligent document processing (IDP) is a technology-driven approach that automates document processing and extraction of valuable information.
While handling structured data is considerably straightforward, processing and analyzing unstructured data is laborious. IDP equips users with the ability to process a multitude of document types, including PDFs, spreadsheets, and Word documents, among others.
IDP platforms offer a powerful solution that streamlines data extraction from these documents by eliminating the need for any manual intervention. The extracted data, when integrated, enables you to make reliable decisions and improve business efficiency.
In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Jay Mishra, COO at Astera, to discuss:
- Traditional document processing and the problems it causes
- AI-powered solutions
- The future of document processing and data extraction
Find out more about Astera’s unified, no-code data management platform here.
From the rise of generative AI to the EU AI Act, it’s been a particularly explosive year in the AI and ML space.
With most industry surveys pointing to bringing in some form of AI as the biggest priority for companies looking to level up their tech stack in 2024 - what challenges and trends need to be addressed before creating and honing that MLOps strategy?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Yaron Haviv, Founder and CTO at Iguazio (recently acquired by McKinsey) as they discuss:
- The current AI landscape
- Implementing AI and ML - in the right way
- How scalable is MLOps?
Austin Kronz is the Director of Data Strategy at Atlan, a modern data workspace enabling better collaboration between diverse users like businesses, analysts and engineers - creating higher efficiency and agility in data projects.
The current world of data and AI is fast-moving - particularly when it comes to empowering companies and data leaders to ensure they’re set up correctly.
But what are some of the key trends that are really shaping what we’re seeing today? And how can you ensure that your data is ready for AI?
In this episode of the EM360 Podcast, Matt Harris speaks to Austin as they discuss:
- Data mesh and improving the way teams work
- Ensuring your data is ready for AI
- Words of wisdom for data leaders
Companies are evolving their approaches to managing content collaboration lifecycles, integrating security measures, and ensuring compliance with industry standards.
The importance of enterprise file storage especially highlights a shift toward adopting standards from public cloud ecosystems and modernising on-premises applications.
In this episode of the EM360 Podcast, Analyst Zeus Kerravala speaks to Jason Dover, CPO at FileCloud, as they discuss:
- The world of enterprise file storage
- Content collaboration and security
- Caring less about underlying infrastructure and more on surfacing content that meets end-user requests
Prof. Steven van Belleghem is an international speaker, EM360 partnered analyst and one of the world’s leading experts in customer experience.
He helps the likes of Disney, Booking.com and Microsoft to develop their CX strategies by incorporating the latest technologies. He is also a highly sought-after presenter and commentator, recently sharing a stage with Barack Obama.
In today’s episode of the EM360 Podcast, Head of Content Matt Harris speaks to Steven as they discuss:
- The customer experience landscape
- What the biggest companies in the world are looking at right now
- Building a customer-oriented company culture
Automated Security Validation. Involving tools, scripts and platforms to emulate true-to-life attacks, Automated Security Validation is a key part of assessing the readiness of the security infrastructure and guiding prioritized remediation.
But how does this implementation of automation really work to empower human expertise? How does all of this relate to compliance? And what words of wisdom can be given for those looking to level up their security strategy in 2024?
In this episode of the EM360 Podcast, Analyst Jonathan Care speaks to Thomas Pore, Director of Product Marketing at Pentera, as they discuss:
- The pen-testing landscape
- How important testing and validating are
- Empowering human expertise and remaining compliant
It seems like VPN products are consistently the initial access vectors for ransomware groups and targetted attacks.
This was demonstrated in the recent Ivanti Connect Secure zero-day vulnerabilities, as well as Cisco when they admitted last year that Akira Ransomware was specifically targeting their VPNs.
But what is the real problem with VPNs - and are they vulnerable by design? How do they fit into wider security architectures and strategies?
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Benny Lakunishok, Co-Founder and CEO of Zero Networks, to discuss:
- The problem with VPNs
- ‘Insecure by default’?
- ZTNA and remote access solutions
Kevin Lee is the Chief Digital Officer, Consumer at BT Group.
Responsible for the overall vision and strategy for all digital products and services across BT’s consumer brands, Kevin works across the UK’s biggest brands including BT, EE and Plusnet. In this role, Kevin oversees a team of product, digital strategy, design, research, and engineering creators to drive innovation and deliver great products to extend BT’s market leadership and surprise and delight millions of customers.
Kevin has a long track record of digital leadership, including roles at eBay, PayPal, Visa, Samsung, Whirlpool and GE Healthcare, in the UK, US, Italy, Korea and beyond. He’s passionate about tackling challenging business and customer problems, working with brilliant growth mindset teams, and driving impact for the customers whose lives are touched by the products and services he and his teams deliver.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Kevin about:
- The future of apps - and what separates the good and the bad
- Mastering customer experience
- Lessons learned from 15+ years of digital leadership
Generative AI is changing the world of customer service.
From deflection and reducing agent headcount using virtual agents/chatbots, or using automation to reduce handle time and after-call work, a lot of the conversation about generative AI in the customer service space has been centred around cost reduction.
But what are some of the more exciting, emerging use cases for AI in the space? And what key challenges can be solved?
In this episode of the EM360 Podcast, Analyst Zeus Kerravala speaks to Ping Wu, CEO at Cresta, to discuss:
- Improving experiences for the end customer
- How AI can transform your business
- Advice for large enterprises attempting to build these solutions in house
Data movement. The art and science behind moving data through the power of technology. An essential part of how modern businesses operate, the movement of data can encompass the replication, synchronisation and effective storage of company data.
But what data movement challenges and obstacles are hurting the way that companies utilise their data? How will the data movement space look over the next 5 years? And what key pieces of advice can be given to those looking to level up their data movement?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Harry Carr, Chairman and CEO at Vcinity, to discuss:
- How data movement impacts the business world
- Data movement challenges and obstacles
- Future trends in the movement space
Rapid breach response. The art of quickly reacting to a security breach or incident. Key for minimising the impact of attacks and ensuring your team is as effective as possible, rapid breach response is an important part of any security strategy.
With the rise and innovation we see in the automation space right now, how could automation be implemented into a security strategy to level up the efficacy of rapid breach response?
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Devin Johnstone, Security Operations Specialist at Palo Alto Networks, to discuss:
- Demystifying rapid breach response
- Implementing and leveraging automation in RBR
- Advice for SOC teams and shifting mindset
Rainfall. Temperature. Humidity. Natural disasters. Human methods of reading and predicting weather can be tracked all the way back to native tribes and ancient civilisations - and it’s still prevalent in the modern world today.
Whether (no pun intended) it’s an agricultural organisation looking to leverage precipitation data for planting schedules, energy companies looking at temperature trends to predict energy consumption patterns or transportation outfits looking to avoid delays, mastering weather data can really help modern companies to protect themselves against the unknown.
In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Christian Schluchter, CTO at Meteomatics, to discuss:
- Key use cases of weather data
- Mastering data access and predictive analytics
- The importance of being data driven
Maximize business value with data products — they incorporate essential data and related capabilities to meet key business objectives.
Data products contain datasets, related metadata and a wide range of functionality to understand if data is fit for use. But unlike relying on a raw dataset or data pipeline to generate value, data products deliver a comprehensive, packaged solution that enables data users to achieve their data-driven goals with easier accessibility.
In this EM360 Podcast episode, Head of Content Matt Harris sits down with Nathan Turajski, Senior Director of Product Marketing at Informatica. They explore how to:
- Drive better business outcomes with data products
- Understand the benefits of user-friendly and efficient consumption
- Improve AI, analytics and customer experience initiatives
The audit process is broken. CISOs and CTOs have faced a multitude of challenges under this outdated audit landscape, and the efficacy of companies are being stunted by a system that desperately needs updating.
But how can technology be leveraged to streamline or even transform that auditing process? And what does the future of infosecurity compliance look like?
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Leith Khanafseh, Managing Director of Assurance and Compliance Products at Thoropass as they discuss:
- The old audit landscape
- Challenges for CISOs and CTOs
- Multiframeworks and the future of compliance
Violeta Martin is Vice President, Commercial Sales EMEA at DocuSign.
She has over 15 years’ experience growing and leading high performing teams in a variety of fast growing startups and enterprise companies, including Oracle and SAP, thanks to a background in software engineering.
Docusign, the revolutionary CX-first tech company that allows companies to manage electronic agreements on different devices, recently partnered with WhatsApp to facilitate quick and secure contract signing through the world's most popular messaging platform.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Violeta as they discuss:
- Why businesses need to consider a mobile-first strategy to retain customers
- The value of multi-channel delivery for creating the best customer experience
- The evolution of the agreement process alongside consumer behaviour trends
In the world of complex supply chains, it’s not enough to secure our own data but also ensuring that third party vendors we work with have robust security.
When it comes to proactively stopping threats and mitigating issues, supply chain monitoring and ensuring a secure software supply chain is crucial to keep organizations’ data safe.
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Rahul Sasi, Co-Founder and CEO at CloudSEK, to discuss:
- Current state of cloud computing security
- Common vulnerabilities in the software supply chain
- Remote work, cloud reliance and mitigating risk
In 2024, the conventional approach of responding to threats is dead. As cyberspace becomes more complex, interconnected, and sophisticated, companies are beginning to recognise the shift from a reactive stance to a proactive one.
This shift isn’t just a technological upgrade - it’s a fundamental change in mindset that can cause ripples throughout the business.
In this episode of the EM360 Podcast, Analyst Jonathan Care speaks to Uri Dorot, Senior Product Marketing Manager at Radware as they discuss:
- AI-powered attacks
- Responsive protection vs proactive protection
- How proactivity works in practice
Dr Clare Walsh is Director of Education at the Institute of Analytics (IoA) and is one of the world’s leading academic voices in data analytics and AI, with her mission at the IoA being to help people in any field feel empowered by technology and understand its benefits.
Having studied under Professor Tim Berners-Lee and Dame Wendy Hall, she was also an academic tutor at the University of Southampton’s Data Science Academy and, during this time, worked for the Government as a researcher within the Office of AI.
Clare contributed to the recently published Government White Paper on AI Regulation, has published peer-reviewed research papers and is often called upon as an expert witness to advise governments in complex legal cases.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Clare about:
- AI regulation and legislation
- Being empowered by technology
- AI in the data analytics and business world
Thomas R Weaver is a tech entrepreneur and author of Artificial Wisdom, a new novel centred around whether AI might sacrifice certain human freedoms in the pursuit of saving humanity from itself.
Set in 2050, Artificial Wisdom’s vividly realised dystopia forces readers to grapple with hard-hitting questions about our relationship with AI, as well as the climate crisis and the price we’d be willing to pay for salvation.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Thomas to discuss:
- Inspiration for Artificial Wisdom
- AI predictions and worst-case scenario
- Recent AI regulation and legislation
AI has become widely used in enterprise communications in the wake of successful launches of multiple LLMs and strides in natural language processing.
From customer support chatbots to automated email responses, the applications leverage new advancements in AI to enhance efficiency and user experience.
But how close is AI to running all aspects of enterprise communications? How can you design a product well enough to replace the complexity of human interaction? Can AI every truly be trusted in the face of multiple ethical and legal considerations?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Micah Singer, CEO at Kurmi Software about:
- The current state of AI and communications
- How close AI is to taking over the comms space
- What AI holds in 2024 and beyond
What has been the impact of generative AI on CX and contact centers?
The recent hype cycle has redefined investment strategies, prompting companies to explore new AI use cases and uncover optimal starting points for implementation. Beyond technology adoption, organisations are strategically operationalising AI to drive transformative change in their operating models.
But how can companies get started, and where are they getting the best results? How do you even benchmark that success? And how can you use AI to improve the efficiency - and satisfaction - of your agents?
In this episode of the EM360 Podcast, Analyst Zeus Kerravala speaks to Devon Mychal, Head of Product Marketing at Cresta, as they discuss:
- How generative AI has impacted CX
- Where companies are getting the best results
- How AI empowers agents - and vice versa
Data access is a critical aspect of how businesses manage and leverage their data to drive decision-making.
With large volumes of data from various sources, it’s important that enterprises have a strategy in place to make the accessing process faster and more efficient while remaining compliant, secure and accurate.
In this episode of the EM360 Podcast, Christina Stathopoulos, Founder at Dare to Data speaks to Anthony Cosgrove MBE, Co-Founder at Harbr, to discuss:
- Data access challenges and pitfalls
- Facilitating business use cases with improved data access
- Advice for CDOs and data professionals
Christina Stathopoulos is a leading voice in the data community, participating regularly as an international public speaker and educator in the field.
Previously at Google and Waze, as well as Nielsen and SAS Institute, Christina is now the Founder of Dare to Data - a new start-up focused on helping businesses reach the next level in their data journey.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Christina about:
- Important takeaways from 2023
- The rise of AI and data democratisation
- Predictions for the next 12 months in data
Jon Arnold is the Principal of J Arnold & Associates, an independent analyst providing thought leadership and go-to-market counsel with a focus on the business-level impact of communications technologies on digital transformation.
A legendary voice in the communications community, Jon joins Head of Content Matt Harris on the EM360 Podcast today to give his predictions for the next 12 months and beyond.
They discuss:
- The dominance of Teams
- Generative AIs place in the communications ecosystem
- Is it time to look past UCaaS?
The data lakehouse has been quickly gaining popularity within the data management and analytics space.
Combining elements of data lakes and data warehouses, the data lakehouse aims to address the challenges associated with both in a way which helps companies reach their data and business goals.
In this episode of the EM360 Podcast, Christina Stathopoulos speaks to Read Maloney, CMO at Dremio, as they discuss:* The state of the data lakehouse * How an effective lakehouse strategy can be the key to digital transformation * How data lakehouses empower business
OT security, or Operational Technology security, focuses on safeguarding industrial control systems, supervisory control and data acquisition (SCADA) systems, and other technologies that manage and automate operational processes.
Unlike traditional IT security, which primarily deals with data and network protection, OT security is concerned with the safety and reliability of physical processes.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Daniel Bren, Co-Founder and CEO at Otorio, to discuss:
- OT security and how its importance is growing
- Why OT security is needed especially by critical infrastructures
- Empowering operational and security teams to manage digital risk
Telemetry data pipelines are designed to collect, process and transmit telemetry data from various sources towards a place where businesses can store, analyse and utilise it for better decision-making.
Important for SREs, DevOps, ITOps, SecOps, DataOps and the wider tech professional, taking control of your telemetry data to address data challenges in a compliant and secure way should be a common goal for the modern business.
In this episode of the EM360 Podcast, Analyst Kevin Petrie speaks to Tucker Callaway, CEO at Mezmo, to discuss:
- Understanding telemetry data pipelines
- Addressing data challenges with telemetry data
- Optimising performance and enhancing security with telemetry data
Using threat intelligence effectively in incident investigation is crucial for identifying, mitigating, and preventing cybersecurity threats.
By integrating relevant threat intelligence feeds, security teams gain insights into the tactics, techniques, and procedures employed by malicious actors. This aids in swift detection and response to potential incidents.
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Richa Priyanka, Solutions Architect at Palo Alto Networks, to discuss:
- Role of threat hunting in SOC
- Typical threat intelligence feeds for incident investigation
- The future of threat hunting
Workload portability, a critical facet of modern computing, empowers businesses to seamlessly transfer applications and data across diverse environments.
Whether migrating between on-premises servers, cloud platforms, or hybrid infrastructures, workload portability ensures flexibility and agility.
This adaptability mitigates vendor lock-in, allowing organizations to select the most suitable infrastructure for their evolving needs.
In today’s episode of the EM360 Podcast, Head of Content Matt Harris speaks to Sameer Zaveri, entrepreneur, global business leader and co-founder of Datamotive, to discuss:
- Workload portability
- Assessing across different cloud environments
- Business continuity planning in private and public cloud environments
Thomas Zoëga Ramsøy is the CEO and Founder of Neurons Inc.
A neuropsychologist by training and a Ph.D. in neurobiology and neuroimaging, Thomas is considered a leading figure in applied neuroscience. Through collaboration with leading universities such as Oxford, Cambridge, Stanford, and Harvard, his work has focused on employing a combination of psychology and neuroscience to understand what drives our choices and behaviours.
Thomas consults leading companies to employ the insights from neuroscience to drive strategic change, both in tech companies like Google and Facebook, retail companies like Lowe's, IKEA, and Tesco, and in domains such as architecture, leadership, and clinical trials.
In today’s episode of the EM360 Podcast, Head of Content Matt Harris speaks to Thomas to discuss:
- The current AI landscape
- Importance of dataset size and quality in AI tool training
- Using AI tools to optimise the customer experience
In an era dominated by the relentless surge of information, data has become the lifeblood of modern businesses and organisations. As the volume, variety, and velocity of data continue to escalate at an unprecedented pace, the role of data leaders has become increasingly pivotal.
These architects of the digital realm are entrusted with the formidable task of not only harnessing the power of data but also steering their organizations through the complex and ever-evolving data landscape.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Niamh O’Brien, Senior Manager of Solution Architecture at Fivetran to discuss:
- Challenges faced by data leaders today
- Becoming GenAI ready
- The big opportunity for CDOs and their teams
Having a 360-degree view of your business means having a comprehensive and holistic understanding of every aspect of your organisation.
It involves collecting and integrating data from various sources and departments to create a unified, real-time view. This panoramic perspective enables businesses to make informed decisions, identify opportunities, and address challenges across the entire enterprise.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Prash Chandramohan, Senior Director of Product Marketing at Informatica. They discuss:
- Having a 360-degree view of your business
- Driving great customer experiences
- Is your data ready for AI?
The Xen Project focuses on revolutionising virtualisation solutions by providing a versatile and powerful hypervisor that addresses the evolving needs of diverse industries.
From empowering innovation and enhancing cloud ecosystems to securing critical systems and revolutionising embedded technologies, what are the key needs of the space right now and how do projects like Xen help find those fixes?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Stefano Stabellini, Xen Project Advisory Board Member and AMD Fellow, to discuss:
- Innovation, scalability and safety in virtualisation solutions
- How the automotive industry has been affected by evolutions in enterprise technology
- The Xen Project and how it’s evolved throughout the years
Application security is a complex, wide-ranging field.
With attackers using a wide range of attacks from credential stuffing to cookie poisoning, how can you keep up with the ever-evolving landscape?
In this episode of the EM360 Podcast, Analyst Jonathan Care speaks to Uri Dorot, Senior Product Marketing Manager at Radware, to discuss:* Main challenges in protecting applications * Growing threat landscape * Consistent security across multi-cloud and hybrid environments
Doing more with less. The art of optimising your cybersecurity strategy and resources to achieve effective protection against cyber threats.
From assessing and prioritising assets to utilising open source tools, understaffed and overstretched cybersecurity teams are looking at ways to maximise what they’re able to do.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Chris Cochran, Advisory CISO and Chief Evangelist at Huntress, to discuss:
- Doing more with less - and why that’s necessary
- Equipping teams to be proactive
- Cybersecurity challenges specific to healthcare industry
Securing Software as a Service (SaaS) applications is crucial to protect sensitive data, ensure user privacy, and maintain the overall integrity of the service.
From data encryption and identity management to network security and a solid incident response plan, there are some crucial things to consider when employing SaaS as a part of your workflow.
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Guy Guzner, CEO and Co-Founder of Savvy Security, to discuss:
- Security challenges with SaaS
- Key worries from CISOs and CIOs
- The problem with existing solutions today
Enabling the business to leverage data while preventing breaches are top priorities for CxOs and boards across industries.
However, data security has long relied on legacy architectures and outdated approaches that were developed to protect data on-premises.
By harnessing artificial intelligence and machine learning to automatically learn and holistically protect a company's unique data, new AI-powered data security platforms are revolutionising data security for the cloud era.
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Roland Cloutier, the former Global Chief Security Officer of TikTok & ByteDance, to discuss:
- Social media and data privacy conversation
- Balancing leveraging data with preventing breaches
- Intelligently harnessing AI and ML for your data strategy
Web data extraction. The ability to transform any website into structured data.
Using a residential proxy network, companies have been able to fine-tune their data collection for a range of use cases - from threat intelligence and email protection to ad verification and market research.
But why do companies need this now? How do the different stacks of data extraction work and how can you make sure which one works best for you? And how is AI being used in this technology to reach industry-leading scalability and reliability?
In today’s episode of the EM360 Podcast, Head of Content Matt Harris speaks to Eitan Bremler, VP of Products at NetNut, to discuss:* Data extraction and why its a problem for companies * The different stacks of data extraction * How AI/ML should fit in to your data strategy
Darren Wood is the Head of Data Product Strategy at ITV. With a decade-long career in product development in FTSE 100 companies, Darren is a visionary leader in the space.
In this episode of the EM360 Podcast, Head of Content Matt Harris is joined by Darren as the pair dive into ITV’s data mesh journey whilst launching new streaming service ITVX.
Discover the invaluable insight and lessons Darren learned while working within the dynamic realm of data implementation, as well as:
- How data empowers ITV to compete with modern streaming disruptors like Netflix
- Data challenges unique to television/media
- Pioneering AI implementation
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Product data that is clean, consistent and enriched with accurate information and descriptions gets results.
When your customers can easily find the products they're looking for you can expect sales to increase, product returns to all but disappear, and brand loyalty to continue to grow. The problem is, how do you consistently deliver this level of quality in a world of disparate data sources, data silos, and the burden of existing technical debt?
AI is a powerful tool that can strategically help this industry unlock the true value of their data and meet the increasing demand for better data. By automating data cleaning, enhancing data quality, and generating actionable insights, organizations can deliver more meaningful experiences to their customers while eliminating the clutter of irrelevant data. This technology accelerates the industry's journey towards data-driven innovation and customer-centricity, ultimately giving trust to the end consumer.
In today’s episode of the EM360 Podcast, Analyst Susan Walsh speaks to Sam Russo, Practice Director of Automotive & Heavy Duty at Pivotree as they discuss:
- Why “perfect” product data is so important
- Issues in the automotive industry
- What AI/ML means for those modelling and enriching product data
No one knows how far gen AI can go in the enterprise but we know that it will be massive. Future platforms will certainly streamline and ensure efficiency, accuracy, and impact.
But there are many questions, including whether open source models perform as well as proprietary research? Will data compliance continue to be the main challenge the industry faces? What does the right to be forgotten mean in a world where gen AI exists?
In this episode of the EM360 Podcast, Analyst Richard Stiennon and Philippe Botteri, Partner at Accel, discuss:
- The world of data security
- Open source models vs proprietary research
- Data compliance today
Accel is a proud partner of Cyera, read more below about how they're addressing the most pressing problems in cloud security.
Abel Aboh is the Data Management Lead at the Bank of England.
Responsible for the design, development & delivery of one of the core Data Management Services (DMS) across the Bank, Abel enables the Banks ability to know, trust and use its data and analytics to achieve its mission of financial and monetary stability for the good of the people in the U.K.
