What is Structured Data for AI?
Structured data for AI is schema.org markup, JSON-LD and clean semantic HTML that makes facts on a page unambiguous and machine-parseable, so both search crawlers and LLM retrieval systems can extract and cite them accurately.
Schema.org structured data — Organization, Product, FAQPage, HowTo, Article, BreadcrumbList and similar JSON-LD blocks — was built for search engines but turns out to matter just as much for GEO, for a simple reason: LLMs and retrieval pipelines still have to parse a page to use it, and clearly labeled, unambiguous facts (a price, a step number, a Q&A pair) are far less likely to be misread or hallucinated than the same facts buried in marketing prose.
FAQPage and HowTo schema in particular translate almost one-to-one into the kind of clean question-and-answer or step-by-step format an AI answer engine likes to lift directly into a generated response. Organization and Product schema help disambiguate a brand from similarly-named competitors, which matters when a model is deciding what your pricing or category actually is.
Structured data doesn't guarantee a citation — the underlying facts still have to be accurate, current and genuinely useful — but it removes a whole class of avoidable failure: a model quoting the wrong price, confusing two products, or skipping a page entirely because its actual content was too hard to parse out of decorative HTML.