Schema alone does not move the needle.
Farhad Divecha
The AI search question for businesses is no longer only whether they can be found. It is whether AI systems understand, describe and verify them accurately before users ever reach their websites.
Farhad Divecha brings a technical marketing and data-led perspective to that problem. As Group CEO of Accuracast, he has more than 20 years of experience in digital, with specialisms across digital strategy, data-led marketing, measurement and international growth.
In this exclusive interview, Farhad discusses why AI search visibility is becoming a public information problem for businesses, what Accuracast’s research across ChatGPT, Google AI Overviews, and Perplexity revealed about the limits of schema markup, and why IT leaders need to audit authority, expertise, and trust signals as carefully as they audit crawlability.
Q. Why is AI search visibility becoming an information accuracy problem for businesses?Users are increasingly reliant on AI for answers and don’t verify information by visiting the website, so discovery is dependent not only on whether you’re listed on AI, but also on accuracy.
That changes the problem for businesses.
In legacy search, users saw results, clicked through to the website, and consumed information at source. With AI search, the answer is formed before that visit happens.
The issue is not only limited to whether a business appears. But it is also whether AI systems understand the business correctly, use the right sources, and give users accurate, up-to-date information.
If that information is wrong or incomplete, the business may not see the damage in website analytics. The user may have already made a judgment before reaching the company’s website.
That is why AI search visibility is becoming a public information problem, not just an SEO issue.
Q. Accuracast analyzed 9,000 citation sources across ChatGPT, Google AI Overviews and Perplexity. What did that reveal about the limits of schema markup?We analysed 9,000 citation sources to see how schema influenced brand mentions on AI answers. The data show that schema helps LLMs distinguish structured data on websites where it isn’t clear, but for most modern websites that are already well-structured, this isn’t a major problem, and LLMs can understand them with or without schema. The main take-away is that schema alone does not move the needle.
It is still useful technical work.
If a website is unclear, schema can help define what the information relates to. It can help systems identify products, organizations, authors, reviews, and other structured elements with greater confidence.
But it should not be treated as the whole answer.
For many businesses, the bigger question is whether the organization and its employees are credible enough to be cited. Schema can help explain the page, but it does not create authority or trustworthiness.
Structured data can support AI visibility, but it cannot replace evidence, expertise, and trust, which matter far more for AI search visibility.
Q. What should IT leaders audit before assuming AI systems cannot crawl or understand their website?Start by benchmarking and understanding if there is really a problem with crawling and semantic indexing; often we find that’s not the problem.
The bigger problem tends to be establishing authority and expertise.
So, IT leaders need to ensure content throughout the site declares expert authors and their credentials. IT leaders need to ensure there is functionality on the website that enables AI systems to identify authors & their expertise, as well as the authority and trustworthiness of the business too – e.g. through placement of trust marks.
That means the audit should look beyond basic crawlability.
A site may be technically accessible and still fail to show why its people, content and business claims should be trusted. Expert authors, visible credentials and clear trust marks all help AI systems connect information to credible sources.
The key is to separate two questions.
Too many businesses focus on the first question and miss the second.
About Farhad DivechaKnown as a technical marketing expert, Farhad Divecha examines how search, structured data, and AI-generated answers shape how businesses are discovered, described, and verified online. As Group CEO of Accuracast, an international digital marketing agency, he brings more than 20 years of digital experience, with specialisms in digital strategy, measurement, data-driven marketing, technical SEO, and growth analytics. His work focuses on the practical decisions business and technology leaders face when visibility depends not only on being found, but on whether AI systems can accurately understand, trust and cite the organization.
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Originally Published on Martech Zone: AI Search is Turning Business Visibility Into an Information Accuracy Problem