In this episode of the EM360 Podcast, Head of Content Matt Harris is joined by Abel to discuss:
- The world of data management
- Data teams and the culture that powers them
- Current data challenges unique to banking sector
Zero Trust is a security concept and framework that assumes no trust, even among users and systems inside the corporate network.
Traditionally, network security models operated under the assumption that everything inside the corporate network could be trusted and that once someone gained access to the network, they could be trusted to access various resources.
This is no longer viable in 2023 and beyond - with the increase of sophisticated cyber attacks, denying by default has become the norm for companies looking to secure their sensitive data.
In this episode of the EM360 Podcast, Analyst Richard Stiennon is joined by Benny Lakunishok, Co-Founder and CEO of Zero Networks to discuss:* What it means to have a true zero trust strategy * Zero trust challenges * MFA and the future of network security
XDR isn’t just a fancy term or the latest trend; it represents consolidating security tools, enhancing defences against sophisticated attacks, and reducing response time to safeguard against data breaches.
Starting from a solid foundation of centralized logs, organizations can use XDR as part of their cybersecurity strategy to detect breaches across many different sources of data.
If we look specifically at the financial industry, XDR can be key in stopping attacks rapidly before they cause too much damage. Through reducing complexity and providing stack-wide visibility, SMBs within the banking sector can solve common challenges like understaffed teams and daunting compliance requirements.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Matthew Warner, CTO and Co-founder of Blumira, to discuss: * Security pain points in the BFSI space * The difference between EDR and XDR * Choosing the right XDR strategy for your business
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In today's data-driven world, where 90% of business decisions rely on data, harnessing the power of enriched data is paramount for organisational growth. This is where data enrichment for analytics comes in.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks with Andy Bell, VP of Global Data Product Management at Precisely. They discuss and discover how businesses are transforming their strategies by enriching their data with comprehensive demographic, industry, social, and consumer insights, enabling them to make profoundly informed and accurate decisions.
Explore how data enrichment revolutionises various sectors:
- Retail: Craft highly targeted marketing messages using precise customer profiling, identify lucrative markets, and pinpoint expansion opportunities.
- Insurance: Enhance policy pricing decisions with a deep understanding of a property’s proximity to diverse risk factors, ensuring more informed and competitive offerings.
- Telco: Optimize network planning and infrastructure rollout strategies by leveraging enriched demographics, property data, and detailed building footprints.
- Government: Pinpoint essential community services such as aged care, child care, education, and medical facilities, ensuring resources are allocated where they are needed most.
Tune in to the podcast and unlock the immense value of enriched data. Learn how this rich portfolio of data can fuel your analytics, empowering you to make decisions that drive unparalleled growth and success.
How is the UK’s National Health Service using the power of data to improve the client/patient experience?
Digital transformation has been a key part of the NHS’ plans to revolutionise and optimise the point of care - and a big part of that has been their new electronic document management system custom-built for the UK’s publicly funded healthcare organisation.
But how has the NHS’ digital transformation journey led them to where they are today? How far away from their paperless goals, and what are the benefits of that change? And how do these improvements to the tech stack ultimately result in better care for patients?
On this episode of the EM360 Podcast, Head of Content Matt Harris is joined by Mary Cahill, Head of Medical Records at London North West University Healthcare NHS Trust and Sarah Arrowsmith, Medical Records Manager at Kettering General Hospital, to discuss:
- The NHS’ digital transformation journey
- How they’re moving to a paperless future
- Data challenges specific to the healthcare industry
It’s officially the spooky season - but something scarier than ghosts, vampires and werewolves is striking fear into the hearts of cybersecurity leaders across the globe.
The unique challenges in the security space have been forcing industry leaders to switch up the ways they operate, specifically in the MSP space.
What does it mean to be a cybersecurity leader today? How have cyber attackers been changing their approach?
In this episode of the EM360 Podcast, Analyst Richard Stiennon is joined by Chris Cochran, Advisory CISO and Chief Evangelist at Huntress, to discuss:* Current state of cybersecurity leadership * Challenges faced by CISOs and IT Directors are facing * Cybersecurity horror stories
Natural disasters predicted. Accidents avoided. Lives saved. The importance of data for businesses has been well-documented - but how is it really improving the world around us?
Dan Everett is The Techno Optimist; with over 25 years of experience in data and analytics, he believes that taking a human-centred and technology-enabled approach to business and societal challenges will help make the planet a better place.
EM360’s Head of Content Matt Harris speaks to Dan on the EM360 Podcast today to discuss:
- Recent trends and the state of the enterprise
- Confidence in AI’s ability to solve issues
- How technology can reach its full potential
There is always a greater goal for networking.
In the 2020s, IT leaders want their network to “get out of the way” and support their business goals in improving real-estate and team productivity with latest generation of digital initiatives, ensuring privacy and security of their digital assets, and treating enterprise data as a key asset to drive intelligence in how they work.
In this episode of the EM360 Podcast, Analyst Zeus Kerravala speaks to Pankaj Patel, CEO of Nile, about what’s next for enterprise networks and more:
- Consuming networks as a service with guarantee performance and no capital expense
- Taking advantage of Zero Trust Networking principles to campus and branch locations
- Radically reducing operational expense for IT organizations with AI automation
Geoff Scott is a highly experienced technology leader with over two decades of experience in the enterprise technology space, specifically with SAP implementation and operations.
As the CEO of ASUG, one of the largest technology communities in the world, Geoff is responsible for bringing together a massive ecosystem of purchasers, users, implementers, partners, and consultants to get the most value from enterprise technology.
His passion for technology and its power to transform the world has made him a respected thought leader in the industry, inspiring innovation and success for organizations of all sizes.
In today’s episode of the EM360 Podcast, Geoff joins EM360’s Head of Content Matt Harris to discuss:
- Current trends - and which ones are positive
- Amplifying the voice of the SAP customer
- Enterprise technology and how it’s changing the world
Rapidly accelerating technology advances, the recognized value of data, and increasing data literacy are changing what it means to be "data driven."
The ability to leverage data for day-to-day activities improves decision making, and fosters better innovation, collaboration, and communication.
With deep insight into the data they have, and the confidence that their data is secure, Cyera is enabling enterprises to leverage data to create truly differentiated customer and employee experiences.
In today’s episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Yotam Segev, CEO and Co-Founder at Cyera, to discuss:
- Data security
- Why this is still a challenge
- Striking a balance between creating new steams
Network management is incredibly important for companies in the modern age.
Monitoring, securing and maintaining computer networks is integral to ensuring the smooth operation of your network infrastructure, especially as the reliance on networks to communicate and deliver grow year-on-year.
But how can you truly optimise your network? What’s holding your digital performance back? And what are some of the biggest challenges that IT managers and COOs are facing globally?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to John Diamond, Senior Solutions Architect at Park Place Technologies, to discuss:
- The evolution of network management
- Optimising your network and the benefits of an efficient stack
- Most common issues - and their solutions
Fivetran automates data movement out of, into and across cloud data platforms.
It automates the most time-consuming parts of the ELT process from extracts to schema drift handling to transformations, so data engineers can focus on higher-impact projects with total pipeline peace of mind.
With 99.9% uptime and self-healing pipelines, Fivetran enables hundreds of leading brands across the globe, including Autodesk, Condé Nast, JetBlue, Lufthansa, Morgan Stanley and Pitney Bowes, to accelerate data-driven decisions and drive business growth.
In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Fivetran’s Founder and COO Taylor Brown at Big Data LDN to discuss:* The data space and how Fivetran fits in * How customers are reacting to generative AI and ML * Trends set to shake up the industry in 2024 and beyond
The cloud plays a pivotal role in business data by enabling efficient storage, processing, and analysis.
It allows organisations to scale their data infrastructure and access powerful tools and services for data management.
Realising value from data relies on a well-articulated and communicated data strategy that leverages cloud capabilities to drive insights, innovation, and informed decision-making.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Sean Poulley, COO at Keepler Data Tech, to discuss:
- The role cloud plays in data for the business
- Realising value from data
- Well-articulated and communicated data strategy
Data storytelling. One of the hottest non-tech trends in the tech space, telling your data story has been critical for data management leaders to secure stakeholder involvement and executive commitment.
But why is data storytelling so important in today’s world? And how can people get started?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Scott Taylor, Data Whisperer, DataVenger and Principal Consultant at MetaMeta to discuss:
- Data storytelling and how to get started
- The data community
- Why data is the new bullsh*t
Network Asset Discovery is the process of identifying and cataloguing all devices, resources, and services present within a computer network.
This is an essential step in maintaining the security, performance, and management of a network - and overlooking the inventory of unknown devices on your network can result in serious problems.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Huxley Barbee, Security Evangelist at RunZero, about:
- Ramifications of a lack of network asset visibility
- Investigating network assets for incident response
- Current state of asset discovery
Data productization. The art of turning raw data into business-ready consumable data products.
Applying product management principles to data management, data productization can connect your business objectives to data and stay ahead of the curve.
But what things should you consider when building a data product? What challenges are likely to arise? And how can you effectively bridge the gap between data teams and business units to ensure the successful adoption and utilization of these products by end users?
In this episode of the EM360 Podcast, Analyst Kate Strachnyi speaks to Colin Brown, CMO at Revelate and Nicolas Doyen, CPO at Revelate, to discuss:
- Building a data product
- Ensuring successful adoption by end users
- Technologies shaping the future of data productization
Over £1,200,000,000 was stolen through fraud last year in the UK alone, with nearly 80% of that being conducted online*.
With cases like these rising, and fraud recovery on top of mind for BFSIs right now, how should the financial sector be leveraging technology to combat fraud and minimise risk?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Fatemeh Nikayin and Thomas Muller, Co-Founders of Rivero, to discuss:
- Increasing rates of financial fraud
- Common pain points for CEOs and COOs
- How BFSIs should be leveraging technology for fraud recovery
What is the relationship between product content and customer experience?
A symbiotic one, say experts, but what technologies need to be implemented and how can companies bring in new tools to eliminate their digital debt?
In this episode of the EM360 Podcast, Analyst George Firican speaks to Derek Corrick, GM of Data at Pivotree and Justin Anovick, Chief Product Officer at Syndigo, to discuss:
- The relationship between product content and CX
- Leveraging AI/ML and how that impacts clients
- Best practices for solid content strategy
What is the relationship between product content and customer experience?
A symbiotic one, say experts, but what technologies need to be implemented and how can companies bring in new tools to eliminate their digital debt?
In this episode of the EM360 Podcast, Analyst George Firican speaks to Derek Corrick, GM of Data at Pivotree and Justin Anovick, Chief Product Officer at Syndigo, to discuss:
- The relationship between product content and CX
- Leveraging AI/ML and how that impacts clients
- Best practices for solid content strategy
The data community is incredibly important.
From knowledge sharing and collaboration to staying updated with trends, the community of data professionals, influencers and C-level thought leaders serve as catalysts for innovation within the data realm.
But why is the data community so much more active and tight than others? What are some of the biggest voices in data talking about right now? And why do events like Big Data LDN provide indispensable opportunities to really understand the world of data?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Kate Strachnyi, EM360-partnered analyst and Founder of DATAcated, about:
- The importance of data communities
- Current data trends
- Big Data LDN
Automation streamlines repetitive tasks, reducing the time and effort required to complete them. This allows employees to dedicate their time and skills to more value-added activities, leading to faster realization of business objectives and an accelerated time-to-value.
By automating manual processes, enterprises can increase their operational efficiency. Automation for enterprises eliminates the risk of human errors and ensures consistency and accuracy in tasks, resulting in improved productivity and better quality outcomes.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Ron Gidron, CEO at xtype, to discuss:
- How automation benefits enterprises
- Accelerating time-to-value and improving agility
- Remaining competitive and agile in the face of evolving market dynamics
Monitoring cyber risk is essential in today's interconnected landscape.
Involving continuous assessment of vulnerabilities, threat detection, and response readiness, companies should be looking at the best way to protect themselves.
But is offence really the best defence? Does a proactive stance provide more of a formidable cybersecurity posture than a reactive stance? And how are the brightest minds in security mastering the art of minimising damage and downtime?
In today’s episode of the EM360 Podcast, Analyst Dr. Eric Cole is joined by Michael Quattrochi, SVP of Defensive Security at CyberMaxx, to discuss:
- Offence fueling defence
- Monitoring cyber risk
- Common exploitation trends
Big Data LDN (London) is the UK’s leading free-to-attend data, analytics & AI conference and exhibition, hosting leading data, analytics & AI experts, ready to arm you with the tools to deliver your most effective data-driven strategy.
From discussing your business requirements with over 180 leading technology vendors and consultants to hearing from 300 expert speakers in 15 technical and business-led conference theatres, there’s something for everyone at the event taking place in the UK capital this year.
In this episode of the EM360 Podcast, Head of Content Matt Harris joins Andy Steed, Editorial and Content Director for Big Data LDN and Mike Ferguson, Chief Executive of Intelligent Business Strategies at Big Data LDN, to discuss:
- Big Data LDN 2023
- New topics and talking points
- Why this year's event will be unmissable for end-users
Generative AI has had an unprecedented impact on the world of enterprise tech.
From applications within cybersecurity to handling data, the brightest minds are watching AI closely in a bid to make it work for them.
With this in mind, how can generative AI be used to boost data engineer productivity? Why are CIOs watching this new technology so closely? And is AI really going to take everyone’s jobs?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Graeme Thompson, CIO at Informatica, as they explore:
- How AI has impacted the data landscape
- Why generative AI is so important to CIOs
- Security, risk and compliance in the AI sphere
The aftermath of a cyber attack for a business can be devastating and may have significant short-term and long-term consequences.
The extent of the impact will depend on the nature and severity of the attack, the level of preparedness of the business, and how quickly they can respond and recover.
But how can you recover from these cyber attacks? How are critical infrastructures being targeted? And what further complications can arise when systems are downed for extended periods of time?
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Alex Yevtushenko, CEO at Salvador Technologies, to discuss:
- The aftermath of a cyber attack
- How critical infrastructures are being targeted
- Consequences of long downtimes
Privacy laws are legal regulations that aim to protect the privacy and personal information of individuals.
Designed to govern the collection, use, storage, and sharing of personal data by businesses, the primary objectives of privacy laws are to ensure that individuals have control over their personal information and to prevent its misuse.
But how have these laws developed over time. And between website friction to removal requests, what complication arise with privacy law compliance and how can these be more efficiently navigated?
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Meaghan McCluskey, Associate General Counsel at TrustArc, about:
- Where privacy laws came from, and how they got to where they are now
- Penalties for non-compliance
- Downsides of privacy law compliance
What might be stopping young people from pursuing a career within the tech industry?
A lack of awareness, suggests some experts - with current careers education perhaps not doing enough to allow more informed choices on entering the tech industry.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Adelle Desouza, Founder at HireHigher, to discuss:
- How young people are getting into the tech sector
- Lack of diversity in the tech industry
- Sustainable recruitment and retention strategies
Developing a company-wide privacy culture is crucial in today's data-driven world where personal information is constantly being collected and processed.
Such a culture ensures that employees, customers, and partners understand the significance of data privacy and actively work to protect sensitive information.
But how can you go about implementing one? What new corridors does setting privacy parameters open for a business? And is this relevant to companies of all sizes?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Noël Luke, Chief Assurance Officer at TrustArc, to discuss:* Benefits of a privacy culture * SMBs vs larger enterprises * How to benchmark your success
Unstructured data refers to any data that does not have a predefined or organized format. It does not fit neatly into traditional databases or tables, and its structure is typically not easily discernible.
The amount of unstructured data has been exploding globally, but why is this growing at the edge and in the cloud? How can you keep data secure? And what does optimising your management of data involve?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Jon Harding, UK Sales Manager at Qumulo about:
- Keeping data safe while making it easily accessible
- Unstructured data exploding globally
- Adopting and optimising hybrid data management
How is the world’s leading logistic company using AI across their business to improve the work lives of its 600,000+ employees?
Deutsche Post DHL Group endeavours to connect people and enable global trade. Focusing on growth in its profitable core logistics businesses and accelerating digital transformation across its divisions, how is DPDHL utilising AI to empower its workforce?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Meredith Wellard, VP of Talent Acquisition at Deutsche Post DHL, to discuss:
- How AI changes what a company is capable of
- Generative AI in workforce planning
- AI’s role in internal mobility and EX
Chief Data Officers, or CDOs, are responsible for all of the data-related activities of an organisation.
From ensuring data quality and integration to monetisation and ROI, CDOs always have their fingers on the pulse of emerging trends in the world of data.
But what are Chief Data Officers worrying about right now? What challenges are present specifically in the data space? And how are shifts in the market changing the role of the modern CDO forever.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Martin French, Chief Technology Data Officer at Apex Group, to discuss:
- The role of CDO and how it’s changing
- Emerging technologies defining the future of the data world
- Practical advice for CDOs
Corporate Performance Management (CPM) is a set of processes, methodologies, and tools used by organisations to measure and manage their performance and achieve their strategic objectives.
CPM encompasses various activities that help businesses plan, monitor, and analyze their performance against key performance indicators (KPIs) and targets.
But why is it so important? How does this technology interact with other business functions? And how can companies get started?
In this episode of the EM360 Podcast, Analyst Doug Laney speaks to Arthur Forbus, Managing Director and COO at HollandParker, to discuss:
- CPM and why every company needs it
- Misconceptions around CPM
- How to raise your CPM game
Data enrichment means combining your organisation’s internal data with data from third-party sources to make it more valuable, accurate, and insightful.
Through data enrichment, organisations can gain greater context about the world around their customers, markets, and operations – including geodemographics, property attributes, environmental risk factors, and much more.
Enriched data enables businesses to make better-informed business decisions, optimise operations, manage risks, personalise marketing campaigns, improve customer experiences, and identify new opportunities.
But what are the challenges that companies face when enriching their data? How can they better streamline that process? And how can you ensure you’re getting the most out of third-party data enrichment?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Andy Bell, VP of Global Data Product Management at Precisely, to explore:
- Data enrichment
- Tips on sourcing data
- Streamlining the data enrichment process
Everyone’s talking about AI right now.
It’s proven to be one of the biggest disruptors to the tech space post-Covid, but how has it affected geospatial data and location intelligence? How can ML and NLM’s be used to recreate and map our world digitally? And how should you go about implementing AI in your business?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Don Murray, Co-Founder and CEO of Safe Software, to discuss:
- AI and its impact on location intelligence
- Implementing AI across the business
- Advice for business leaders
A recent Gartner report stated that companies that implement CTEM (continuous threat exposure management) will be three times less likely to suffer from a breach.
With the objective of CTEM being the achievement of a consistent, actionable security posture, why should you bring that into your brand protection strategy? Should a proactive approach be prioritised over a reactive approach? And how can CISOs implement this while ensuring they’re compliant with incoming regulations such as DORA?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Jorge Montiel, Head of Pre-Sales EMEA at Red Sift, to discuss: * Continuous threat exposure management * How CISOs should approach compliance * Proactive approach vs reactive approach
Data modernisation is becoming increasingly important to CIOs and CTOs in today’s world.
From leveraging modern technologies to improving performance, scalability and functionality, database modernisation can be a key component to meeting the evolving needs of an organisation.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Suda Srinivasan, VP Strategy and Solutions at Yugabyte, to discuss:
- Database modernisation and why it’s so important to CIOs/CTOs
- Dangers of ties to legacy database technology
- Supporting businesses in a multi-cloud world
The rise of generative AI and its seemingly unlimited potential in the world of work has been well-documented in recent months.
But how can this new, hot technology be used to meet your company’s employee experience and customer experience goals?
In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Karthik SJ, VP of Product at Aisera about:
- How AI is shaking up the enterprise
- Entry costs of AI are at an all time low
- Using ML and NLM to deliver ROI
The rise of AI has been well-documented over the last year, but one ever-present concern that has risen alongside has been how generative models interact with data privacy issues.
Italy briefly banned ChatGPT earlier this year, citing no legal basis to justify "the mass collection and storage of personal data for the purpose of 'training' the algorithms underlying the operation of the platform". This was later reversed but sparked a global debate on how AI interacts with our information.
So, do we have anything to worry about? And how can businesses implementing AI into their practices ensure they remain compliant?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Gal Golan, CTO at MineOS, about:
- How the use of AI impacts data privacy concerns
- Using AI to enhance data privacy protection
- The future of compliance in the tech industry
Is the modern data stack dead? How can you better leverage your MDS? And how can you stay ahead of the curve in a market which is seeing more and more new trends emerging constantly?
These were questions posed at the recent Modern Data Stack Roadshow; Fivetran's follow-up to the successful Modern Data Stack Conference. These half-day events convene top industry experts to discuss how to drive impact and business growth using data.
With plenty of exciting talking points raised by the industry leaders in attendance, how are some of the biggest movers and shakers talking about the data space right now?
In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Mark Van De Wiel, Field CTO at Fivetran, to explore: * Keeping up with the modern data stack * Leveraging your modern data stack * Advice on tackling complex data challenges
Active Directory security is crucial for maintaining the confidentiality, integrity, and availability of an organisation's network resources and data.
It helps protect against unauthorised access, data breaches, insider threats, and other security risks, ensuring the smooth and secure operation of the IT infrastructure.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Simon Hodgkinson, Strategic Advisor at Semperis and ex-CISO of BP, about:
- Biggest threats to Active Directory
- Hybrid AD environments
- Top tips for CISOs
From ruthlessly targeting BFSIs to leaking the personal data of cancer patients, the horror stories that surround serious cybercrime are worse than ever before.
Getting one step ahead of cyber attacks and becoming proactive with your cybersecurity is essential to keeping your company secure, and one way to do that is adopting a deny-by-default philosophy.
But what is deny-by-default? What are CISOs worrying about most in this current landscape? And what lessons can be learned from assuming your enterprise has already been breached?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Rob Allen, VP of Operations EMEA at Threatlocker, about:* Zero Trust and a deny-by-default philosophy * Assuming that the attackers are already in * Dangers of data exfiltration
During his 16 years at the FBI fighting cybercrime targeting U.S. companies and entities, Jason Manar, now Chief Information Security Officer at Kaseya, investigated countless cyber incidents and saw first-hand how organisations can struggle in the aftermath of an attack.
He also witnessed how intruders, once discovered, could wreak further havoc if the breached organisation didn’t tread carefully.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Jason about:
- Lessons learnt from 16 years at the FBI fighting cybercrime
- How cybercriminals go unnoticed, and linger in environments
- Detecting persistent attacks
Earlier this year, Gartner predicted that companies that implement Continuous Threat Exposure Management, or CTEM, will have 3x fewer incidents year-on-year.
Visibility is critical when it comes to cybersecurity, and a programmatic approach to that visibility should include CTEM in some capacity, according to SecurityIntelligence.
