AI’s Next Move: Private Cloud & Edge Computing In this episode, Sugata Sanyal speaks with Vineet Sharma, Global Alliances & Ecosystems Lead at Cloudera, about the transformative role of AI in private cloud and edge computing. As businesses rethink their partner relationship management (PRM) strategies, they are shifting workloads to private cloud for cost, compliance, and security advantages. Vineet shares insights into emerging AI trends, the evolution of PRM, and the impact of edge computing. This discussion explores how enterprises are adapting their partner networks for AI-driven growth and operational efficiency. Listen to gain insight into the next wave of AI infrastructure and PRM advancements. Related Guidebook Hybrid Cloud and Edge AI Computing Impacting the Future of PRMHow AI, Hybrid Cloud, and Edge Computing Are Transforming Partner Relationship Management Download your COMPLIMENTARY COPY of Hybrid Cloud and Edge AI Computing Impacting the Future of PRM Best Practices Guidebook. How AI, Hybrid Cloud, and Edge Computing Are Transforming Partner Relationship Management.Download for FREE Video Podcast: AI’s Next Move: Private Cloud & Edge Computing ✔ Chapter 1: The Rise of AI in Private Cloud & Edge Computing The rapid evolution of AI and cloud computing has transformed the way enterprises manage their partner ecosystems. While public cloud has dominated AI workloads, businesses are now reconsidering private cloud and edge computing due to increasing data security concerns, compliance regulations, and cost management. Many companies initially moved AI workloads to public cloud providers like AWS, Azure, and Google Cloud, only to realize the high operational costs and governance challenges associated with these environments. As a result, organizations are now embracing hybrid and private cloud infrastructures that allow them to maintain greater control over data while optimizing costs. The shift toward private cloud and edge computing is being driven by industries that require real-time AI processing, low-latency decision-making, and strict compliance requirements. Sectors like banking, healthcare, and government agencies are particularly focused on keeping data within secured environments to ensure regulatory compliance. This shift has forced enterprises to rethink their partner relationship management (PRM) strategies, as partners play a key role in integrating and optimizing AI workloads across hybrid cloud environments. Additionally, the rise of edge computing is pushing AI processing closer to where data is generated. Retailers, manufacturers, and telecommunications providers are leveraging edge AI to process data locally, reducing the need for constant cloud connectivity. This trend allows businesses to reduce latency, enhance real-time decision-making, and optimize network bandwidth usage, making partner collaboration more crucial than ever in AI adoption. ✔ Chapter 2: The Evolution of Partner Relationship Management (PRM) in AI As AI adoption accelerates, PRM platforms are evolving to support more complex and dynamic partner ecosystems. Unlike traditional PRM models that primarily focused on deal registration and partner incentives, today’s AI-driven PRM strategies incorporate predictive analytics, automation, and AI-powered insights to enhance partner engagement and productivity. Enterprises are leveraging AI to automate partner onboarding, personalize training content, and optimize co-marketing campaigns, ensuring that partners can quickly become productive in selling and deploying AI solutions. One of the biggest transformations in AI-powered PRM is the ability to provide real-time partner insights and performance track...