But how does CTEM actually work? What problems does it solve? And how can it be seamlessly brought into to an enterprise to helps CISOs prioritise initiatives and measure progress?
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Rogier Fischer, Co-Founder and CEO at Hadrian, as they explore:* Continuous threat exposure management * Benchmarking an organisation's security posture * Solving the challenges that most CISOs face
In today's highly competitive digital landscape, software development has become the cornerstone of innovation and progress.
From creating cutting-edge applications to developing robust systems, developers play a vital role in shaping businesses and how they interact with customers, partners, and the market.
However, amidst the ever-increasing demands for software solutions, developers often find themselves grappling with productivity challenges that hinder their ability to deliver high-quality results efficiently.
In this episode of the EM360 Podcast, Analyst Richard Stiennon welcomes Jon Owings, Global Director of Cloud Native Architecture at Portworx, to discuss:* How developers can overcome operational efficiencies * Reducing development costs * Simplicity at scale
Generative AI has taken the enterprise tech world by storm, and its growing influence within the contact centre space is no different.
So how has AI begun to integrate with unified communications tools? And how can companies overcome challenges and barriers to ensure their successful use of AI in their communication stack?
In this episode of the EM360 Podcast, Analyst Jon Arnold speaks to Scott Kolman, CMO at Cresta, and we’re here to talk about:* How generative AI has changed the face of business forever * How AI has begun to integrate with contact centres and communication * Moving from on-prem to cloud and the AI gameplan
Data exfiltration has become a serious issue for companies in today’s world.
The unauthorised removal and theft of company data are becoming more commonplace as cybercriminals become more sophisticated in their attacks.
A good Data Loss Prevention, or DLP, strategy used to be enough to help protect the enterprise from malicious attacks, but has this changed? Is DLP dead?
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Darren Williams, CEO and Founder at Blackfog, as they discuss:
- The current state of cybersecurity
- How companies are struggling to protect their data
- Differences between anti data exfiltration and DLP
The UK’s new Online Safety Bill is a new set of laws to protect children and adults online, with a key part compelling social media companies to be more responsible for user safety on their platform.
While clear goals remain to prioritise the protection of user data and minimise illegal content like hate speech, the bill is illustrative of the political division in the UK.
Split between politicians who are eager to further limit Big Tech and politicians eager to cut back on corporate regulation in the post-Brexit era, these technology laws may prove to be pivotal to digital law in the West.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Suraj Mohandas, VP Education Strategy at Jamf, to discuss:
- UK Online Safety Bill
- Using technology to keep children safe
- How the UK compares to other countries
In today's fast-paced and highly competitive work environment, productivity is essential for success.
To tackle productivity in the modern workplace, it's important for companies to first identify the barriers that are switching off employees and halting specific business functions.
But how can simple things like flexible work schedules, regular breaks and professional development be rethought in a smarter way to revolutionise how your company runs?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Sanj Bhayro, Head of EMEA, to explore:
- Barriers to productivity
- How tech can destroy unnecessary meetings
- Tackling inefficiencies with these tried-and-tested methods
Moving from an on-prem infrastructure to a frictionless cloud model has become a key goal for many companies.
From scalability to improved security, as well as cost-saving benefits, moving to the cloud bring a lot of benefits. But what challenges are enterprises facing in their migration, and how can this process be made easier?
In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Alex Merced, Developer Advocate at Dremio, to discuss:* On-prem data lakes * Moving to a frictionless cloud * How to streamline the migration process
From protection of sensitive data to ensuring business continuity, being one step ahead of cybercriminals and threat actors is key to surviving as a business.
With the pandemic being just one of the factors that forced many companies onto the cloud and into remote working, cybersecurity is more important than ever before.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Jonathan Tomek, cybersecurity expert and former Marine, about:
- Incident handling and what companies are struggling with
- Lessons learnt from leading anti-cybercrime and espionage teams
- Top tip for business/customer security in 2023
Physical identity plays a crucial role in security. Through biometric authentication technology like facial recognition and iris reading to fingerprint reading, physical identity is used to verify who a person is.
The use of physical identity is becoming more and more prevalent in public places, particularly in healthcare where patient safety and security is paramount.
In this episode of the EM60 Podcast, Analyst Dr. Eric Cole speaks to Clete Bordeaux, Director of Healthcare Business Development at HID Global and Michael Ramstack, System Senior Director of Security from Essentia Health, about:
- Security challenges in the healthcare industry
- Physical identity priorities
- Why visitor management works best as part of a multi-pronged approach
SCA (Software Composition Analysis) tools are crucial for effective risk management in software development. These tools help to identify and mitigate security vulnerabilities that may exist in third-party and open source software components used in applications.
To master risk management with SCA tools, it is important to understand their capabilities and limitations.
By effectively utilising SCA tools, developers can reduce the risk of security breaches and ensure that their applications comply with open source licensing requirements. With continuous monitoring and improvement, SCA tools can help organisations stay ahead of potential security threats and maintain a strong security posture.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Kevin Wang, Founder and CEO of FOSSA, about:
- Risk management strategies
- Issues and frustrations with SCA tools
- Why organizations find it difficult to get a complete and up-to-date inventory of their software components
- Effectively managing these problems
Machine learning (ML) systems can provide several benefits to organisations.
From improved efficiency and productivity to enhanced decision-making, ML can help organizations gain a competitive advantage by enabling them to process and analyze data more effectively than their competitors.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Matt Thomson, Senior Director of EMEA Field Engineering at Databricks, to discuss:
- Benefits of ML system deployment
- Integration across the business
- Databricks Model Serving
Working in the age of generative AI presents both opportunities and challenges. On one hand, the ability to automate certain tasks and generate new ideas and solutions can greatly increase productivity and efficiency in the workplace.
On the other hand, there is the potential for job displacement and the need for workers to adapt and learn new skills to stay relevant in the workforce.
As AI continues to evolve, it will be important for companies and individuals to find a balance between leveraging its capabilities while also maintaining ethical and responsible use. This includes considerations such as data privacy, bias, and transparency in decision-making.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Mike Bollinger, VP of Strategic Initiatives at Cornerstone, about:
- The meteoric rise of generative ai
- Death of white-collar jobs?
- Solving problems by employing an AI-friendly culture
Small and medium-sized enterprises (SMEs) face numerous challenges when it comes to cybersecurity.
One of the most significant challenges is the lack of resources, including budget and personnel, to invest in robust cybersecurity measures. This often leaves SMEs vulnerable to cyber threats, such as phishing attacks, ransomware, and data breaches.
Additionally, SMEs may not have the expertise to effectively implement and manage cybersecurity solutions, leaving them susceptible to cyber-attacks.
This lack of attention to cybersecurity can lead to devastating consequences for SMEs, including financial losses, reputational damage, and legal liabilities.
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Matthew Warner, CTO and Co-founder at Blumira, to discuss:
- Common cybersecurity threats that SMEs face
- How these threats differ from those faced by larger companies
- Implementing effective cybersecurity measures
Cyberattacks have evolved beyond data theft and financial fraud to pose a real risk to human life.
From power grids to medical devices, many critical infrastructure systems are now connected to the internet, leaving them vulnerable to cyberattacks. Attackers could potentially shut down power grids, disrupt transportation systems, or manipulate medical equipment, causing widespread harm and even death.
As society becomes increasingly reliant on technology, it is crucial that cybersecurity measures are prioritised to mitigate the risks that cyberattacks pose to human life.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Simon Chassar, CRO at Claroty, to discuss:
- Cyber-physical systems and connections to company networks
- Fatal cyberattacks and ransomware deaths
- Securing your systems is a matter of life and death
Data management platforms (DMPs) have soared in popularity over the last decade, as understanding and gaining value from data has become a big priority for modern companies.
A DMP can collect, organise and store data from a mixture of sources and use that data to build everything from detailed customer profiles and ad campaigns to personalisation initiatives.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Ibrahim Surani, CEO at Astera, to discuss:
- How data management has evolved as a priority
- Common problems
- Unified data management platforms
Find out more about Astera’s unified, no-code data management platform here
Generative AI is the latest tech craze that has set the world on fire.
From creating marketing copy and engaging emails to designing logos and composing music, it has been adopted across the board by modern companies and its impact is expected only to grow as the technology develops and becomes more sophisticated.
Ultimately, tools like ChatGPT have the potential to completely transform how businesses operate and make society and the business world operate much more effectively, but what risks lie with this?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Andy Patel, Senior Researcher at WithSecure, to discuss:
- How the modern workday has been changed forever by AI
- CEO fraud and other prompt engineering risks
- Will humans always matter more than robots in the workforce?
Augmented Analytics and Data Storytelling are two innovative technologies that are shaping the future of Business Intelligence (BI).
Augmented Analytics uses machine learning and natural language processing to automate data preparation, analysis, and insights generation, reducing the reliance on data analysts and democratizing access to insights across the organisation.
On the other hand, Data Storytelling focuses on presenting data in a compelling and easily understandable way, turning complex data sets into impactful stories that drive decision-making.
Together, these technologies enable organizations to make data-driven decisions faster, improve business performance, and gain a competitive edge.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Clarence Rozario, Head of Business Intelligence Product Suite at Zoho Corp, to discuss:
- Bringing automation into BI
- Using BI to empower data storytelling
- The future of augmented analytics
Identity data is a valuable commodity in today's digital world.
With data breaches and identity theft on the rise, it's more important than ever to protect your personal information and the personal information of your employees.
But why is it so important to manage your company’s identity data? What challenges and threat can arise if you don’t? And how do you begin this cleaning process?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Wade Ellery, Field CTO at Radiant Logic, to discuss:
- Cleaning up identity data
- Security threats from unmanaged identity data
- Drawbacks of cuts and retrenching ahead of a recession
Data pipeline automation is revolutionizing the way organisations handle data.
This new approach to data management is challenging the traditional modern data stack, which relied on a series of disparate tools to handle different aspects of data processing. With data pipeline automation, organizations can simplify their data stack, relying on a single tool to manage the entire process.
This shift will allow businesses to focus on insights and decision-making, rather than spending time wrangling data. As a result, data pipeline automation will become the key component of the post-modern data stack.
In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Sean Knapp, Founder and CEO at Ascend.io, and we’re here to talk about:
- Solving data stack challenges
- Automation in data pipelines
- What the ultimate solution will be
GRC (governance, risk management, and compliance) and ESG (environmental, social, and governance) are critical for companies to balance in today's business landscape.
While GRC focuses on achieving objectives responsibly, mitigating risks, and meeting compliance requirements, ESG addresses a company's broader responsibilities to its stakeholders, including the environment, employees, and society as a whole.
Balancing both can be challenging, but it is essential for companies to operate sustainably and responsibly. Companies that prioritise ESG practices often have better long-term financial performance, while those that prioritise GRC can avoid costly legal and reputational risks.
Therefore, companies should look at integrating ESG and GRC to maximise efficiency and support the integrity of financial and non-financial reporting for sustainable growth.
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Grant Ostler and Mark Mellen, Industry Principals at Workiva, to discuss:
- How ESG has transformed in the last few years
- Integration of ESG into GRC to improve risk management
- Auditing ESG
Frictionless commerce is the ability to seamlessly find customers, establish trust, and transact and deliver products without any hiccups.
However, enterprises face three significant problems in achieving frictionless commerce: getting the right data, managing tech debt, and ensuring data interoperability. And much like the old children's book "I Know an Old Lady Who Swallowed a Fly" - each problem seems to lead to another.
That's where Data-as-a-Service (DaaS) comes in. A cloud-based service that provides users with on-demand access to high-quality data, it can help organisations with these challenges by providing them with accurate and reliable data while reducing the burden of managing and maintaining it.
In this episode of the EM360 Podcast, Analyst Doug Laney speaks to Derek Corrick, General Manager of Data Management at Pivotree, to discuss:
- Frictionless commerce and how it can be accelerated
- Common challenges in data management
- Data-as-a-Service and how to get started
Intelligent automation refers to the use of advanced technologies such as artificial intelligence, machine learning, and robotic process automation to automate business processes.
This enables organisations to increase operational efficiency, reduce costs, and improve customer experience.
By using intelligent automation, businesses can streamline repetitive and time-consuming tasks and free up human resources to focus on more value-added activities.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Tom Croll, Advisor at Lionfish Tech Advisors, about:
- Intelligent automation and tooling trends
- The role of human improvement and how it’s changing
- Preparing for implementation of intelligent automation
Supply chain attacks occur when hackers compromise a third-party vendor's software or hardware, which then infects the vendor's customers. Such attacks can be devastating, as they allow the attacker to gain access to the systems and data of many organisations.
To mitigate the risks of supply chain attacks, organisations should perform due diligence on their vendors, monitor their vendor's security practices, and implement strict access controls and network segmentation.
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Uri Dorot, Senior Product Marketing Manager at Radware, to discuss:
- Supply chain attacks from the client side
- Traditional WAF vs server protections vs client side protections
- Deployment experiences
Hyperautomation and AIOps are two of the most important technologies that are driving the digital transformation of businesses across the globe.
The business value of Hyperautomation and AIOps is significant. By automating repetitive tasks, hyperautomation helps businesses to save time and reduce costs, while also improving accuracy and efficiency.
AIOps, on the other hand, helps businesses to monitor their IT infrastructure in real-time, detect and resolve issues faster, and optimize IT operations, which ultimately leads to better business outcomes.
On this episode of the EM360 Podcast, Analyst Doug Laney is joined by John Appleby, CEO at Avantra, to discuss:
- AIOps as an enabler
- Tangible returns on investment
- Future of SAP landscapes
Shadow IT refers to the use of technology and IT systems within an organization without the approval or knowledge of the central IT department.
This can range from employees using their own personal devices for work purposes to departments setting up and using their own software and systems.
Shadow IT can increase security risks and lead to data breaches and violations of regulatory requirements. It can also cause operational problems and slow down decision-making.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Chris Buijs, Chief Evangelist at EfficientIP, about:
- The explosion of shadow IT
- Cybercriminals’ approach to exploiting shadow IT
- How companies can regain control
Data management is essential for retailers to manage their data effectively to gain valuable insights into customer behavior, preferences, and purchase patterns. By doing so, retailers can make data-driven decisions and improve their operations, sales, and marketing strategies.
However, managing data can be challenging for retailers due to the volume, variety, and velocity of data generated by multiple sources, such as social media, mobile devices, and online platforms.
Retailers must also comply with data privacy regulations and ensure the security of their customers' personal information. Additionally, they need to invest in advanced technology and skilled personnel to manage data effectively.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Ramesh Shurma, Founder and CEO at Orion Governance, to discuss:
- Major data challenges faced by retailers
- Protecting data assets in the face of recession
- Governance predictions for the next five years
Risk management is the process of identifying, assessing, and controlling threats to an organisation's capital and earnings. These risks can come in many forms, including market risk, credit risk, operational risk, and others.
Effective risk management helps companies minimize the potential impact of negative events, protect their reputation, and ensure the stability of their operations.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Phil Robinson, Founder of Prism Infosec and David Adams, GRC Security Consultant at Prism Infosec, about:
- How businesses should select their risk methodology
- Security teams and how to effectively communicate with them
- Where businesses go wrong
In traditional data architecture, data was always centralised in a data warehouse or a data lake and governed by a centralised team.
However, with the rise of distributed systems, microservices, and agile methodologies, this approach has proven to be inadequate for managing data at scale. Data Mesh proposes a different approach, where data is treated as a product and owned by the teams that produce it.
In other words, it's a way of thinking about data management that focuses on decentralisation and autonomy. But how can companies use this to their advantage?
In this episode of the EM360 Podcast, Analyst Christina Stathopoulos spoke to Paolo Platter, Co-Founder and CTO at Agile Lab, about:
- Successful data mesh strategies
- Benefits vs monolithic data lakes
- Customer success stories
Agile Lab works with an array of clients across the globe, creating business vertical solutionsto address specific challenges and needs in their field of activity. To hear about their success stories and the ways in which they exceed their clients' expectations, skip to 19:40.
Location intelligence. Location intelligence is crucial for a company's data-driven decision-making process, providing insights into the relationship between location and business operations. It helps identify new market opportunities, optimize operations, improve customer experiences, mitigate risks, and provide a competitive advantage.
By analyzing location-specific information, companies can make informed decisions that drive growth, reduce costs, and increase profitability. Ultimately, location intelligence is a valuable tool for companies seeking to make strategic decisions that optimize operations, enable growth, and gain a competitive edge in their respective industries.
In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Adam Ejsmont, Co-Founder of Echo Analytics, about:
- Location intelligence in the modern world
- Data collection and ensuring data privacy
- Why investing in location intelligence is critical
Incident response is the action taken to detect, triage, analyse, and remediate problems in software with the ultimate goal of minimising damage and restoring normal business functionality as quickly as possible.
A well-executed incident response plan can help organisations mitigate the impact of security incidents and maintain the trust of their customers and stakeholders, but how specifically can the efficacy of an incident response program be assessed?
In this episode of the EM360 Podcast, RedMonk analyst Kate Holterhoff spoke to Fred Hebert, Staff Site Reliability Engineer at Honeycomb, as they explore:
- Why some metrics are better than others
- Lessons we learn from fighting forest fires
- Incident response methodology
Business agility refers to the ability of a company to quickly adapt and respond to changes in the market and customer demands. In today's fast-paced business environment, companies need to be nimble and flexible to remain competitive and succeed.
Agile practices have become a key factor in achieving business agility, with organizations adopting methodologies such as Scrum, Kanban, and Lean. These practices focus on collaboration, continuous improvement, and delivering value to customers as quickly as possible.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Arie van Bennekum, Business Agility pioneer and co-author of the Agile Manifesto, about:
- How to become more agile
- Responding efficiently to market changes
- Key metrics in tracking level of agility
Companies are using the metaverse in the workplace in a variety of ways.
From using virtual reality environments to allow remote employees to work together as if they were in the same physical space, to using virtual events and trade shows to showcase their products and services to a global audience, the metaverse is a growing commodity for forward-thinking companies.
The metaverse is now proving to be a versatile tool for companies looking to enhance the workplace experience for employees, but what are its risks and drawbacks? Are some companies right to be reluctant?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Jos van der Westhuizen, CEO and Co-Founder of Remio, about:
- How companies are exploring VR programs
- Challenges of driving employee adoption of VR
- Enterprise Metaverse-as-a-Service and how it will evolve
Automating compliance controls refers to the use of technology to manage and monitor compliance with regulations and laws.
The purpose of automating compliance controls is to ensure that organizations meet their obligations in a consistent and efficient manner, while reducing the risk of non-compliance.
Automating these controls can provide significant benefits to organizations. It can help to reduce the risk of non-compliance, increase efficiency and consistency, and save time and resources.
However, it’s essential that automation should not be seen as a replacement for human oversight.
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Kayne McGladrey, Field CISO at Hyperproof to explore:
- Automating compliance controls vs SOAR automation
- Helping CISOs
- Can one master set of controls cover multiple frameworks
Managing third-party risk has become an increasingly important concern for enterprises as the use of third-party vendors and partners continues to grow in the business world.
In the wake of Uber’s second third-party breach from vendor Teqtivity in December, resulting in a data dump of almost 80,000 Uber employees’ personal information, serious questions needed to be asked about what companies should be doing differently.
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Paul Valente, CEO at VISO Trust, to explore:
- Facing security challenges with third-party vendors
- Positioning third-party risk to CXOs
- Assessing third-party risk and how to automate this process
Data is the backbone of any successful business, and having a 360-degree view of it is crucial to understand the key metrics and drivers of the organization.
By collecting, processing, and analyzing data from various sources such as customer interactions, financial transactions, and employee performance, your business can gain valuable insights into its operations.
This 360-degree view of the business data will allow your company to take a data-driven approach to decision-making, leading to better results and improved performance.
In this episode of the EM360 Podcast, Analyst Susan Walsh speaks to Dan Everett, VP of Product and Solution Marketing at Informatica about:
- Connecting different types of data
- Collecting, analysing and storing data while complying with regulations
- Business-wide observability challenges
Data ethics. The ever-changing landscape of how people perceive their personal data - and how companies use it - has been the subject of debate as data collection becomes more and more commonplace.
With US politics heading for data protection laws that could rival the severity of GDPR and consumers more aware than ever of how much their data is worth, what trends will we see arise in the next 12 months on an enterprise level?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Zaira Pirzada, Security and Risk Management Advisor at Lionfish Tech Advisors, and we’re here to talk about:
- The average person's approach to their data safety and security
- Modern events and how they’re shaping companies’ data decisions
- Data ethics in 2023 and beyond
Data observability refers to the ability to collect, measure, and analyse data from various sources in order to understand the current state and behaviour of a system.
This includes monitoring the system's performance, availability, and errors, as well as identifying patterns and anomalies in the data.
By implementing data observability, organisations can gain insights into their systems and make data-driven decisions to improve performance, optimize resources, and reduce costs. Common tools used for data observability include logging, metrics, tracing, and alerting.
In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Lior Gavish, Co-Founder and CTO at Monte Carlo, to discuss:
Getting started with data observability
Observability trends for 2023
How to implement and common challenges
Email security is vitally important for modern companies, with 95% using email as their main communication tool and 80% using email for sensitive data transfers.
But is this a mistake? Has email security fallen behind compared to other methods of communication? And what’s the alternative?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Adam Low, CTO at Zivver, as they explore:
- Progressive digital security
- Is email the worst way to transfer sensitive data?
- The role of security awareness training
Digital forensics have transformed crime prevention and the handling of cases permanently.
With over 5,000 British police officers able to work cases remotely and upload sensitive evidence directly to the cloud, forensic investigations that could have taken days or even weeks to resolve can now be dealt with instantaneously.
So how have strides in technology led to clearing case backlogs, securing faster convictions for violent criminals and bringing faster closure to victims and their families?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to West Midlands Police’s Detective John Price and Jon Cook, International Training Instructor at Exterro, about:
- Biggest challenges with digital forensics within the UK police force
- Moving digital forensics into the cloud
- The impact of FTK implementation
Cloud-native observability is a practice of rapidly detecting and remediating issues in complex and distributed systems.
Observability of cloud-native environments is important because it helps to ensure that these applications and infrastructure are running smoothly and effectively. To achieve this, enterprises typically use a combination of tools to ensure critical systems are highly reliable and performant
In this episode of the EM360 Podcast, EMA Analyst Torsten Volk joins Rachel Dines, Head of Product and Developer Marketing at Chronosphere to discuss:* Cloud-native observability in 2023 * Helping with employee burnout and retention * Cost issues with legacy tools and how Chronosphere can help
Cyber warfare has changed cybersecurity forever.
Rising tensions across the world have seen multiple state-sponsored attacks hit states like Ukraine, China and the US. With global superpowers spending millions on their cyberdefence strategies, are there any lessons that the enterprise can take away?
In this episode of the EM360 Podcast, Head of Content Matt Harris speaks to Jeremy Strozer, Advisor at Lionfish Tech Advisors about:
- Cybersecurity’s role in modern warfare
- Strategic cyber intelligence
- The biggest cybersecurity challenge of 2023
Predictive data intelligence is the use of data, AI-driven algorithms, and machine learning techniques to quickly connect data consumers with the most relevant data they need to drive their business initiatives and deliver greater value.
The goal of predictive analytics is to go beyond simply describing data to enable data consumers to accelerate the next-best actions to take for more effective decision making. For example, a retailer can understand their most relevant and high-quality data sets to better forecast consumer demand for a product, or a financial institution may identify the most accurate, complete customer data used to fuel analytics that help identify the likelihood of default on a loan.
In this episode of the EM360 Podcast, Analyst John Santaferraro speaks to Informatica’s Ian Stahl, Senior Director of Product Management and Chris Phillips, VP of Product Management to discuss:
- Shifting from business intelligence to predictive data intelligence
- Data sharing and data marketplaces
- The data consumption revolution
Containerisation is a method of packaging applications in a way that allows them to be easily deployed and run in different computing environments.
Containers allow applications to be easily moved between different environments, such as different servers, cloud platforms, or local development environments, without the need to worry about compatibility issues.
This makes it easier to develop, test, and deploy applications, as well as to scale and manage them in production.
In this episode of the EM360 Podcast, Analyst Richard Stiennon joins Sarvesh Jagannivas, VP of Marketing at Portworx to explore:
- Containerisation and why companies are moving towards it
- Backing up data from Kubernetes
- K8 clusters and data back up
Contract Lifecycle Management automates and streamlines everything related to a business' contract processes.
From authoring and sharing to signing and approving, contracts play a massive role in how businesses deal and correspond with the rest of the market.
In this episode of the EM360 Podcast, Editor Matt Harris speaks to Ronan Copeland, Group Vice President & General Manager EMEA at DocuSign, about:
- Digitising contracts and their management
- Post Covid digitalisation fatigue
- Contract lifecycle management
Low code and no code are popular alternatives to traditional software development that limit the amount of coding needed in a bid to make working on applications quicker, easier and more accessible.
Saving time, boosting efficiency and filling talent gaps are among the advantages of low code/no code, but what limitations could these practices provide? And what has contributed to the meteoric rise of this development philosophy?
In this episode of the EM360 Podcast, Editor Matt Harris speaks to Chai Rajebahadur, Executive VP and Head of Europe at Zensar, to discuss:
- The acceleration of low code, no code adoption and who is benefiting from it
- Advantages and disadvantages of low code
- What low code means for the talent market
The last few years have seen rapid changes in the cybersecurity landscape.
From work-from-home cybersecurity becoming a key part of companies’ strategies to ransomware becoming an ever-present risk, cybersecurity has presented consistent challenges to the enterprise.
But what does 2023 hold for the world of cybersecurity?
In this episode of the EM360 Podcast, Editor Matt Harris speaks to Brad Laporte, an EM360-Partnered Analyst and advisor at Lionfish, to discuss:
- What happened in 2022, and what's to come in 2023?
- Increases in state-sponsored cyber attacks
- AI/ML playing a bigger role in cybersecurity
The smart city. A modern, urban area where technology is intertwined with and relied on by the overall infrastructure.
Traffic flow, footfall, healthcare, education; almost all aspects of our everyday lives can be affected and improved by the way city systems can collect data and use it for good.
But what happens when the smart city becomes compromised?
In this episode of the EM360 Podcast, Editor Matt Harris speaks to Aare Reintam, COO at CybExer Technologies, to discuss:
- Insecure smart cities and how disruptions could be catastrophic
- How cybercriminals look to exploit specific vulnerabilities
- Does pre-emption really trump prevention?
Driving data adoption. From prioritising BI and data-driven decisions to utilising powerful analytics tools, data adoption is key for businesses as they stay current in today’s market.
According to a bi-survey.com report, the three biggest problems that enterprises face when tackling data adoption are a lack of analytical knowledge, a lack of technical knowledge and a lack of trust in data.
In this episode of the EM360 Podcast, Editor Matt Harris speaks to Cindi Howson, Chief Data Strategy Officer at Thoughtspot, to discuss:
- Starting your analytics journey
- Modern data stacks and how they’ve evolved
- How business analytics leadership can solve the major problems of our time
Mergers and acquisitions. A practice the tech industry itself is certainly no stranger to, M&A’s happen all the time and mark the consolidation of companies.
Companies can take on assets, share capital and equity interests; but they can inherit serious data risks too - and that’s a problem.
In this episode of the EM360 Podcast, Editor Matt Harris speaks to Erwan Keraudy, CEO of CybelAngel, to discuss:
- Cyber due diligence during a M&A
- The impact cyber risks have on recently merged companies
- Improving security posture post-deal
Enterprise communications consist of everything a company uses to connect its employees.
Video meetings, instant messaging, dedicated phone extensions. It sounds trivial to the average employee in the post-COVID workplace, but really this stack of tools and practices can seriously impact how firms can collaborate, share, and perform as a well-oiled unit.
In this episode of the EM360 Podcast, Analyst Jon Arnold speaks to Mark Sher, Senior VP of Product Marketing at Intermedia, to discuss:
- Cloud adoption in 2022
- Business value in UCaaS and CCaaS
- Uncertainty in investing and using new technology
Machine identity is an essential part of ensuring companies maintain a good level of data security and structural integrity.
The management of digital certificates and keys allows all internal traffic to be encrypted, seriously narrowing the attack surface of an enterprise.
In this episode of the EM360 Podcast, Editor Matt Harris speaks to Chris Hickman, Chief Security Officer at Keyfactor, to discuss:
- Where machine identity trends are heading
- Why companies are paying more attention to machine identity
- Identity as a single thread
Today's professional networking websites have devolved into the same reposting of social media nonsense.
The content has strayed too far from what is relevant to you, your field and your development as an IT professional.
And we're here to change that.
Introducing the new EM360 website, a place to publish, learn and earn while growing your place in the enterprise tech world.
In this very special episode of the EM360 Podcast, Editor Matt Harris joins EM360's Founder Michael Lodge and EM360's Head of Operations Ripon Deb to discuss:
- Designing a platform with a community-first mindset
- The biggest CX and UX turn offs and how EM360 solves this on a digital level
- The secret to success in B2B tech
Bot mitigation helps enterprises to identify and block unwanted bot traffic as it hits your network.
And with half of all internet traffic coming from bots (both good ones and bad ones), managing that bot traffic is critical.
Financial institutions, ticket-selling sites and shopping sites are among the hardest hit, with cybercriminals employing ML and AI in these bots to scale the size of their crimes and ambitions.
In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to Uri Dorot, Senior Product Marketing Manager at Radware, to discuss:
- The world of application protection
- Why companies are underequipped to deal with bot attacks
- Dedicated bot mitigation solutions
Enterprise service management, or ESM, is the concept of applying IT service management to other areas of the business, with the common goal to improve efficiency, performance and results.
With employee experience becoming increasingly important in the midst of the great resignation, could ESM be the key to protecting your company?
On this episode of the EM360 Podcast, Editor Matt Harris speaks to Martin Schirmer, President of Enterprise Service Management at IFS, about:
- Why EX is becoming a top priority
- The cost of bad EX and how to stop this
- Implementing ESM within organisations
Enterprise service management, or ESM, is the concept of applying IT service management to other areas of the business, with the common goal to improve efficiency, performance and results.
With employee experience becoming increasingly important in the midst of the great resignation, could ESM be the key to protecting your company?
On this episode of the EM360 Podcast, Editor Matt Harris speaks to Martin Schirmer, President of Enterprise Service Management at IFS, about:
- Why EX is becoming a top priority
- The cost of bad EX and how to stop this
- Implementing ESM within organisations
Data engineering is how companies design and build systems for collecting and using their data at scale. A critical practice as companies are pressured to make more and more data-driven decisions, data engineering is essential for enterprises to get ahead. In this episode of the EM360 Podcast, Editor https://em360tech.com/user/3673 (Matt Harris) speaks to https://www.linkedin.com/in/salma-bakouk-2999711b6?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAADJVC1UBRDqdneOVftZFsyUXKwa2JZVptAE&lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3Bzi1fFov0SOWW2R4dOI1ocw%3D%3D (Salma Bakouk), Co-Founder and CEO at https://em360tech.com/solution-providers/sifflet (Sifflet), to discuss; Trends shaping the data engineering industry Caring about data reliability and observability What the future brings
Data engineering is how companies design and build systems for collecting and using their data at scale. A critical practice as companies are pressured to make more and more data-driven decisions, data engineering is essential for enterprises to get ahead. In this episode of the EM360 Podcast, Editor https://em360tech.com/user/3673 (Matt Harris) speaks to https://www.linkedin.com/in/salma-bakouk-2999711b6?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAADJVC1UBRDqdneOVftZFsyUXKwa2JZVptAE&lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3Bzi1fFov0SOWW2R4dOI1ocw%3D%3D (Salma Bakouk), Co-Founder and CEO at https://em360tech.com/solution-providers/sifflet (Sifflet), to discuss; Trends shaping the data engineering industry Caring about data reliability and observability What the future brings
Who are Lionfish Tech Advisors? A team of premier IT Advisors, Lionfish comprises 25+ industry veterans who endeavour to advise some of the biggest firms on their tech stack and give them an essential competitive edge. Covering AI, Data, Cybersecurity and more, Lionfish boast hundreds of years of collective global advisor and analyst experience. In this episode of the EM360 Podcast, Editor Matt Harris meets Rob Smith, CEO of Lionfish Tech Advisors and Brad Laporte, industry veteran and advisor at Lionfish. Want to learn more? Head over to https://www.lionfishtechadvisors.com/ (lionfishtechadvisors.com) or visit the https://www.linkedin.com/company/lionfish-tech-advisors/ (Lionfish LinkedIn page).
Who are Lionfish Tech Advisors? A team of premier IT Advisors, Lionfish comprises 25+ industry veterans who endeavour to advise some of the biggest firms on their tech stack and give them an essential competitive edge. Covering AI, Data, Cybersecurity and more, Lionfish boast hundreds of years of collective global advisor and analyst experience. In this episode of the EM360 Podcast, Editor Matt Harris meets Rob Smith, CEO of Lionfish Tech Advisors and Brad Laporte, industry veteran and advisor at Lionfish. Want to learn more? Head over to https://www.lionfishtechadvisors.com/ (lionfishtechadvisors.com) or visit the https://www.linkedin.com/company/lionfish-tech-advisors/ (Lionfish LinkedIn page).
Data privacy. The ever-changing landscape of collecting and sharing personal data is complex, with attitudes and regulations constantly being updated. So what’s happening in politics right now that could affect ¾ of the world’s data privacy rights? How are consumers reacting to all this? And why are customers struggling so much with compliance? In this episode of the EM360 Podcast, Editor https://em360tech.com/user/3673 (Matt Harris) speaks to https://www.linkedin.com/in/neilkentjones?miniProfileUrn=urn%3Ali%3Afs_miniProfile%3AACoAAAF_qwQBn7MMrVCmHZygyh-W2l9qeLIDnmk&lipi=urn%3Ali%3Apage%3Ad_flagship3_search_srp_all%3BGNhzmhF0QJWdfxRAV9A5Uw%3D%3D (Neil Jones), Director of Cybersecurity Evangelism at https://em360tech.com/solution-providers/egnyte (Egnyte), to discuss: Data privacy in US vs. UK How current events affect companies How the landscape will look in 10 years' time
Fraud-as-a-Service, or FaaS, allows the offer of DDoS attacks, stolen data and social media passwords for sale, and all available with one single click. It can allow not only cybercriminals to monetise their illicit skills, but allows non-tech savvy criminals to carry out their own cyber crimes on a whim. In this episode of the EM360 Podcast, Editor Matt Harris speaks to https://www.linkedin.com/in/jamesbrodhurst/?originalSubdomain=es (James Brodhurst), Principal Consultant at Resistant AI, about: Fraud-as-a-service What security analysts need to look out for Examples of FaaS in action
Data management is essential for the enterprise to get right, especially now as firms across all sectors are collecting and using vast amounts of data. But what exactly is good data management? Why do we need it? And what are some of the unacknowledged ramifications that have serious impacts on our day-to-day lives? In this episode of the EM360 Podcast, Analyst https://em360tech.com/user/3642 (Doug Laney) speaks to https://www.linkedin.com/in/mkapushesky/ (Misha Kapushesky), CEO at https://em360tech.com/solution-providers/genestack (Genestack) and https://www.linkedin.com/in/vivek-iyer-686b301/ (Vivek Iyer), Team Lead from the https://www.linkedin.com/company/wellcome--institute/ (Wellcome Institute), to discuss: What makes good data management How data impacts everyday life Driving behavioural and cultural change
IT service management, or ITSM, manages the delivery of IT services to employees and customers. A common misconception is that ITSM is basic IT support - but it’s so much more than that. Because, when done correctly, it can free up your enterprise to focus on essential automation. In this episode of the EM360 Podcast, Analyst Dr Eric Cole speaks to Prem Maheswaran, Product Manager at ManageEngine, to discuss: ITSM Democratising IT in the pursuit of automation How chatbots create space for business functions
Confidential computing is a cloud technology that isolates sensitive data in a protected CPU enclave as it's processed. Accessible only to authorised programming code, confidential computing helps protect private data and intellectual property while not worrying about the cloud as part of your attack surface. In this episode of the EM360 Podcast, Editor Matt Harris speaks to Ivar Wiersma, Head of Conclave, about: Confidential computing and its benefits compared to other data privacy technology How enclaves and trusted execution environments work Why businesses need to care about this emerging technology
Hyperautomation is the business philosophy that the modern enterprise is using to rapidly automate SAP tasks and provide value back to the customer. A term coined by Gartner in 2019, hyperautomation and its rise are said to be indicative of how much RPA benefits businesses. In this episode of the EM360 Podcast, Editor https://em360tech.com/user/3673 (Matt Harris) welcomes https://www.linkedin.com/in/johnappleby/ (John Appleby), CEO at https://em360tech.com/solution-providers/avantra (Avantra), and https://www.linkedin.com/in/nick-miletich-9a7a37/ (Nick Miletich), CTO at https://managecore.com/sap-monitoring-automation-platform/ (ManageCore), to discuss: SAP Operation Automation and overcoming challenges The importance of using hyperautomation for SAP Customers How Avantra’s hyperautomation platform improves, agility, reliability, and security of SAP Where hyperautomation should be on your priorities and customized to your business requirements How Managecore leverages hyperautomation to provide best in class SAP support
Data culture is becoming an increasingly important philosophy in the modern enterprise. Making data-driven decisions is critical to the success of a company in today’s world, and there really is no better way to do that than ensuring a data culture runs through the firm. There are plenty of studies that show a correlation between the maturity of a data culture and the success of a business, https://www.collibra.com/us/en/resources/idc-data-intelligence-report (including this one from Collibra) which states “Organisations with higher levels of maturity across their data culture are likely to realise higher business benefits and performance versus peers.” In this episode of the EM360 Podcast, Editor https://em360tech.com/user/3673 (Matt Harris) spoke to https://em360tech.com/solution-providers/databricks (Databricks)’ Field CTO https://www.linkedin.com/in/robin-sutara/ (Robin Sutara) at Big Data London 2022 to discuss: Building and maintaining a data culture Data culture maturity The Women in Data movement
A software supply chain attack is when someone infiltrates your system by attacking a third-party provider or partner with access to your data. Recent high-profile supply chain attacks, most notably SolarWinds, has this type of attack into the public eye, and it’s clear that with more suppliers handling sensitive data than ever before, the attack surface of a typical enterprise has been changed dramatically. In this episode of the EM360 Podcast, Analyst https://em360tech.com/user/3627 (Richard Stiennon) speaks to https://www.linkedin.com/in/suresh-bhandarkar-36277895/ (Suresh Bhandarkar), Director of Product Solution Architecture at https://em360tech.com/solution-providers/beyond-identity (Beyond Identity), to discuss: Software supply chain attacks Weaknesses in the CI/CD pipeline The issue of software code provenance
Beyond Identity cuts through the anonymity of to provide a secure, scalable way for development and GitOps teams to immutably sign and verify the author of every commit. Their author verification API in proves that what you’ve shipped is what your developers actually built—and that nothing else got added.
As data continues becoming a core part of how businesses operate and make decisions, managing data quality has never been so important. Poor data quality can hit all enterprise levels hard, from marketers annoying prospects to supply chains becoming unable to automate processes properly. In this second episode of the three-part EM360 Podcast series with Anomalo on data quality, https://www.linkedin.com/in/eshmu/ (Elliot Shmukler), Co-Founder and CEO at https://em360tech.com/solution-providers/anomalo (Anomalo) joins Analyst https://em360tech.com/user/3633 (Christina Stathopoulos) to discuss: The right time for data quality monitoring What happens if you wait too long Who should be involved
Spatial data, also known as geospatial data, affects our everyday lives.A term used to describe data related to locations on Earth’s surface, spatial data can be used in everything from heat maps and political maps to smaller-scale indoor representations like in hospitals and offices. In this episode of the EM360 Podcast, Analyst https://em360tech.com/user/3644 (John Santaferraro) speaks to https://www.linkedin.com/in/spatialdna/ (Todd Lewis), Founder and CEO of Spatial DNA, to discuss: Digital revolution and the challenges it’s produced Helping customers overcome complexity The future of spatial data
Spatial DNA is a partner of https://em360tech.com/solution-providers/safe-software (Safe Software).
Data warehouses are centralised repositories of information that can be repeatedly analysed and utilised to make more informed decisions. These are empowered by business analysts and data scientists who use BI tools to act more intelligently at a business level. In this episode of the EM360 Podcast, Editor Matt Harris speaks to Umair Waheed, Head of Product Marketing at Yellowbrick, to discuss: Biggest trends in the data warehouse space All industries equally going towards the cloud Future of data warehouses Data warehouses are centralised repositories of information that can be repeatedly analysed and utilised to make more informed decisions.
As an IT Professional, you know that cyberattacks are ever-increasing, and businesses must do everything they can to ensure they remain protected. Organisations across the globe are beginning to implement Zero Trust solutions to protect their files, data, devices, and networks. Zero Trust is a concept that operates on the idea that nothing can be trusted, and everything is a threat until it has been properly verified. This process helps to mitigate and manage new and emerging cyber threats. In this episode of the EM360 Podcast, Editor https://em360tech.com/user/3673 (Matt Harris) welcomes https://www.linkedin.com/in/ben-jenkins-/ (Ben Jenkins), Director of Cybersecurity at https://em360tech.com/solution-providers/threatlocker (Threatlocker), to discuss: What is Zero trust, and why do businesses need it? How are cyberattacks evolving? Common cyber threats and how to better protect your business against them
Identity Governance and Administration (IGA) systems are a fundamental part of an enterprises identity and access management strategy. For companies that need functionalities like role-based access and automated approval, IGA systems can be essential in ensuring that the right people are getting access to the right things. Sounds easy enough, but issues with adoption, sponsorship and employee access speak to the fact that plenty of things can derail a deployment. In this episode of the EM360 Podcast, Analyst https://em360tech.com/user/3627 (Richard Stiennon) speaks to https://www.linkedin.com/in/rodlsimmons/ (Rod Simmons), VP of Product Strategy at https://em360tech.com/tech-index/omada (Omada), about: Automating already broken processes Disconnect between IGA goals and business goals Testing, testing, testing
Identity Governance and Administration (IGA) systems are a fundamental part of an enterprises identity and access management strategy. For companies that need functionalities like role-based access and automated approval, IGA systems can be essential in ensuring that the right people are getting access to the right things. Sounds easy enough, but issues with adoption, sponsorship and employee access speak to the fact that plenty of things can derail a deployment. In this episode of the EM360 Podcast, Analyst https://em360tech.com/user/3627 (Richard Stiennon) speaks to https://www.linkedin.com/in/rodlsimmons/ (Rod Simmons), VP of Product Strategy at https://em360tech.com/tech-index/omada (Omada), about: Automating already broken processes Disconnect between IGA goals and business goals Testing, testing, testing
Data quality monitoring is a process that manages and ensures a high-standard data within an organisation. Performed through strategies like automation and full-stack monitoring, companies set their own data quality metrics and KPIs to measure and evaluate it. In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Jeremy Stanley, CTO and Co-founder of Anomalo, to discuss: Data quality monitoring in a data reliant market Using unsupervised ML Changes in the last 5 years
Data quality monitoring is a process that manages and ensures a high-standard data within an organisation. Performed through strategies like automation and full-stack monitoring, companies set their own data quality metrics and KPIs to measure and evaluate it. In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Jeremy Stanley, CTO and Co-founder of Anomalo, to discuss: Data quality monitoring in a data reliant market Using unsupervised ML Changes in the last 5 years
Data governance in the modern world is the managing, utilising and securing of data in enterprise systems, and it’s becoming increasingly more important as organisations face new data privacy regulations as well as the need to make data-driven decisions. Well-designed data governance programs often include governance teams, steering committees and data stewards. But behind these lie data standards, policies and philosophies that can help businesses handle astounding amounts of data in the right way. In this episode of the EM360 Podcast, Analyst Christina Stathopoulos speaks to Ramesh Shurma, Founder and CEO at Orion Governance, to discuss: Current data governance space Bottom-up vs top-down approaches Lowering TCO and increasing ROI
Customer experience, or CX, is the impression your customer has from all aspects of their journey, and the way you collect, store and analyse their data can be a big part of this. A particular problem is inaccessible and disorganised data - so what’s the best way to organise and segment this with CX issues in mind? In this episode of the EM360 Podcast, Editor Matt Harris speaks to Daniel Bailey, VP EMEA of Amplitude, to discuss: Customer data platform vs data management platform Getting the most out of inaccessible and disorganised data Insights-driven CDPs and what they solve
It’s safe to say we’re witnessing a digital transformation revolution. Not just an integration of tech into all areas of a business, true transformation comes from cultural change and continuously challenging the limits of your brand. And as the world becomes more and more digital, there’s no longer a question of if you transform, but when and how drastically your transformation is. In this episode of the EM360 Podcast, Editor Matt Harris speaks to Alex Castro, Founder of ReM Score, to discuss: The one thing that companies need to change Accelerating value creation Owning tech vs buying data
Cloud-native can mean a lot of different things. Coined by Netflix as they became the world’s largest on-demand consumer content provider, cloud-native can increase the velocity of an enterprise to boost the efficiency of automation and scalability. On this episode of the EM360 Podcast, Editor Matt Harris speaks to Mohamed Ahmed, VP of Developer Platform at Weaveworks, about: Security as code Cloud-native application delivery Trusted delivery and why it matters
Raw data is data that has not yet been processed for practical use. It, of course, has the potential to become real and actionable information - but the transformation requires selective extraction, organisation and formatting. Businesses today are really beginning to recognise the value of raw data. With consumer data being one of the hottest commodities of the 21st century, the ability to make more informed decisions is driving the enterprise to make this unprocessed data work for them. In this episode of the EM360 Podcast, Analyst https://em360tech.com/user/3644 (John Santaferraro) speaks to https://www.linkedin.com/in/nickjewell/ (Nick Jewell), Senior Director of Product Marketing at https://em360tech.com/solution-providers/incorta (Incorta), about: Hidden gem of modern analytics Acting with intelligence to improve outcomes The world of raw data
Networking technology giant Cisco has this year expanded its partnership with McLaren Racing, providing collaboration infrastructure to enhance the F1 team’s speed, scale and power across their stack. McLaren Racing was founded by New Zealand racing driver Bruce McLaren in 1963, and with more than 180 F1 Grand Prix wins under their belt, they are one of the most iconic motorsport brands in the world. They now use Cisco’s solutions across their enterprise, upgrading their offices as well as their on-site race day deployments. EM360 visited the team’s headquarters in Surrey - the McLaren Technology Centre - to check out everything from VR headsets to real-time office space virtualisation. In this special episode of the EM360 Podcast, Editor Matt Harris spoke to Gary Blenkarn, Technology Solutions Architect at Cisco, about the future of work in the racing industry.
The evolution of business communication in the last 10 years, even the last 5 years, has been enormous. Trends toward group chat apps and video calling have empowered companies to think bigger about their physical footprints, enabling enterprises to seamlessly work internationally. Meanwhile, centralised internal comms have forced standalone solutions like PBX, conferencing and call centres to be integrated into a unified platform. On this episode of the EM360 Podcast, Analyst https://em360tech.com/user/2524 (Jon Arnold) speaks to https://www.linkedin.com/in/patrick2600hz/ (Patrick Sullivan), Co-Founder and Co-CEO of https://em360tech.com/solution-providers/2600-hz (2600Hz), to discuss:Building the communication foundation Combining comms elements company-wide Why offer UCaaS and CCaaS together
Data discovery is a subset of business intelligence (BI), referring to the collecting and consolidating of data from multiple databases into a single source. This makes it much easier to investigate and detect patterns, as well as apply real-time data controls to ensure safe storage and analysis. In this third episode of the three-part EM360 Podcast, Analyst https://em360tech.com/user/3633 (Christina Stathopoulos) is joined by https://em360tech.com/user/3633 (Richard Heyns), Founder and CEO of https://em360tech.com/solution-providers/brytlyt (Brytlyt), to discuss: Scaling analytics speed How to optimise the processing of geospatial data The next generation of BI
Least privilege is the philosophy which restricts access rights for users purely to the essentials. Providing employees with the minimal level of privilege needed to do their job has its downsides; but goes a long way to reduce the attack firms of tech firms across the world. In this episode of the EM360 Podcast, Editor Matt Harris speaks to Stephen Cobbe, CEO of Opal, to explore: Least privilege and its importance The shifting of business leader mindset Access management and how it’s evolved
Location Intelligence (LI) is how we use data to answer spacial questions. It goes beyond visualising data on a map - in fact, the analysis of location data has become integral to our daily lives. From 5G network deployments and geomarketing to Dominos Pizza understanding where you are and what you’re likely to order as soon as they pick up the phone, it’s clear that every sector is adopting LI to strengthen their processes. In this episode of the EM360 Podcast, Ciaran Kirk, Operations Director at IMGS joins Analyst John Santaferraro to discuss Location Intelligence aspects such as: Newest trends in data integration Streaming data challenges Modern data pipelines and what they give enterprises
Low-code development platforms have been around for over a decade, and provide an environment in which app software can be created through user interfaces and configuration. With these allowing for IT teams to build apps with modern interfaces, integrations and workflows at record time, it’s no wonder this corner of DevOps is taking the tech world by storm. In this episode of the EM360 Podcast, Editor Matt Harris speaks to James Bent, VP of Solutions Engineering at Virtuoso, to explore: Trends in the testing industry The SaaS DevOps challenge How QA leaders can work better with developers
When the pandemic forced employees to work out of their living rooms, companies had to be quick to adapt. Unified communications were needed more than ever, launching companies like Zoom from relative obscurity to a household name. One company that are a great example of this was Deliveroo, who used Slack to deliver a million meals to NHS frontline workers. In this episode of the EM360 Podcast, Editor Matt Harris talks to Craig Foster, Director of Global Enterprise Account Management at Deliveroo, about: How UC tools can be used as a digital HQ
feedingthefrontline
Empowering campaigns with enterprise tech
Authentication is the art of determining whether something is what it says it is. Passwords provide a great way for customers and consumers to access their personal information but when it comes to the enterprise, newer concepts like two-factor authentication (2FA) and zero trust network access (ZTNA) may be required. It’s been part of computing since its inception two decades ago - yet IT teams and businesses are still putting a lot of time into it. So why is authentication still such an issue?In this episode of the EM360 Podcast, Analyst Richard Stiennon speaks to https://www.linkedin.com/in/matthewlewis33/ (Matthew Lewis), Director of Product Marketing at https://em360tech.com/solution-providers/hid-global (HID Global), to explore: How the work from home movement impacted employee authentication “Passwordless” vs client-side certificates Adaptive authentication
Sustained transformation allows for enterprises to create new business processes, culture, and customer experiences to meet new market requirements. Transcending traditional departments like sales and marketing, transformation at its core begins and ends with an overall business strategy and how technology can empower that. On this episode of the EM360 Podcast, Analyst https://em360tech.com/user/3633 (Christina Stathopoulos) joins https://www.linkedin.com/in/jaygoldman/ (Jay Goldman), Co-Founder and CEO of https://em360tech.com/solution-providers/sensei-labs (Sensei Labs), to explore: Why ‘constant transformation’ is necessary for survival Traditional tech-enablement vs enterprise orchestration Assessing delivery capabilities
The traditional face-to-face identity check has exhausted its welcome. Instantaneously proving our identities when online banking and booking flights has made things such as physically opening a bank account or applying for a mortgage seem incredibly inefficient - and only limits access to those who are busy during working hours or unable to travel. In this episode of the EM360 Podcast, Editor Matt Harris speaks to Russell King, CEO at Xydus, about: Driving factors behind the growth of digital identity verification Challenges when verifying workers and customers The ethics, bias and risks of facial recognition
Observability allows businesses to measure the internal state of a system by assessing its output. Credited with improving the performance of distributed IT systems, observability uses metrics, logs and traces to allow teams to get to the root cause of an issue. In this episode of the EM360 Podcast, Analyst Susan Walsh, Founder and MD of The Classification Guru speaks to Martin Mao, Co-Founder and CEO at Chronosphere, to explore: Observability and its history Adopting observability when becoming cloud-native Use cases
The trend of data at our fingertips is continuing. Virtually, everything we do is impacted by data. From driving your car to shopping to fighting pandemics such as Covid-19. Everything is impacted by data and understanding is improved by embracing and using it Data powers many technologies and itself is neither good nor bad. As data influences more of our life, we have to ensure that we use it responsibly so as to improve the lives of everyone from customers, employees, citizens, and the planet we all live on. We face many challenges and data plays a critical role in helping us make the best decisions. In the last episode of a three-part podcast series with Safe Software, Analyst Susan Walsh speaks to Don Murray, President and co-founder of Safe Software, to explore: How data was critical in the fight and management of Covid 19 around the world. The importance of using data responsibly so that people and organizations understand the often unintended consequences of their actions. The critical role of data is to drive decisions to meet the challenges we face as individuals, organizations, and a planet. Our future depends on using data.
There is no time like now for all of us to embrace data.
We often hear about the importance of performance when it comes to data. But how can you ensure that storage solutions meet the demand for efficient access to data without slowing down internal processes? In this episode of the EM360 Podcast, Editor Matt Harris speaks to Jeff Whittaker, VP of Product Management at Panasas, to discuss: Rapid access to data without compromising performance Purchasing IT infrastructure and priorities AI and high-performance computing
The trend of data at our fingertips is continuing. Virtually, everything we do is impacted by data. From driving your car to shopping to fighting pandemics such as Covid-19. Everything is impacted by data and understanding is improved by embracing and using it Data powers many technologies and itself is neither good nor bad. As data influences more of our life, we have to ensure that we use it responsibly so as to improve the lives of everyone from customers, employees, citizens, and the planet we all live on. We face many challenges and data plays a critical role in helping us make the best decisions. In the last episode of a three-part podcast series with Safe Software, Analyst Susan Walsh speaks to Don Murray, President and co-founder of Safe Software, to explore: How data was critical in the fight and management of Covid 19 around the world. The importance of using data responsibly so that people and organizations understand the often unintended consequences of their actions. The critical role of data is to drive decisions to meet the challenges we face as individuals, organizations, and a planet. Our future depends on using data.
From healthcare to finance, manufacturing, energy and more, business automation is taking the enterprise tech world by storm. The ubiquitous nature of automating recurring processes can fit the priorities of any sector. So how should businesses be looking to adopt and utilise automation? In this episode of the EM360 Podcast, Editor Matt Harris talks to Mika Vainio-Mattila, CEO and co-founder of Digital Workforce, to discuss: End-to-end business automation Application of APIs and low code tooling How business automation will mature by 2030
Deep learning is a subgenre of machine learning and AI that mimics human behaviour - lending itself to predictive modelling and statistics. But how can we take the power of deep learning and make it more accessible to the citizen data scientist? In this episode of the EM360 Podcast, Analyst https://em360tech.com/user/3633 (Christina Stathopoulos) speaks to https://www.linkedin.com/in/richardheyns/ (Richard Heyns), Founder and CEO of https://em360tech.com/solution-providers/brytlyt (Brytlyt), about: Deep learning and artificial neural network systems DL vs ML Embedding AI into the database
Rapid Product Development is a method of creation quickly gaining popularity; allowing developers to prove their concept and bring products to market faster. Automation is a key part of this, assisting in initial build-out times and allowing for the inclusion of more unique features. In this episode of the EM360 Podcast, Editor Matt Harris speaks to Max Tkacz, Principal Product Designer at n8n.io, as they explore: Maintenance vs initial fixed cost Building in features without altering the core product Keeping things accessible while empowering the skills of tech teams
Enterprises accumulate huge amounts of data every single day. From your marketing departments to sales teams to social media strategies, your company is generating data that can provide valuable insights into how you should operate. But how much of this insight is being overlooked? A recent Tableau report revealed that more than 4 in 5 CEOs wanted to be data driven - with leaders understanding the ability to make better decisions. In this episode of the EM360 podcast, Editor Matt Harris speaks to Steve Neat, GM EMEA of Alation, to explore: Why data catalogs are important Fostering a data culture Utilising data to make decisions
Machine Learning Operations, or MLOps, is a set of practices that aims to deploy and maintain machine learning models reliably and efficiently. Similar to the DevOps approach, MLOps seeks to increase automation and improve the quality of production models while focusing on business requirements. In the first part of this three-episode series on the ‘Transformational Serverless Acceleration for Analytics’, Analyst Christina Stathopoulos speaks to Richard Heyns, Founder and CEO of Brytlyt to cover: Why do two-thirds of models built with the intention to deploy never make it to deployment Databases and the critical role they play Scaling up analytics and ML
Unstructured data refers to the information that isn't arranged according to a pre-set data model, meaning it can’t be stored in a traditional database or RDBMS. With recent numbers showing that up to 90% of the data collected by enterprises is unstructured, how can businesses pivot into managing these huge amounts of information? In this episode of the EM360 Podcast, Editor Matt Harris speaks to Paul Speciale, CMO at Scality, to discuss: What is behind the huge growth in data Managing unstructured data Selecting a storage solution for cloud, on-prem and edge deployments
API security is a key component of modern web application security. But due to their common use, and their access to sensitive data, they are quickly becoming a primary target for attackers. A recent study from Imperva showed that 70% of organisations believe a lack of API security has restricted their API adoption - but should companies feel anxious that API adoption will increase their attack surface? In this episode of the EM360 Podcast, Editor Matt Harris talks to Karl Triebes, SVP Product and GM AppSec, as the pair explore: APIs and their importance in the modern economy Data breaches and how to stop them Managing identity and access management for APIs
Hyperautomation refers to the approach businesses can take to rapidly automate as many IT and business processes as possible. Using RPA and low-code/no-code tools, the hyperautomation software market has exploded in the last few years as enterprises seek to streamline their internal processes - with Gartner expecting it to reach a value of $600 billion by the end of 2022. So just how is this automation philosophy gaining so much traction? And why do businesses need to care about it? In this episode of the https://em360tech.com/ (EM360) podcast, Editor https://www.linkedin.com/in/matt-harris-269bb7177/ (Matt Harris) speaks to https://www.linkedin.com/in/paul-j-turner/ (Paul Turner), Automation Expert at https://em360tech.com/solution-providers/trayio (Tray.io), to discuss: The true definition of hyperautomation Shifting from a project mindset to a product mindset How to successfully implement hyperautomation
Continuous integration and continuous delivery/deployment, or CI/CD, refers to the method used to deliver apps by introducing automation into the development stages. But why is this corner of the tech world gaining so much momentum? In this episode of the EM360 Podcast, Editor Matt Harris speaks to Rob Zuber, CTO at CircleCI, as they talk about: Creating a more positive experience for developers using CI/CD Software delivery metrics and what makes an elite team How developers can implement CI/CD to build, test and deploy more efficiently
Back in March, the FBI revealed that the majority of ransomware attacks against critical infrastructure target the healthcare industry. But why is the public health sector being attacked more than, for example, the banking or retail sector? In this episode of the EM360 Podcast, Editor Matt Harris speaks to Trevor Dearing, Director of Critical Infrastructure Solutions at Illumio, as they explore: The pandemic’s role in enlarging the healthcare industry attack surface Isolating attacks vs preventing them How public health organisations can strengthen their security posture
Automation is well-known for facilitating higher production rates and allowing for more efficient use of materials across the worldwide workforce. But how can it be used in the modern workplace and across the business to break down barriers for neurodiverse and disabled people? In this episode of the EM360 Podcast, Editor Matt Harris is joined by https://www.linkedin.com/in/gavin-mee-4b309b2/ (Gavin Mee, MD for Northern Europe at UiPath), as the pair discuss: How automation tech impacts consumers and organisational culture Technology’s role in breaking down barriers Why automation is becoming a strategic priority for the C-Suite
Attack surface management is the sustained monitoring, classifying, and inventory of a businesses IT infrastructure. It sounds as simple as asset management, but ASM is different in the way it approaches these responsibilities from an attacker’s perspective. The security of an enterprise's surface is paramount in the current era of cloud - but how can companies manage their cloud security posture management and tackle basic misconfigurations? In this episode of the EM360 Podcast, Chief Research Analyst at IT-Harvest Richard Stiennon speaks to David SooHoo, Director of Product Management at Censys, as the pair discuss: Attack surface management vs asset management The shift of the cloud Zero-day attacks and how to mitigate them
Businesses today are under increasing pressure to level up data security as ransomware and data theft continue to rise. Data-first security solutions provide businesses with next-generation protection against exfiltration while maintaining accessibility for day-to-day operations, even during an attack. In this episode of the EM360 Podcast, https://www.linkedin.com/in/dr-eric-cole-92a164211/ (Dr. Eric Cole), CEO and Founder at https://secure-anchor.com/ (Secure Anchor Consulting) speaks to https://www.linkedin.com/in/paul-lewis-17ba987/ (Paul Lewis), CEO of https://calamu.com/ (Calamu), about: Today’s biggest threats to data The problem of data exfiltration How a data-first security approach provides next-generation protection
The explosion of 5G has resulted in organisations having more efficient signalling for Internet-of-Things (IoT) devices, faster connectivity speeds, and greater network performance. However, the use of 5G has also opened the door to new potential threats and vulnerabilities such as DDOS attacks on 5G service interfaces and cyberattacks on the IoT ecosystem, which has led to zero-day exploits and software tampering. So, as 5G grows in use, what can organisations do to protect themselves against such attacks? In this EM360 podcast, Content Producer Matt Harris talks to https://www.linkedin.com/in/sunil-ravi-065b971/ (Sunil Ravi, Chief Security Architect at Versa Networks), to discuss: The new threats that organisations are exposed to due to 5G such as zero-day exploits, DDOS attacks and lateral movements in 5G networks. Why the telecommunications industry does not take security seriously when it comes to 5G networks and how this mindset can change. How organisations can strike a balance between security and optimal networking performance.
The Nature of Cybersecurity is undergoing rapid evolution. Cyber attacks are becoming more violent - and sophisticated. Big developments in tech over the last few years have led to some of the most shocking ransomware incidents. In this episode of the EM360 podcast, Chief Research Analyst at https://it-harvest.com/ (IT-Harvest), https://www.linkedin.com/in/stiennon/ (Richard Stiennon) speaks to https://www.linkedin.com/in/mmmpp/?originalSubdomain=uk (Mariana Periera), Director of Email Security Products at https://www.darktrace.com/en/ (Darktrace), to explore: How businesses can come back stronger following a threat The email supply chain and how attackers are using legitimate credentials to attack Core capabilities and the importance of augmenting with AI The true changing nature of cybersecurity
In 2021, more than half of all widespread threats began with a zero-day exploit that was targetted by threat actors before vendors could even make patches available. With security teams now being put under immense pressure, what can organisations do to help secure their online presence against modern cyber threats? In this episode of the EM360 podcast, Content Producer Matt Harris talks to Caitlin Condon, Vulnerability Research Manager at Rapid7, as they explore: How security teams can respond to threats more swiftly and effectively Remote working’s effect on company weakpoints How enterprises can better understand and remediate high-priority threats
When it comes to cybercrime and cybersecurity threats, social engineering attacks are unique in the way that they rely on human error versus software and operating system vulnerabilities. This is because as technological defenses become more and more robust, cybercriminals are increasingly targeting the weakest link in the chain: people. Using a variety of means both online and offline, unsuspecting users can be conned into compromising their security, releasing sensitive information or even transferring money. Secureworks Adversary Group, a security consulting department within Secureworks, walk-us through various social engineering scenarios used during their attack simulations. In the third episode of this three-part podcast with Secureworks, our host Dr Eric Cole the Founder and CEO of Secure Anchor Consulting will be talking with Ben Jacob, Technical Lead at Secureworks, about: Social engineering attack techniques and their lifecycle How phishing, vishing, and spear-phishing impact industries from a social engineering standpoint What can companies offer from a training and education standpoint to help mitigate these risks Value of XDR in detecting suspicious user behaviour
Artificial intelligence. The catch-all term defines the machines that can mimic and display sentient cognitive skills such as learning and problem-solving. A key part of modern technology, the advancements of AI indicate just how far the human race has come. AI can be used by businesses to interpret and use massive volumes of data. In this third episode of a three-part EM360 podcast series with Findability Sciences, Data Whisperer and Analytics Expert, Christina Stathopoulos speaks to the company’s Founder and CEO Anand Mahurkar, as the pair explore: Getting the most out of wide data Bringing the power of AI to traditional automation solutions Calculating ROI for AI projects
The cloud experience has had far-reaching benefits on all sectors within the enterprise. Digitally, cloud-based IT has evolved the capabilities of technology, while cloud-based infrastructure lets IT teams deliver flexible and on-demand resources that boost a company’s agility. But with a recent study showing that 3 out of 5 companies who have moved to the cloud have repatriated workloads to on-prem environments, why must businesses bring their cloud experience on-premises? In this EM360 podcast, Content Producer Matt Harris talks to Tim Pitcher, VP of Nebulon, as they discuss: Investing in achieving a cloud-like experience in their data centres What enterprises can learn from smart devices to build a smart infrastructure Key trends in the data centre space
Cyber insurance helps to provide critical cover for those who need protection against digital threats. While businesses are responsible for their own cybersecurity, liability coverage can help provide crucial support to help them stay afloat when the worst happens. This includes the costs of investigating a cybercrime, recovering lost data and restoring of the systems. It can even recoup the loss of income, manage reputation, and notification costs if required to notify a third party. In this third episode of a three-part series with Sophos, Senior Director Nicholas Cramer talks to Dr Eric Cole CEO and Founder of Secure Anchor Consulting about: The current state of cyber insurance Difficulty in getting policies How to better position your EDR and MDR
Digital twins are virtual models designed to accurately reflect a physical object or process. The real-world applications of this are endless - from city planning to construction and decoration, digital twins can help you visualise concepts within spaces with ease. When it comes to processes a digital twin can represent measurements of flows that are difficult to show such as wind direction, or temperature of flows within pipes. What’s more, the twinned object can be outfitted with sensors and produce performance data that can be applied to the digital copy. This offers a valuable insight into how the physical object will perform in real life. How do digital twins relate to spatial data? In the second episode of a three-part EM360 Podcast with Safe Software, President Don Murray speaks to Susan Walsh, Founder and MD of The Classification Guru, about: Digital twins and the evolution of spatial data What expertise and requirements are needed to create a digital twin The potential that lies in digital twins for the future and how they can move society forward
A recent F-Secure survey of 7,200 internet users showed that two-thirds of remote workers have reported worrying about their online security and privacy. And with a large percentage of the UK population transitioning into remote work following the pandemic, many have had to take cybersecurity seriously when accessing company platforms and data on our personal devices. But what exactly is meant by ‘digital anxiety’, and why are more people experiencing it? In this episode of the EM360 Podcast, Content Producer Matt Harris speaks to Tom Gaffney, Principal Consultant at F-Secure, as the pair explore: Digital anxiety and why more people are experiencing it The steps employees can take to secure themselves and their privacy Smart habits to bring into your routine
Cyber risk intelligence is critical for businesses that operate in the digital world. It is the collection, evaluation, and analysis of cyber threat information by those with access to all-source information. Like other areas of important business intelligence, cyber threat intelligence is qualitative information put into action to help develop security strategies and aid in identifying threats and opportunities. In this episode of the EM360 podcast, Richard Stiennon, Chief Research Analyst at IT-Harvest, speaks to Caitlin Gruenberg Director, Risk Solutions Engineer at CyberGRX as the pair explore: Third-party cyber risk management vs self-assessments Cyber risk intelligence in the wake of huge, high-profile breaches The meaning of a true risk exchange
Full-stack Observability (FSO) allows real-time monitoring across the whole modern technology stack - bringing applications, software, storage, services and network under one roof transforming siloed data to allow for omniscient management and actionable insights. Through FSO, IT teams can develop a deeper understanding of how the cogs of their application topologies turn, and can easily access and search data. But why is full-stack observability so important? In this episode of the EM360 podcast, Content Producer Matt Harris talks to Stuart Little, SHI International EMEA Commercial Director at Cisco Solutions, and James Harvey, Executive CTO EMEAR at Cisco App Dynamics, to discuss: FSO and the components that make it up Why organisations need to care Case studies of how FSO has turned enterprises around
Breaches are nothing new to the tech world. But since the beginning of the pandemic especially, the world has seen serious security attacks which have massively disrupted the functionality of enterprises. Moving to the cloud over the last two years has seen the world shook with some of the biggest and most unforgettable safety breaches like Accenture, Verizon and Kaseya - in fact, 40% of organisations experienced some sort of cloud-based data breach in 2021 (451 Research). Why are these cloud data breaches happening, and how serious is this issue? In this episode of the EM360 podcast, Content Producer Matt Harris talks to Thorsten Geissel, Director of Sales Engineering, EMEA at Tufin, to explore: The most common cloud misconfigurations that lead to security breaches Automation tech’s role in security policy management How companies can achieve end-to-end cloud network security
Data democratisation is the continuous process of enabling company-wide access to data, regardless of technical know-how, in a bid to spread a data-led decision-making mindset across all departments of an organisation. It can be a big challenge - and serious investment - for companies as employee education and tool implementation is not trivial undertakings. How can companies set up their data democratisation strategy? In this episode of the EM360 podcast, Content Producer Matt Harris talks to Giuseppe Mura, Director of Solution Engineering at StreamSets, as they tackle: The steps companies should utilise to set up their data democratisation strategy How the demand for DataOps will be affected as businesses adapt their data integration processes Bringing in non-IT-native and non-DevOps experts and providing them with everything they need
Identity sprawl describes the growth in the many differing and incompatible accounts a user creates to access online services. As the number of accounts increase, a user’s identity and online presence spreads, or ‘sprawls’, which can be excessively confusing and even dangerous when compared to a more unified approach. So how can organisations help to consolidate identity to solve this access management issue? In this EM360 podcast, Head of Content Max Kurton talks to Chad McDonald, Chief of Staff at Radiant Logic, as they explore: The common challenges and pain points of identity sprawl for enterprises The best way organisations can go about implementing identity data fabric to reduce IAM stress How Radiant Logic’s intelligent identity data platform is changing the game
CIAM enables organisations to securely capture and manage customer identity and profile data, as well as control customer access to certain applications and services. Usually providing a variety of features including customer registration, self-service account management, and 2FA/MFA, the best CIAM solutions ensure a secure and seamless customer experience. But how can enterprises hit a balance between security and customer friction? In the first of two EM360 analyst podcasts with Beyond Identity, Chief Research Analyst at IT-Harvest, Richard Stiennon speaks to Jing Gu, Senior Product Marketing Manager, about the role CIAMs play when it comes to managing end-user activities.
Cybersecurity has traditionally been the responsibility of the CTO and IT department, casting a company-wide forcefield to protect businesses from exterior attacks. But in the modern age of heightened connectivity, as remote workers bring sensitive company information into their homes, the responsibility could - and should - fall upon every member of the team. In this EM360 Podcast, Head of Content Max Kurton talks to James Hadley, Founder and CEO at Immersive Labs, to explore the benefits of every department having a hand in cybersecurity - and the risk of having ‘too many cooks’.
Social media offers an important outline for people of all ages and walks of life to connect, share life experiences and post pictures of their breakfast. But oversharing - or not being wary of impostors - can lead to serious compromises in personal and professional security. In a press release on the report's findings, Phishlabs “enterprises must broaden their line of defense [in 2022,] starting with strong, cross-channel monitoring, and building relationships with technology providers in new areas.” “Fraud-related attacks made up almost half of all social media threats in 2021” In this episode of the EM360 podcast, Head of Content Max Kurton talks to John LaCour, Founder & CTO of Phishlabs and Principal Strategist at parent company HelpSystems, about: Where the concept of ‘social media as a threat channel’ comes from and what it concerns What the first steps towards the mitigation of social media threats look like and the route companies need to take How enterprises can turn social media into an actionable intelligence channel
The current state of wide data is that it is not as widely used for Artificial Intelligence as it is for analytics. While analytics needs a treasure trove of historical data, AI merely needs a variety of big data. And big data needs AI, too. It's the most efficient and effective way for organisations to optimise their processes and identify their audiences. But how can we use machine learning practices and AI to tackle critical business challenges? In this 3 part EM360 Podcast series with Findability Sciences we have previously discussed 'What Big Data Discussions Ignore' In Episode 1. In this second episode, we are joined once again by the Founder and CEO Anand Mahurkar to talk about: The relationship between wide data, learning and machine learning Critical business challenges when it comes to AI mimicking a more human process Why we should be using wide data for AI
In this age of technological evolution and industrial resilience following the fallout of the Covid-19 pandemic, businesses have had to modernise working practices in a big way. From installing unified communications software to ensuring cybersecurity as employees bring sensitive information and company data out of the working environment, businesses have been thrust into the 2020s. But just how exactly can technology modernise working practices? In this episode of the EM360 Podcast, Content Producer Matt Harris speaks to Russell Bristow, Senior Partner at Ampito, as the pair explore: Why working practices need to be updated How data sensitivity can be ensured and secured Real-world examples within the NHS and auto-repair industry
In this EM360 Podcast, we delve into the use cases and benefits of CX and scalable unified-communications-as-a-service (UCaaS) in the modern contact centre with Chris Selby-Rickards, UK Marketing Director at NFON, and Steve McSherry, Commercial Director at Daktela UK
CEO of Evervault, Shane Curran, shares his thoughts on plaintext data and why it is the 'real enemy' when it comes to ransomware attacks.
Edge computing places information processing closer to the consumer, allowing for lower latency and higher reliability to transfer faster and more secure data. Growing in popularity, edge is often talked about with decentralisation, an important and unique advantage to a company's digital strategy. It sounds simple; but the best place to run business logic doesn't always mean the cheapest or most secure. Edge computing's increasing usage has lead some to refer to it as 'the new mainframe' In this podcast Max Kurton, Head of Content at EM360 talks to Melissa Dore, VP of Partnerships and Alliances at Ori Industries. Throughout this podcast, Melissa and Max explore: The basics of edge computing and the current state of the industry How it relates to cloud and fog computing when it comes to decentralisation Where the future of edge is heading and how it's fundamentally changing how we interact with infrastructure
The data-driven revolution has enabled brands to achieve true customer centricity — but only if they have the right data analysis and experience orchestration capabilities. Whether creating a single customer view, generating predictive insights, or orchestrating seamless omnichannel experiences, organisations must work to make sure their customer data is accurate, accessible, and actionable. Hosting this episode of the EM360 Podcast is Susan Walsh, Founder, and MD of The Classification Guru. Joining her is the Head of Martech Strategy at ActionIQ, James Meyers, who will be sharing his insight on the data-driven revolution and its growing impact on the customer journey and customer experience (CX) as a whole. With an ever-growing number of competitors entering the market, it's vital for businesses to grow and retain their customer relationships by ensuring they have a polished, data-driven CX strategy. Tune in to learn about: Why siloed data continues to be one of the biggest pain points, for organisations looking to create seamless CX The types of valuable insights marketers can obtain if their company's data is de-siloed Use cases of customer data platforms and how they're helping to power CX strategies today Decisions organisations face when choosing between building a CPD in-house or licensing from a vendor
Antivirus software, and indeed all security systems for businesses, have existed since around 1971 to address some of the potentially devastating effects unwanted adversaries could cause to our systems. The current threat landscape has hugely shifted over the last few years with the increase of hybrid work. According to the BCC, more than half of all organisations recognise that exposure to attacks has increased since their employees have started to work from home instead of from the office. This has led to new demands for antivirus providers and security systems for businesses. They now have to match new expectations, and these expectations are fully justified - hybrid does create serious security challenges. In this podcast, Peter Stelzhammer, Co-Founder of AV-Comparatives, runs us through: How security systems for businesses are entering paranoia mode How the current threat landscape is influencing business attitudes The effectiveness of antivirus tests.
When looking into Unified Communication and Collaboration tools, there are many factors to take into account that, if not navigated around carefully, can slow down implementation. Your end-users need to be well trained, and they need to be versatile enough to adapt to any changes in the software. We saw enough problems with employees saying, "I can't hear you, is your microphone on?" 10 times a week in the last year, but when collaboration tools end up dealing with more complicated and sensitive tasks than simple work meetings, training can be the difference between a company's success and its failure. In this podcast, Max Kurton from EM360 talks to Pascal Moindrot, Chief Operating Officer and Co-Founder at Kurmi Software. Throughout this podcast, Pascal will run us through: The challenges with end-user adoption How Unified Communication and Collaboration tools can streamline deployment The day to day management of enterprise comms processes
While AI is now beginning to be used in every industry (to the point in which it is now being regarded as a buzzword), few organisations are reaping the benefits of using AI for cybersecurity. The COVID-19 disaster urged on a second pandemic, dubbed by many as the 'cybersecurity pandemic', leading to an influx of new solutions. The worrying thing is that despite the huge increase of cybersecurity solutions and the technological breakthroughs that we have seen within the last few years, adoption has been slow. This means that while new solutions have arrived, adversaries are improving their abilities at a faster rate than organisations have been able to keep up with. In fact, over ⅓ of endpoints deployed in the UK currently have no security agent installed and 70% of businesses report that they cannot ensure that every endpoint has the same level of protection. In this podcast, Brooks Wallace, VP EMEA at Deep Instinct, discusses the reasons why adversarial AI poses a risk to companies using legacy systems and the top considerations to take into account in 2022. AI for cybersecurity is no longer a pipedream - it's the reality of some of the most robust organisations in the industry.
Over 90% of people feel overwhelmed with the sheer abundance of data they have at their disposal, which is a story that we hear all too often. While data is essential to all forms of decision, more and more companies suffer with the same issue, which is that they have too much data coming from different places, meaning it's hard to know what is genuinely reliable. As a wise man once said, "you can have the most expensive cranes in the world, but if you're building a house out of Lego, expect child's play." So what can you do to simplify this? We hear time and time again that C-suite executive rely too much on gut decision making, but is a bit of intuition a bad thing? The concern that many organisations have is that it's near enough impossible to quantify intuition, making it hard to really see if it results in good results. Joining us to explore the use of data analysis tools in the modern day is Nicky Tozer, EMEA SVP at Oracle NetSuite. In this podcast, Nicky delves into: Gut-based decision making in the workplace Data analysis tools and informed decision making Providing employees with ready-to-use insights
As we make our way into 2022, we have to acknowledge that workers are still inclined to favour remote working jobs. In fact, statistically people of colour and women are more likely to pursue remote working jobs, with 87% of Asian workers, 81% of black workers and 85% of women of every ethnicity stating it as a major preference. When you take into account that many workers are looking for new places to work in 2022, employers will have to meet new demands in order to create an attractive work environment for future staff. That said, a recent report called "The great executive-employee disconnect" recently got published by Future Forum, which found some worrying statistics. According to the report, "Most executives (66%) report they are designing post-pandemic workforce policies with little to no direct input from employees."Now, if workers' demands are increasing, surely employers need to create a workplace with their employees in mind, but how does one go about doing that? In this EM360 Podcast, our Head of Content Max Kurton talks to Stuart Templeton, Head of UK Slack, about how employees are faring 18 months into the pandemic. Throughout this podcast, they cover: How to win the war for talent How to create equity at work Being intersectional in the workplace How to make an attractive work environment
Ever heard of the data-decision gap? If you have, you likely recognise that many organisations struggle to make data-driven decisions. A big problem for many organisations is while they might have data, the source of this data is questionable at best, which makes it hard to drive decision making. A key answer is visualised data and the ability to test your data to see if it genuinely can bring you in depth results. A problem that occurs with this is the the traditional approaches to visualising data, which are usually outdated. According to Quantexa's Data in Context Report, Outdated approaches tend to be rules-based, reliant on batch-processing and require too much manual work. Traditional single view solutions are often use-case specific and hard to integrate, quickly replicating data silos, according to 46%. They also struggle with integrating key third-party data, 40%, such as public records, which are critical for analytics in many use cases.In this podcast, we speak to Jamie Hutton, CTO at Quantexa. Jamie gives us a full overview of: The dangers of the enterprise data decision gap How this gap affects C-suite level decision makers How to build a robust data foundation How to make trusted decision making How to make a platform for visualised data
You know that using social media in business can lead to some fantastic results, so you think of a post that you know will resonate with your audience. After a few hours building a graphic, using social media listening tools and doing thorough background research, you post it. At the end of the week, the post only has two likes. You are thinking, "Should I use a social media agency?" Knowing exactly how to market yourself on social media is an absolute minefield but sadly it is key to nurturing your existing relationships and engaging prospects. Occasionally, businesses look for advice from a social media agency. The problem is that if you do not know exactly what outcomes you want to see from social media and do not know how to align social strategies with specific business outcomes, a social media agency won't either. You have the strongest understanding of your target market, what your audience likes and what you want to demonstrate to your audience when using social media in business. Audiences want to see personalised posts from their favourite influencers and a one-size fits all approach never works. You just need to use those insights and find out the best way to apply them in order to reach your audience. In truth, all you need is a push in the right direction. In this EM360 podcast, we speak to Tim Rickards, Director of Social and Content Strategy at Hearsay Systems. Tim runs us through the key findings of their Social Selling Content Study, the types of social content that resonates best for B2B and B2C audiences, how to draw on real world analytics to accelerate your sales cycle and the best ways to engage prospects and nurture relationships. This podcast is essential for anybody involved in sales or marketing, regardless of the industry you belong to.
You can have the greatest tech in the world but if you only have bad data, you're effectively flogging a dead horse. We might hear people say that data is their biggest asset and that data is the only way to make informed decisions but this data is very often pulled from various different locations that are impossible to track. You have a statistic that says that 65% of people in your target market are looking for better customer support, but where did that number come from? When was this study conducted and what was the sample size? The reality is that without a strong data strategy, you will inevitable have bad data, and bad data is of no use to anyone. We recently did a podcast on how c-suite executives often rely on gut based decision making, which brings up an interesting discussion point: why do they not trust their data? According to Syniti, only 5% of c-suite executive trust their enterprise data. If they recognise they have bad data, what steps can they take to improve their data strategy? In this podcast, we explore some of the key themes that are holding companies back from implementing a strong data strategy. Kevin Campbell, CEO of Syniti, reveals that only 23% have implemented a consistent and policy-aligned data strategy at scale across their organisations, but he also details the steps you need to take. With facts, figures and high quality resources at hand, this podcast proves to be an essential guide for anyone who is currently dealing with the everlasting headache of bad data. After all, you might have the most expensive crane and forklifts on the market but if you are building a house made of sand, you should expect it to fall apart by the morning.
With the increase of cyber threats globally since the pandemic, conducting a cybersecurity risk assessment for your business is more important ever. Making your organisation compliant with cybersecurity measures is essential in the modern day but did you know that only 60% of organisations have a comprehensive cyber insurance policy to protect them from financial losses in the case of a cyber attack? This number only becomes more concerning with the added fact that hospitality services are actually the most at risk. According to Arctic Wolf, "the hospitality industry has the lowest adoption rate of all industries surveyed with just 35% of respondents from this vertical claiming to have a comprehensive cyber insurance policy." It asks the question, has the hospitality sector conducted a thorough cybersecurity risk assessment? Are they prepared for threats along the way and what is their backup plan if all else fails? The risk is simply too high to gamble on, particularly given the amount of customer information, revenue and credentials that can easily be exploited if so much as one threat penetrates their defenses. Joining us in this podcast is Ian McShane, Field CTO at Arctic Wolf. Ian talks us through: Vulnerability management How to conduct a cybersecurity risk assessment The current stability of various industries in relation to cybersecurity And much much more.
As we know, marketers are always looking for an edge, something that positions them above their peers. By embracing new technologies that enable conversations such as Chatbots, businesses can design a conversation flow and solicit more valuable information about customers' needs. In this podcast, Jiaqi Pan, CEO and Co-Founder of Landbot, walks us through why conversation is critical for marketers. He begins by outlining the significant downsides of lead forms and how conversations can improve business processes and strengthen relationships with new leads. Also, he covers how chatbots can help to solicit more valuable information about a customer's needs. Finally, Jiaqi provides some use case examples of Landbot's no-code chatbot platform builder.
Hosting this episode of the EM360 Podcast is Torsten Volk, Managing Research Director at Enterprise Management Associates (EMA). Torsten speaks on how Kubernetes became a platform that brought developers and operators together with Grant Miller, CEO and Co-founder at Replicated. The two experts explore: The term 'Multi-prem', where it comes from, and how it relates to Kubernetes How Replicated chase after integration points with Kubernetes vs OpenStack How to differentiate Kubernetes from other open-source contained orchestration systems How organisations should deliver and orchestrate applications to stay on top of developments
If you have been paying attention over the last few years, you will realise that cybersecurity is moving more towards an anticipatory approach, particularly with the advancements of managed detection and response software. Beyond this however, precautions now have to be interwoven into the very fabric of an organisation. Email protection is not enough; what we need is a comprehensive network throughout Microsoft 365 that establishes security precautions within Teams, SharePoint and OneDrive. With the birth of the hybrid work environment, establishing security guidelines and implementing detection and response software throughout your team is essential. Organisations are now working throughout the cloud, which creates new attack vectors for adversaries. While productivity is up for organisations, it is also up for adversaries. Phishing scams and malware are now being tailor made for hybrid workers and the only solution is to invest in a more robust managed detection and response software. In this podcast, we speak to Datto's CISO Ryan Weeks. Ryan walks us through the security gap in the public cloud and why it's causing deep problems for organisations, how to detect and respond to ransomware before it causes a problem for your organisation and how to build your first line of defence. This podcast is a must listen for anybody that works in a SME or startup; it's the ultimate guide for protection in the hybrid world.
With an increase in adoption of commercial and investment banking technology, organisations are now providing customers with greater communication, ease of access and financial opportunities. In fact, between 2017-2021, consumers in Asia-Pacific emerging markets increased their use in digital banking by 33%, with 88% of consumers now utilising it today. Furthermore, investment banking technology really took off during the last decade with blockchain as even political bodies such as the EU are now looking to invest in crypto currencies. For many people at heritage financial firms, the digital transformation seems like a scary move. Gartner recently predicted that by 2030, 80% of heritage financial firms will either go out of business, become commoditised or only exist formally. The expectation is that fintech organisations and global digital platforms will only gain more relevance and thrive under the conditions of digital transformation. The problem for many is the use of legacy technology, which by its very nature is traditionalist and outdated. With an increase of people working from home, people want both stronger commercial and investing banking technology. For the customer, it will allow them to access their finances with ease, which creates opportunities for fintech security companies that are then able to provide greater protection from outside threats. For investors, the ability to mobilise their investments with greater ease can only be achieved through stronger technology. In this EM360 podcast, we speak to Mark Aldred, VP of Sales at Auriga, about the use of banking technology in 2021, the risks associated with it, what new technologies we expect to see and how we, as business professionals, can prepare ourselves for the inevitable dangers.
As much as people fear that they have lost their anonymity on the internet, technologies that previously companies and individuals alike to regain this privilege are starting to show their shortcomings. The VPN setup, which has been gaining steady momentum since it became publicly available in 1999, is finally reaching the end of its lifeline as the surge of cybercrime has reared its ugly head. The best thing we can do during this uncertain time is to make the VPN setup comfortable in its final days, say our farewells and welcome the future of SASE technology. With the increase of remote working globally helping to improve productivity and employee satisfaction, new challenges have arrived. One of the key problems comes with unsafe Wi-Fi networks, which can usually be found within cafes or at home and can put organisations at risk. The VPN setup also often covers huge areas, which when combined with insecure networks can mean that potential security risks are actually more destructive than ever before. SASE, or Secure Access Service Edge, provides users with access to critical apps for all parts of your business, without having to go through corporate headquarters. This means that regardless of where you are working, your data remains safe and your network remains protected. Joining our Head of Content Max Kurton in this EM360 Podcast is Mike Wood, CMO at Versa. In this podcast, Mike guides us through the way in which IT teams go about introducing, implementing, and adopting SASE into their organisations, the shortcomings of the VPN setup and much more.
Needless to say, trusted computing is a complex and heavily debated subject. Even today, in 2021, the debate continues, and organisations are still weighing up the benefits of what a trusted computing hardware or software system might bring to them. In traditional trusted computing hardware, technology is used to allow the user to decide what they can trust and what they can't. Of course, this advantage of freedom can seem fantastic to many users, but the debate opens up again surrounding the effectiveness of humans. We already know that humans make mistakes, and we know that sometimes computers can be much better judges thttps://em360tech.com/podcasts/daniel-burrus-agility-react-disruption (han humans.) Opening this can of worms with us in this EM360 podcast is Thorsten Stremlau from Trusted Computer Group. In this podcast, we hear how far trusted computing hardware and software has come in the last few decades, what the future brings for it, the answers to some of the most popular questions in this hot topic and the benefits trusted computing can truly bring.
With the increasing lack of anonymity on the internet, users and organisations alike are looking to implement a VPN setup within their system in order to gain a stronger sense of security. In countries with strong firewalls such as China, businesses prioritise the use of VPNs in order to open themselves up to the global market. With that said, a weak VPN setup can often cause severe security problems within their organisation. Companies are now forcing their workforce to work from home, and while it's granted a huge amount of flexibility and has yielded some overwhelmingly positive results for organisations, it comes with security risks. When organisations implement VPNs, it means that they are extending their full network into their home device and are actually allowing more entry points for potential adversaries to commit security offenses. Rejecting the VPN Setup in Favour of Zero Trust Network Access ModelsMore modern practices are favouring Zero Trust Network Access models, or ZTNAs, as a way to assist organisations with hybrid working. ZTNA is an architecture that is fundamentally different from a VPN setup and allows users to operate on a separate network. In this podcast, our Head of Content Max Kurton speaks to Kurt Glazemakers, Chief Technology Officer at Appgate. They talk about the future of the ZTNA industry, the problems organisations have in switching from a VPN setup to a ZTNA and the drawbacks of using a VPN.
Privacy enhancing technologies, or PETs, can be used for a multitude of reasons; whether it's being used to decrease the crime rates of countries, for social good or even for the use of your business, PETs have proved time and time again to be effective. PETs are broad, and when using one within your business, the focus really should be on providing a safe network for your customers, clients and consumers. One way in which PETs can be used for this is by blocking third party website traffic analysis, thus preventing your customers from being monitored. This is not only something that needs to be paid attention to by people within the tech industry, but really for any B2B or B2C business. Customer data is often readily available, and when permission has not been given by the customer, legal implications await. In this EM360 podcast, we speak to Ellison Anne Williams, Founder and CEO at Enveil. Ellison Anne covers the many different ways in which PETs can be used for social good, how to implement them, the necessity of PETs in areas such as the health industry and the future of data protecting tech.
What data science needs, in our current world where we have more data than we know what to do with, is a solution that allows data to be readily applicable and useful for the growth of an organisation. This does not just mean the ability to analyse the market, but it also means the ability to enhance integrated experiences, giving organisations a stronger connection with their customer base. This is where we start to mark the difference between data cleanliness and data readiness. With data cleanliness, we are enabling a process that fixes errors, corrects formatting and completes data within a dataset. This ultimately makes that data much more high quality and rewarding depending on what data science aims your business has. Data readiness, in contrast, is data that's ready to be used by the business owners and can be combined with other data sources in order to make intelligent decisions. Yes, data cleanliness is important in order to achieve data readiness, however the two are distinct operations. Joining us in this EM360 podcast is Mike Kiersey, CTO at Boomi. Throughout this podcast, we will walk you through the methods of becoming data ready, the best practices to maintain in your data strategy, the use of AI in data readiness and much more.
Changing methodologies and approaches to B2B marketing creates constant challenges for those attempting to reach their market segment with ease. What B2B means today is very different to what it meant in the past, and this is in part due to the effects of content marketing. While the days of print magazines, posters and radio ads are less common nowadays, new incarnations of these, in the format of content marketing, consistently change the industry. One way in which companies are now capturing the attention of their audience is through podcasting. Again, what B2B means in the modern day is different to what it meant in the past, but that doesn't mean that some commonalities cannot be held. In contrast to its distant relative, radio advertising, podcasting allows organisations to take the audience on a long journey, exploring potentially relatable problems that they face in the day to day. It still grants the advertiser air time, it still provides them with a platform to talk to people while they make their daily commute to work, but it's more in depth and relatable for their market segment. It then allows organisations to provide themselves as the solution to their posed problems, driving more leads and sales to their business. In this EM360 podcast, we are joined by Kieran Flanagan, Senior Vice President Marketing at HubSpot. Kieran is here to discuss the new age of B2B customer communication, the types of ROIs companies likely to see if they add podcasts and other digital media to their marcomms mix and other ways to implement B2B marketing campaigns.
While new technologies are constantly being developed to fight cybercrime and strengthen cybersecurity systems, much of the cybersecurity is left yawning. New additions to technologies such as Endpoint Detection and Response (EDR), while effective, are not implementing the level of change that we need to see if we want to ensure safety while reducing workloads of employees. EDR, for instance, often sends alerts to employees notifying them that unexpected activities need to be investigated. How many emails do we receive a day from job recruiters, collaboration tools, social media tools and others? Of course, investigating cyberthreats is important, but it's hard to care about additional newsflashes after receiving your 20th promotional email of the week from your local pizzeria. Beyond this, there are already some serious undeniable threats in cyberspaces that cannot be ignored. With hundreds of devices existing within every organisation, there exists hundreds of attack vectors. Yes, certain cybersecurity technologies can exist, but adversaries always develop new attack methods. Really, it's worth keeping up to date with the latest news in AI in order to find a technology that can learn these methods and grow over time. News in AI proves to be more and more interesting everyday with new technologies being applied to protect security interests. For those of us already working in cybersecurity, machine learning in AI is old news, but how many organisations are using deep learning-based prevention? According to Deep Instinct, deep learning-based prevention helps us to surpass "The Cybersecurity Trade-Off" where organisations prevent threats, but also receive high volumes of false positives. This helps to prevent a 'boy-cried-wolf' situation and instead brings real, analysed threats to your attention. Delivering us the latest news in AI is Shimon Noam Oren, VP Research & Deep-Learning at Deep Instinct. In this podcast, he delves into the 'prevention trade-off dilemma', the problems with cybersecurity prevention software, the ins and outs of deep learning and how it can provide a more robust cybersecurity methodology.
The phone scam has been in the cybercriminal's playbook for decades, but the pandemic has lead to a sharp increase of these attacks. According to Eric Griffith from PC Mag, According to Eric Griffith from PC Mag, a well constructed phone scam can exploit more money than a scam conducted via email, social media, websites or apps. This becomes all the more concerning with our reliance on our phones in 2021, particularly when employees work from home. With the increase of remote working and fewer people in conventional workplaces, the need for communication tools has of course increased, but call centres are now sifting through more work than anybody could have anticipated. For some, call volumes increased by 800%, which has created intense work pressure for employees. Cybercriminals have now adapted their phone scam methods to specifically target call centres, leaving them vulnerable to attacks and placing huge responsibilities on customer service staff. The Evolution of the Phone Scam Voice phishing, or 'Vishing', is a form of social engineering attack that is primarily used to steal privileged credentials from corporations. The aim is to manipulate the target into exposing a weakness in the company, leading to data leaks or cybertheft. Vishing is not new, but it evolves continuously; changes in the market lead to changes in behaviour, which lead to new tactics. Joining us on in this podcast is Nikolay Gaubitch, Director of Research at Pindrop. Throughout this podcast, Nikolay will explain the dangers of vishing, how it affects call centres and what you can do to protect your business from a devastating phone scam.
Security threats are unavoidable and inescapable for modern businesses. No matter the size of the enterprise, dealing with the likes of data breaches and ransomware attackers has become commonplace. The key, then, is to know how exactly to detect and respond to these incidents. With new threat hunting and detection technologies, tools, and techniques being created each quarter, the security solutions pool is becoming bigger and bigger. In this podcast, Chris Steffen, Research Director at Enterprise Management Associates (EMA), speaks with Dr. Anton Chuvakin, Head of Solutions Strategy at Chronicle and Google Cloud, about the emerging trends in threat hunting and investigation, as well as incident response. The conversation kicks off with a look at the challenges that organisations face when a breach occurs and the proliferation of high-profile security breaches and ransomware attacks within legacy systems. Dr. Anton then lends his expertise on the act of combining intelligence about global threats in the wild, threats inside your network, and unique signals from the overlap between the two, before delving into top tips for overcoming the “signal to noise” ratio. To close, the pair explore the impact of President Biden’s Executive Order on Cybrsecurity and the latest trends in threat hunting and investigation.
The world of artificial intelligence and machine learning is everchanging, with new trends being discovered every year. In the wake of GDPR in 2018, the use of such technologies was applied to legal documents, company legislations and privacy regulations. In 2019, this trend continued while others experimented with incorporating AI into video game design. In 2020, the COVID-19 pandemic meant that AI was used to create digital workers, making up for medial labour that users would usually perform while in the office. In 2021, we are seeing new trends, but we are also seeing barriers. According to IDC, the artificial intelligence market is forecast to grow 16.4% by the end of 2021, but even still, obstacles stand in the way for innovation and even for development. Deploying machine learning is difficult; that's why, for this exclusive EM360 podcast, we are speaking to Dr. Eugene Izhikevich, CEO of Brain Corp. In this podcast, we will be delving into some of the biggest problems facing the AI landscape today, predictions for 2021 and some of the solutions.
With new analytic trends emerging as we delve deeper into this decade, organisations are starting to pay attention to solutions and tools that offer them greater insights into their data. A study from Forrester Research revealed that less than 0.5% of all data is ever analysed and used, while only 12% of enterprise data is used to make decisions. As it currently stands, much of our data is confined to silos, meaning that it is too segmented to be analysed, while many organisations still have not received enough training to empower their data scientists and fix the data gap. The quickest solution would be to invest in a technology that performs much of the analysis for you automatically, i.e. augmented analytics. Augmented analytics is one of the latest data trends and for good reason; it implements machine learning and natural language processing to automate analysis processes that would usually be conducted by an expert in that field. Essentially, data is processed faster than it would be by a human, which also makes it cost effective. Despite this, some organisations remain concerned about the implementation process, the perceived risks and the costs. Joining us in this EM360 podcast is Rohit Maheshwari, Head of Strategy and Product at Subex. In this episode, we talk to him in depth about the benefits of augmented analytics, how it can bring value to your business and the restrictions of legacy software.
Implementing AI to automate sales and financial duties is nothing new, but recently there has been a lot of discussion related to AI powered Order-to-Cash platforms. In nearly every sector, reducing waiting times means reducing costs, but Order-to-Cash AI can also be the key to customer retention and expansion while also speeding up financial processes. In 2021, we are attempting to bounce back from a massive disruption, but that disruption has meant the development of new technologies that allow organisations to excel. Securing customers and retaining pre-existing customer bases has been cited as the biggest challenge to 61% of companies by SEM Rush. So, could Order-to-Cash platforms be the solution? Joining us on this EM360 podcast is Mark Sheldon, CTO of Sidetrade. In this episode, Mark delves into the the impact of Order-to-Cash AI on sales and finance teams, how payment intelligence software can benefit ROI and cost reduction as well as exploring the top considerations for organisations to be aware of before investing in AI for their sales and finance teams.
As more and more businesses experience latency issues in traditional cloud databases, edge computing is now more popular than ever before. Having a device at the edge of your network allows for smoother run times while also synchronising with other geo-distributed devices in your ecosystem that are placed on other parts of the globe. Fusing an already impressive piece of kit with machine learning results in something truly impressive: Edge AI. Edge AI brings in faster decision making, vast improvements to UX and is more energy efficient than other data management tools. Processing data can now be done in real time, so why is there still scepticism about adopting edge AI? Why haven't more businesses adopted it already? Joining us in this EM360 podcast is Dan Warner, CEO and Co-Founder of LGN; an organisation dedicated to bringing new edge technology to a wider audience.
Email is the front door into an organisation and humans typically manage it. However, with phishing attacks becoming more targeted and sophisticated, and increasing cases of account takeover and data loss due to a successful email attack, humans alone can no longer be relied on to protect the inbox. Fortunately for businesses, there are email security solutions - Artificial Intelligence (AI) technologies - that can help. Join Dr Eric Cole, CEO and Founder of Secure Anchor Consulting, and Mariana Pereira, Director at Darktrace, as they discuss email security and why organisations now, more than ever, need to treat it as a top priority. In this podcast, the pair explore how to secure enterprise inboxes with AI. Mariana leads the conversation by sharing her knowledge and expertise on the current threat landscape for email in 2021, the use of AI in email security, and the key factors decision-makers should consider when determining the best AI system. The discussion ends with a look at a real-life case study of an email attack autonomously stopped by AI. Want to learn more? Check out our recent Q&A with Mariana on how Antigena Email can create a self-defending inbox.
One of the biggest problems when managing data is that vast quantities of it is scattered across data silos and multiple systems. The primary issue this causes is the inability to shape your business to your customers' demands. What's often forgotten about is that when that data also has transactional information, it becomes hard to monitor suspicious activities from within your business. This is where money laundering becomes a fear. Regularly, industries rely on legacy systems, however this has proved ineffective as over $2 trillion is laundered every year. Financial sectors spend over $180 billion on anti-money laundering capabilities to catch less than 1% of the financial criminals responsible. 66% of this is spent on staff and with the volume of transactions increasing exponentially, it's easy to understand that simply scaling teams to manually trawl through this data is unsustainable. Increasingly, financial organisations are looking to new technologies to provide assistance. The key is to invest in the right kind of anti money laundering (or AML) software, but how do you know where to start? In this podcast, Chief AI Officer at Napier Luca Primerano and CTO of Napier Nick Portalski talk about the problems with modern approaches to AML, the potential of AI as a solution to problems in the compliance space and what the future of AML looks like.
2020 was comprised of big data breaches, leaks and new obstacles, leading to what many have dubbed a "Cybersecurity Pandemic." Surviving in these difficult times has been hard and more often than not, it's the people that suffer; in fact, 58% of breaches in the last year involved some level of personal data. The Cybersecurity Pandemic has affected so many people and organisations that the worldwide cybercrime spending is estimated to reach $6 trillion this year, a sharp increase from $1 trillion in the year before. In this EM360 podcast, we spoke to Raghu Nandakumara of Illumio about the best ways to navigate around this cybersecurity pandemic, the importance of the Zero Trust Model and the best ways to mitigate the impact of high-profile breaches in 2021.
Technology as a service is a methodological approach that seeks to place the importance of the customer's need at the forefront of the software. The world of Unified Communications saw the breakthrough of Unified Communications as a Service (or UCaaS) in around 2014 and it has since managed to leverage cloud technology to send requests and communicate across hybrid workplaces. The key with cloud technology, as always, is to simply and unify, but how does UCaaS allow organisations to achieve this goal? Explaining the ins and outs of UCaaS is Anthony Cummings, Director of Infrastructure and Operations at Frank Recruitment. In this episode, Anthony gives us the basics in UCaaS 101, the advantages and use cases of it and the way it works in hybrid workplaces to support employees and business leaders alike.
As a security framework that has rapidly developed over the last few years, "Zero Trust" has become a hot topic for many in the industry. Despite the huge amount of attention that Zero Trust is receiving, at this point 70% of reported correspondents have stated that they have no Zero Trust access projects underway or in place. The fear for many is having to struggle with the major technological shifts in strategy and architecture. In this insightful EM360 podcast, we speak to Rich Langston, Director of Product Management at Tempered, about Tempered's latest Zero Trust Report. Implementing this security framework is essential for businesses; why not tune in today to find out what obstacles you need to know about?
It's now widely accepted that customer experience (CX) knowledge now has a direct impact on a company's success, and if you don't know how to leverage that knowledge to make informed decisions, your company might not be reaching its full capabilities. The problem with focusing on CX is that it occasionally comes at the expense of organisations' security and it is also difficult to navigate around the separate global regulatory requirements. Whether you're navigating around GDPR or PIPA, improving a customer experience comes with the same difficulties. Our guest today is Phillip Dunkelberger, CEO of Nok Nok Labs. Phillip knows exactly how focusing on CX can improve your organisation and, this time, we seized the opportunity to ask him some of the most important questions on this hot topic.
Over the last decade, the development of cybersecurity has accelerated faster than ever before. The initial deployment of endpoint detection and response (EDR) was quickly replaced with extended detection and response (XDR), and it seems that this adoption of AI is transforming cybersecurity. To find out more about how AI is transforming cybersecurity, we spoke to Sohrob Kazerounian. Sohrob is the AI Research Lead at Vectra. Vectra's AI driven platform is proving useful to many companies that are looking to advance their cybersecurity capabilities.
Providing appropriate representation of women in the workforce remains a challenge for many businesses due to their complicated history with patriarchy. While many women are told that if they work hard enough, they will be able to fight sexism, this fight can only be achieved if all companies take representation seriously and provide an infrastructure that empowers women. In this podcast, we spoke to Rachel Roumeliotis, Laura Baldwin and Marie Manrique, all of whom are distinguished experts that are leading O'Reilly Media to success.
By making the communication, processing, and consumption of events part of the foundations of your application, you are incorporating what we refer to as event-driven architecture. Event-driven architecture is a fantastic new approach to application design as it fosters versatility by facilitating greater responsiveness. In this EM360 podcast, we speak to Jamil Ahmed. Jamil is an engineer at Solace who understands the ins and outs of event-driven architecture.
The majority of employees within your organisation likely aren't thinking about cybersecurity as their first priority. They each have their own individual roles, and taking on the responsibility of manoeuvering means taking on additional work when your time is already stretched. It's for this that the majority of businesses are looking at cybersecurity wrong; instead of it being viewed holistically, it is currently being seen as an add-on. In this episode of Ask the Expert, we talk to Kody Kinzie about how businesses are currently looking at cybersecurity wrong and how they can improve their approach in the upcoming years. Kody is a security researcher at Varonis and also the host of educational YouTube channels Hak5 and Null Byte.
https://www.linkedin.com/showcase/business-agility-/posts/?feedView=all (Staying agile) in the fast paced world of enterprise technology is only possible if you are implementing the most agile technology. Enterprise Resource Planning software, or ERP, has become one of the https://em360tech.com/podcasts/data-transforming-bus-series-2-ep2 (key components) of all enterprises in recent years. Despite its popularity, installing ERP comes with its challenges; most notably, employees are concerned about the implications of additional technical problems when installing ERP. Joining us on this episode of Ask the Expert is CEO at https://www.epicor.com/en-uk/offers/erp-selection-ebook/?utm_source=google&utm_medium=paidsearch&utm_term=epicor&utm_content=g-c&utm_campaign=7013x000002PLuP&gclid=Cj0KCQiAgomBBhDXARIsAFNyUqM2NH2WpJ7RqUEt8LG1hJLTAOzRV02uLhG0P9wCR1s5oR2HdVtOLJcaAoUDEALw_wcB (Epicor) https://www.linkedin.com/in/steve-murphy-epicor/ (Steve Murphy), who is here to tell us about the huge return on investment you will see when installing ERP software.
They say that data is the new oil, but being able to manage large quantities of data remains a challenge for many organisations in 2021. Anmut, a company that specialises in helping companies leverage the power of data, recently showed that only 34% of businesses currently manage data assets with the same discipline of other assets. The fact is that data is a tangible asset, but treating it as intangible only serves to restrict your business. Joining us in this podcast is Herman Heyns, CEO of Anmut, who will talk about Anmut's key findings concerning data management, the implications, and the solutions for businesses.
As cybersecurity technologies become stronger, so do the adversaries. Over the last decade, we have seen the rise of ransomware, petya and, most recently, typosquatting. Despite our best efforts to be meticulous when reading URLs, there is always a margin of error that could compromise the security and economy of your business. Joining us to tell us more is Jeremy Hendy; CEO at Skurio. In this podcast, he details the risks that typosquatting poses and the key to protecting your data.
As talks of the impact of business decisions on climate change become more prevalent, enterprise sustainability is beginning to rise closer and closer to the top of business leaders' list of priorities. Organisations are moving towards being more environmentally conscious, especially when it comes to lowering their carbon footprint, and big data is lending a hand. Joining us to tell us more is David Falconi, Founder at Kooling. In this podcast, he explains how big data can be used to achieve accurate carbon emissions measurement, before sharing some tips on what businesses can do to cut carbon emissions. Tune in to find out more!
Data-driven culture has long been a hot topic in the enterprise, but many organisations are only now catching on to the trend and its ever-growing list of advantages. Joining us to tell us more is Finn Wheatley, Director of Data Science at Whitehat Analytics. In this podcast, he gives us an overview of what it means to be data-driven, before sharing the multiple business benefits of the approach and the key steps to effectively embracing it. Tune in to find out more!
Entity resolution is a no-brainer for businesses today. By Quantexa's definition, entity resolution is “the ability to connect data wherever it is, regardless of quality to create a single, complete view.” Thus, it offers organisations a multitude of capabilities and efficiencies, namely by reducing false positives by 90% and finding related entities that traditional matching approaches cannot. Joining us to tell us more is Jamie Hutton, CTO at Quantexa. In this podcast, he gives us an overview of entity resolution, before sharing use cases and the shortfalls of traditional matching approaches. Tune in to find out more!
In this weeks episode our Editor in Chief Max Kurton spoke with Archana Vemulapalli, GM, Managed Infrastructure Services at IBM. In particular, she explores how the pandemic has heightened the need for digital transformation, before delving into how it compares across different industries. In a bonus question, Archana also shares leadership lessons that she learnt during her time as Chief Technology Officer for Washington, D.C. Tune in to find out more!
Traditional routes to financing are slowing and becoming more unpredictable. Simultaneously, they are slowly becoming eclipsed by corporate venture building, which is gaining recognition as a major driver of innovation and startup creation. Joining us to discuss corporate venture building in more depth is Felix Staeritz, Co-Founder and CEO at FoundersLane. In particular, Felix gives an overview of corporate venture building and what it brings to corporates and innovation. He also shares his predictions for the fate of traditional routes, before finally exploring the impact of COVID-19 on corporates, innovation, and corporate venture building itself.
In this week's Ask the Expert, we're delving into the current challenges and priorities facing CIOs today. Joining us to shed light on the matter is Andi Grabner, DevOps Activist at Dynatrace, who will be outlining the findings of Dynatrace's latest survey of 700 CIOs. As well as sharing the key findings of the survey, Andi advises on how CIOs can spend less on 'keeping the lights on'. What's more, he also explores whether automation is necessary for business processes today, before highlighting what he believes the main priority will be for CIOs moving forwards.
Business leaders are increasingly focusing on the need to forge relationships with machines. Simultaneously, they also need to consider how to recraft relationships with humans. Joining us to tell us more is Tony Judd, Managing Director UK and Ireland for Verizon Business. In particular, Tony describes the kind of relationships leaders need to work towards with machines and human employees. Furthermore, he shares his thoughts on the idea that 'humans will replace robots', before telling us what kind of human-robot split he expects to see in offices in 10 years' time.
When it comes to orchestrating their cybersecurity, businesses cannot afford to take shortcuts. Rather, it's crucial that companies get their protection and defences right, or suffer consequences such as financial loss and reputational damage. In light of this, we're being joined by Professor Avishai Wool, CTO and Co-Founder of AlgoSec, to discuss the security challenges around the complexity of enterprise networks. In particular, Avishai outlines the issues organise face when orchestrating their security, as well as the common mistakes made. Furthermore, Avishai demonstrates how to turn security into a strategic business asset and the areas in which caution should be exercised.
The uptake of cloud computing has increased significantly amid the pandemic. However, while cloud has dealt businesses a lifeline in enabling businesses to work remotely, companies need to consider the security implications that it comes with. Joining us to share his thoughts and advice is TJ (Tsion) Gonen, Head of Cloud Product Line at https://www.checkpoint.com/ (Check Point Software Technologies). In this podcast, TJ voices his concerns for cybersecurity post-COVID in particular relation to agility and the rapid increase of cloud adoption. He also delves into the advantages of multi-cloud security and lends his expertise on how best to approach cloud migration.
Since the start of the pandemic, keywords such as uncertainty and continuity have been dominating the business lexicon. As a result, most businesses have unsurprisingly been focusing more on survival than the new opportunities the crisis has presented. However, one opportunity not to be missed is to build an artificial intelligence-powered enterprise. In this week's Ask the Expert, https://www.linkedin.com/in/val%C3%A9rie-perhirin-1b399b8/ (Valerie Perhirin), Managing Director at https://www.capgemini.com/service/invent/ (Capgemini Invent), shares her thoughts on AI and automation's current acceleration. Tune in to find out her suggestions for becoming an AI-empowered enterprise and how to achieve efficient ROI on your AI investment.
The failure rate of bots has long been unremittingly high. However, Pegasystems is challenging the statistics by unveiling its new solution, which is the industry's first self-healing robotic process automation (RPA) capability. The offering, called X-ray Vision, is able to detect and fix broken bots with no human intervention, making for a very exciting development in the RPA arena. Here to tell us all about it is https://www.linkedin.com/in/franciscarden/ (Francis Carden), VP, Digital Automation and Robotic at https://www.pega.com/ (Pegasystems). Francis is joining us to give us an introduction to X-ray Vision, as well as to demonstrate the benefits self-healing RPA will bring to RPA users. Tune in to find out more!
In this week's Ask the Expert, we're delighted to welcome back Amanda Finch, CEO at the Chartered Institute of Information Security. As some of you may remember, Amanda last joined us to discuss the cybersecurity skills shortage and why cybersecurity education needs improving. This time, Amanda is joining us to walk us through the findings of the Chartered Institute of Information Security's annual professionals survey. In particular, the survey shone a spotlight on the diversity problems within the cybersecurity industry today. Furthermore, Amanda explored why more than half of IT security professionals had either left a job due to overwork or burnout, or worked with someone who did. Tune in to find out more!
The COVID-19 pandemic has disrupted plans and trajectories since it surfaced some months ago. The impact of the outbreak on business and entrepreneurship is widely varied. While some businesses and individuals thrived, others sadly failed. However, as we set our sights on a post-COVID era, innovation and entrepreneurship will have to find their feet again. In this week's Ask the Expert, Jon Hirschtick, President SaaS Business at https://www.ptc.com/en (PTC), shares more on the global trends in innovation and entrepreneurship. Tune in to find out his suggestions for empowering innovators post-COVID, and the support he recommends for entrepreneurs at this time, among other interesting discussion.
In this podcast, Dr. Galina Datskovsky, CEO at Vaporstream, talks to us about secure messaging platforms and why they have grown in importance amid the coronavirus pandemic. First, she explains the features a secure messaging platform must have to uphold privacy. Also, we look at privacy and security shortfalls associated with open-source solutions. Finally, Galina outlines the future of privacy in a post-pandemic world and what the future looks like for secure messaging platforms.
We're all familiar with the fear that robots may one day take over our jobs. However, it doesn't necessarily need to be on a one-in, one-out basis. Rather, the future of work needs to innovate and accommodate for the career-changing landscape. Joining us to share her ideas and research is Professor Giselle Rampersad, Professor in Innovation at the College of Science and Engineering, Flinders University. In particular, Giselle joined us to talk about a study she conducted that investigated how to drive innovation to help the future employment landscape. Tune in to find out about her research, including innovation gaps Giselle identified and the steps that can be taken to ensure newer students aren't left behind.
Lockdown may be loosening, but the UK is not out of the woods yet. As July draws to a close, the next few weeks are crucial to keeping a second wave at bay. However, as scientific knowledge grows in residual immunity to COVID-19, it also becomes more plausible to explore ways that individuals who tick the right boxes can go back to 'normal'. One way of doing so is through the use of immunity passports. We spoke to Roger Tyrzyk, Country Manager at IDnow, about the company's candidacy in creating these passports. Tune in to find out how IDnow’s identity verification technology makes immunity passports possible, as well as Roger's observations on digital behaviour in the pandemic and the increased demand for IDnow.
Uberisation is becoming an increasingly attractive business model for companies today. Not only does it directly benefit organisations, but it also is advantageous to IT contractors themselves. Joining us to delve further into the matter is Neil How, CEO and Co-Founder at ten80 Group. In this podcast, Neil introduces uberisation, before exploring the perks that it brings. Furthermore, Neil outlines considerations businesses should take into account when looking to uberise a project. Tune in to find out more!
Industries everywhere are embracing artificial intelligence (AI) to unlock new opportunities and address current challenges. The financial industry is no exception to the rule, but of course, comes with its own unique considerations. Joining us to delve further into the matter is Spencer Tuttle, VP EMEA at ThoughtSpot. In particular, Spencer shares the findings of ThoughtSpot's research into the investment of AI in the financial sector. He also explores how AI can unlock growth opportunities and reduce costs for organisations. Finally, he shares his hopes for the future of AI in the financial sector.
Innovation is high on the business agenda. Not only can it drive productivity and help businesses solve existing problems, but innovative thinking can also strengthen a company's competitive edge. However, despite innovation being a no-brainer, businesses musn't go in gung-ho; rather, they need to consider the investment that comes alongside it. Joining us to explore the matter is Arthur Shectman, Founder and President at Elephant Ventures. Arthur firstly delves into why organisations are seeing a decline in return on investment while trying to innovate. Then, Arthur outlines how data-driven technology can help with that innovation end result. Tune in to find out more!
Security orchestration, automation, and response, better known as SOAR, has quickly developed in the last five years. In particular, SOAR solutions help businesses speed up incident response by automating data gathering and security automation and providing case management and analytics. Joining us to tell us more about the current state of SOAR is Faiz Shuja, CEO at SIRP Labs. Faiz discusses how easy it is to deploy SOAR tools and which businesses are using them, before outlining examples of use cases of workflows SOAR enables that were once difficult to achieve.
Legacy systems are a well-known headache for organisations. This is reinforced in a recent report by Advanced which delved further into the challenges of legacy systems modernisation. Among its key findings, the 2020 Mainframe Modernization Business Barometer revealed that a staggering 74% of organisations have started a legacy system modernisation project but failed to complete it. Advanced's very own Brandon Edenfield, Managing Director of Application Modernisation, joins us in this Ask the Expert to share the report's key takeaways. Brandon also discusses reasons behind the high rates of failure and advises on how to improve the relationships between leadership teams and technical teams. Finally, Brandon shares his thoughts on the future of cloud implementation and legacy system modernisation.
Kubernetes is one of today's most popular orchestration tools. Hailed for its simplicity of use and its offerings in the cloud, Kubernetes has now firmly made its mark on the software arena. Joining us to discuss exactly how Kubernetes is revolutionising software is Rory Hanratty, Deputy CTO of Kainos, a digital services and platform provider. In this podcast, Rory explores why Kubernetes is needed. He also delves into the attitudes and costs surrounding Kubernetes and bridging the skills gap it comes with. Finally, Rory shares what he expects the Kubernetes landscape to look like in ten years’ time.
With an attack landscape so rife, it's imperative to narrow the cybersecurity skills gap. One way of doing so is by revamping workflows, as well as considering ways that juniors can benefit from their seniors guidance. Joining us to share his thoughts on the matter is Dan Cole, Senior Director of Product Management at ThreatConnect. In particular, Dan delves into the time constraints of training new recruits, before demonstrating how cybersecurity teams can switch up workflows to accommodate the gap and mitigate risks. Finally, Dan shares his recommendations for what juniors can do to take the edge off the skills gap.
Businesses today are feeling the pressure of stricter data governance laws. In light of this, we are now seeing more companies turn to their metadata for insights than ever. As in-house metadata models mature, now is a good time to dig deep into why metadata is so important. Joining us to share his thoughts on the matter is Steve Wood, Chief Product Officer at Boomi. Tune in to this episode to discover why metadata matters and how it ties into data privacy and machine learning.
Software-as-a-Service has been nothing short of a revolution. Since its beginnings, which admittedly left some of us scratching our heads (what is this?), the uptake has been so significant that it has paved the way for Everything-as-a-Service (XaaS). One area that has enjoyed a positive XaaS-driven impact is sales. Joining us to tell us more is Wendy Higley, Global Account Director at Upland Altify. Wendy is the perfect person to speak sales with; since joining Altify, she has achieved over 250% and 179% quota attainment and has been the company’s top performer. In this podcast, Wendy recaps customer revenue optimisation, before sharing her thoughts on what led to a surge of XaaS offerings. Wendy also delves into the impact of CRO software and XaaS on enterprise sales. Finally, we ask Wendy the million-dollar question: what is the secret to her success in sales?
Cloud collaboration tools have always had known advantages. However, the COVID-19 outbreak would see these tools shift from being a nice-to-have to being a lifeline for businesses. With more users than ever, organisations are at a heightened risk of human error, possibly compromising security. Joining us to share his thoughts on the matter is Matt Lock, who is Technical Director for the UK at Varonis. Tune in to find out the pros of cloud collaboration, the impact of human error, and how automation and audits could alleviate some of the burden.
In this week's Ask the Expert, we're welcoming back Ryan Weeks, CISO at Datto. If you missed it, Ryan joined us back in December 2019 to walks us through Datto’s fourth annual Global State of the Channel Ransomware Report. This time, he's delving into the findings of Datto's European State of the Channel Ransomware Report. Tune in to find out what Datto uncovered in their survey, including what they expected to find as well as what they didn't. Ryan also shares his expectations and hopes for companies in the future.
Historically, the odds have always been stacked in favour of cyber attackers. Malicious actors only need to succeed once, while cybersecurity professionals need to be succeeding 100% of the time. However, one approach that is turning all of that on its head is deception technology. This style of cyber defence enables businesses to play tricksters at their own game. Joining us to lend her expertise on the matter is Caroline Crandall, Chief Deception Officer at Attivo Networks. In this podcast, Caroline shares why she thinks deception technology has been slow in gaining traction. As well as this, she advises on how businesses can ensure their deception and decoy solution works.
Software-as-a-Service (SaaS) has skyrocketed in popularity, with much excitement surrounding the advantages it comes with. From lower costs to ease of use, SaaS brings a range of attractive benefits to the enterprise. However, in the rush to utilise it, security has become somewhat of an afterthought. Thus, how secure is SaaS and could it be the new Trojan horse? Joining us to lend his expertise on the matter is Kowsik Guruswamy, CTO at Menlo Security. As a multifaceted IT expert, Kowsik was the perfect guest to delve into SaaS-based threats and how to mitigate them. In particular, Kowsik introduces the findings of Menlo Security's research into SaaS and security, as well as expectations for the future.
As industries eagerly await the ubiquitous roll-out of 5G, fintech in particular is raring to go. The opportunities that the next generation of connectivity will bring to the field are many, paving the way for new and improved financial services. To get a clearer idea of fintech's 5G-driven future, and understand who the major players will be, we spoke with https://www.linkedin.com/in/wgenovese/ (Bill Genovese), Vice President Corporate Strategic Research and Planning Banking, Financial Markets at https://www.huawei.com/uk/ (Huawei). Tune in to hear Bill's expertise on the matter and what his predictions are for fintech in 10 years' time.
Blockchain is poised to be a top trend for 2020. As the technology gains traction, we spoke with Leanne Kemp, Founder and CEO at Everledger, about the ethical, transparency, and trust considerations that blockchain comes with. Leanne lends her unrivalled expertise that she applies every day at her company, which she founded to better verify the diamond industry. In this podcast, Leanne outlines the sustainability and ethical shortfalls often encountered in luxury goods supply chains. She also delves into how blockchain can alleviate these shortfalls, before detailing how it can contribute to a circular economy. Finally, Leanne shares her thoughts on the future of supply chains.
In this podcast, Matthew lends his expertise to explore the growth of data and how to action it effectively with the findings of a MarketPulse survey by IDG research and Matillion. Tune in to hear Matthew’s advice on gaining actionable insights and his predictions for the future of data warehousing. https://www.linkedin.com/in/matthewscullion/ (Matthew Scullion) is the Founder and CEO at Matillion. Matthew has a demonstrable history working in commercial IT and software development at a number of British and European system integrators. He then started Matillion in 2011 and has since expanded the company, opening offices in the USA.
In this podcast, Nanjunda explains why legacy systems are the Achilles heel of digital transformation. In particular, he explains why businesses are stuck in a legacy rut, and how low code can get them out of it. Finally, Nanjunda shares his thoughts on the future of legacy systems and digital transformation. https://www.linkedin.com/in/nanjunda-prasad-ramesh-1a5aa516/ (Nanjunda Prasad) is the Director of Marketing at https://wavemakerglobal.com/ (WaveMaker). Nanjunda has over 10 years of experience in product development, as well as a demonstrable history of delivering critical components of a new product ahead of market introduction.
In this podcast, Stephan delves into the many ways that cloud drives digital transformation. As well as this, he outlines the obstacles associated with cloud, before sharing his advice on how to overcome them. Stephan also lends his OpenStack expertise and discusses whether he thinks open source is the future of technology. https://www.linkedin.com/in/stephanfabel/ (Stephan Fabel) is the Director of Product at https://canonical.com/ (Canonical). Stephan has over 15 years of experience in product management, technical cloud architecture, software development, and product development. During this time, Stephan has built a reputation for unwavering commitment to excellence.
In this podcast, Paul outlines what ‘connected worker’ really means and why this style of working is on the rise. As well as this, he lends his expertise on how to implement the right communications technologies for your teams. Finally, Paul shares his thoughts on what the enterprise will look like in 10 years’ time. https://www.linkedin.com/in/paulnclark/ (Paul Clark) is the Senior Vice President, EMEA Managing Director at https://www.poly.com/gb/en (Poly). Paul has worked at Poly since it was Plantronics in the 90s (it would later merge with Polycom). At the company, Paul is responsible for the combined entity in EMEA and for growing the overall revenues in this region.
In this podcast, we spoke with Grace Fisher, Senior Product Manager at Persado, about her journey to becoming a woman in tech. As well as this, Grace shares her thoughts on what organisations and schools could be doing to encourage women to take STEM subjects and career paths. Finally, Grace gives some kind words of advice to women who would like to work in the tech industry.
EachforEqual is the mantra for this year’s International Women’s Day. This is especially appropriate for the tech industry, which has historically been dominated by men. However, many organisations have taken great strides to offer equal opportunities to women in the tech arena. Now more than ever, women are filling positions all the way up to C-level.
https://www.linkedin.com/in/simon-hayward-b3a51b/ (Simon Hayward), Vice President EMEA at https://www.domo.com/ (Domo), joins us for this week’s Ask the Expert. At Domo, he helps customers realise the power of data in driving their organisations forward. Simon is particularly knowledgeable in how best to leverage data when running a complex, fast-paced business, making him the perfect person to speak with us about how data fragmentation is impeding the digital transformation efforts of organisations. Tune in to find out what Domo (in partnership with IDC) discovered in its poll, surveying the barriers met by UK and European organisations when introducing digital tools and practices to improve decision-making. Simon also explores how data fragmentation hinders digital transformation efforts, before lending his expertise on overcoming these obstacles.
In this podcast, Shashi firstly explores the trends associated with SD-WAN and the hype around it. He also outlines what organisations should look for in a Network-as-a-Service vendor, before delving into whether organisations should choose an as-a-Service approach or DIY. https://www.linkedin.com/in/skiran/ (Shashi Kiran) is the Chief Marketing and Product Officer at https://www.aryaka.com/ (Aryaka Networks). Shashi has over 20 years of experience in business and technology, spanning areas such as sales, business development, and product management in large global companies as well as smaller startups.
In this podcast, Peter details the shortfalls of Internet of Things (IoT) and what that means for its future applications. He also delves into the impact of 5G on IoT, before addressing data hoarding in business. Finally, Peter demonstrates how to unlock untapped value from data and how to better monetise it. https://www.linkedin.com/in/peter-ruffley-3922927/ (Peter Ruffley) is the Founder at https://www.zizo.co.uk/ (Zizo Software). Peter has over 40 years of broad experience in the IT industry, including working with some of the biggest data technologies such as Oracle and IBM. At Zizo, Peter has brought the company to the forefront as one of the leading providers of big data analytics for business and retail.
Tom is joining us to explore why companies spend so much focus, manpower, and cash on recruitment, yet much less to retain talent. He delves into how technology can help in both recruitment and retention, paying particular attention to AI-driven analytics. https://www.linkedin.com/in/tommmckeown/ (Tom McKeown) is the CEO and Co-Founder at https://www.trendata.com/ (TrenData). Tom is a senior executive with over 25 years of experience in software and technology. During his career, Tom had spearheaded growth in several early- and middle-stage startup software companies, resulting in acquisitions with multi-million dollar returns for investors.
Joining us in this Ask the Expert is Deloitte’s David Mapgaonkar and Michael Wyatt. David is a principal with Deloitte Cyber practice, and Michael is the Deloitte Risk and Financial Advisory principal for the CyberDeloitte. In this podcast, David and Michael firstly outline the findings of Deloitte Cyber’s research. In particular, the research explored the top trends and challenges that enterprises must consider to protect themselves and their consumers. As well as this, they detail the hesitations surrounding upgrading legacy environments and how companies should approach their digital identity. Finally, David and Michael share their thoughts on what 2020 will bring.
In this podcast, Joseph discusses whether the c-suite should be solely accountable for data breaches. As well as this, he outlines which areas of security organisations should focus on more, rather than cut back on. Then, he lends his expertise on conversing with IT professionals to implement proactive measures and appropriate budgets, before sharing his thoughts for the future. https://www.linkedin.com/in/josephcarson/ (Joseph Carson) is the Chief Security Scientist at https://thycotic.com/ (Thycotic). Joseph has over 25 years of experience in enterprise security and infrastructure and is also an adviser to several governments and cybersecurity conferences.
In this podcast, Gregory discusses the role of corporate leadership in cybersecurity. Firstly, he explores why cybersecurity has crept into the corporate priority list. Gregory also demonstrates how leadership can learn more and involve themselves better. Finally, Gregory shares his predictions for how the boardroom and their responsibilities might change. https://www.linkedin.com/in/gregory-a-garrett-9686175a/ (Gregory Garrett) is the Head of International Cybersecurity at https://www.bdo.com/ (BDO),. Gregory is an IT and cybersecurity industry leader, as well as a best-selling author, with 23 business books in his portfolio. Furthermore, he has done business in over 50 countries and managed over $40 billion-worth of P&L.
In this podcast, John shares his thoughts on public key infrastructure and IoT security. Firstly, John gives a roundup of key security trends in 2019, before sharing his predictions for 2020. Then, he delves into the security considerations surrounding IoT specifically. John also lends his expertise on navigating IoT security ahead of the ever-growing number of IoT-driven devices. https://www.linkedin.com/in/johngrimm/ (John Grimm) is the VP of Strategy & Business Development at https://www.nciphersecurity.co.uk/ (nCipher Security). nCipher Security is a leading company in the general purpose hardware security module market. As a senior strategy and marketing professional with a strong cybersecurity background, John brings his unique blend of early career technical background in firmware engineering and product management to his role.
In this podcast, James firstly gives a recap of the most prominent threats in 2019. Then, he delves into ‘good bots’ and ‘bad bots’ and their impact across industries. Finally, James addresses concerns that come with artificial intelligence-driven solutions, before sharing his predictions for 2020. https://www.linkedin.com/in/james-maude-3aaa0649/ (James Maude) is the Head of Threat Research at https://www.netacea.com/ (Netacea), a company that offers machine-learning powered intent analytics. James is a security professional with particular experience as an innovator within cybersecurity products. Today, James is also a regular presenter at international events and provides media commentary on threat and defence strategies.
In this podcast, Daniel walks us through the challenges organisations face with data privacy in an M&A transaction. Also, the considerations regarding post-deal privacy. Finally, Daniel explains how organisations can benefit from having an effective data inventory and how to achieve this. https://www.linkedin.com/in/daniel-barber/ (Daniel Barber) is the CEO and co-founder at https://datagrail.io/ (DataGrail). The only purpose built platform of its kind with live data mapping technology and over 150 enterprise integrations with Oracle, Salesforce, Amazon and others, helping companies achieve and maintain compliance with even the newest data privacy laws.
In this podcast, Akhil walks us through the different purposes of virtual agents and digital colleagues in organisations. He then explains the technology behind this, how it can help cut back on costs and complexity, and what the future of digital colleagues looks like. https://www.linkedin.com/in/akhilsahai/ (Dr Akhil Sahai) is the Chief Product Officer at https://www.symphonysummit.com/ (Symphony SummitAI). SummitAI is a leader in AI-driven IT service management that is a part of SymphonyAI. The one billion dollar investment fund committed to building the next generation of artificial intelligence and machine learning applications across multiple verticals.
In this episode, Theo delves into the anti-futurist role, the current state of AI and its direction, and the importance of good data. Firstly, he discusses the importance of the futurist mindset and keeping people grounded with all the new technologies out there. Then, he shares his views on the current approach to artificial intelligence (AI) in the enterprise. As well as this, he gives an overview of how AI is marketed towards consumers. Theo also explores algorithm bias, before sharing his thoughts on the future. Theo is recognised globally as an influential voice, particularly in the emerging technologies arena, Theo is an in-demand keynote and TEDx speaker. He has also held senior positions at large, global enterprise software companies and served as a mentor at start-up accelerators. For information regarding your data privacy, visit https://www.acast.com/privacy (acast.com/privacy)
This week’s Ask the Expert is with Marc Vanmaele, CEO of TrustBuilder. TrustBuilder provides state-of-the-art identity and access management solutions with an agile approach. With a wealth of knowledge in security solutions, Marc also specialises in business development, internet marketing, and identity and access management. The Status Quo and Future of Cybersecurity In today’s episode, Marc outlines the current state of cybersecurity and the threats he predicts will surface. He also elaborates on the challenges he has encountered during his career in the industry. In light of these challenges, Marc then expands on the safety of today’s companies. Finally, Marc shares his thoughts on how he thinks cybersecurity will evolve over the next five years. For information regarding your data privacy, visit https://www.acast.com/privacy (acast.com/privacy)
This week’s Ask the Expert is with David Liu, who is Founder and CEO at Deltapath. Deltapath is a leading unified communications technology company driving business collaboration. In his role, David oversees the company’s vision, strategy, and growth. As well as this, David is responsible for spearheading their technical strategy. What’s more, David led the development of the company’s SIP-based telephone system. In this podcast, David lends his expertise to outline trends in the workforce. Specifically, he explores the different generations, their skill sets, and their different needs. Further to this, David delves into the specifics of attracting and retaining millennials. Finally, David discusses whether saving time actually means saving money. For information regarding your data privacy, visit https://www.acast.com/privacy (acast.com/privacy)
We recently attended https://whitehallmedia.co.uk/bdajun2019/ (Big Data Analytics) (BDA) 2019, hosted by https://whitehallmedia.co.uk/ (Whitehall Media), which brought together people in the data field to define the current climate and explore innovations for enterprise organisations. Attendees of the cross-industry conference included CEOs, key decision-makers, analysts, senior IT professionals, and more. Between the various seminars and networking opportunities, we spoke with a number of industry experts about why big data is better data.
In this podcast, Sarah talks about removing the confusion around the buzzwords relating to AI. Also, how AI is increasing accuracy in the medical field and changing British agriculture. Dr Sarah-Jayne Gratton is a technology influencer and futurist, specialising in emerging technologies and covering trends in artificial intelligence, machine learning and augmented reality. Removing the Confusion Around AI Buzzwords
In this podcast, Jim offers some invaluable insights from climate change to the future of technology. He also poses an important question relating to the sustainability of exponential technologies. Jim Harris is an international bestselling author and Disruptive Innovation thought leader. His work in disruptive technologies is evidently crucial to raising awareness of key global issues.
In this podcast, Tristan discusses the dangers users face of not understanding how their data is collected and used. Also, what Qwant means for the future of search engines. Lastly, the importance of having open source software as a prominent focus in the tech industry. Tristan Nitot is the Vice President Advocacy at Qwant. Tristan is an Open Source executive specializing in Internet-related technologies, community building and Open-Source Marketing.
In this podcast, Rajarshi explains how to battle against hackers who are constantly changing and evolving their tactics. Also, how a new focus needs implementing to make consumer IoT devices more secure. Rajarshi Gupta is the Head of AI at Avast Security. Rajarshi is a pioneer in AI, cybersecurity and networking, with 15 years of technical leadership and executive experience.