Structured data is machine-readable metadata embedded in web pages that explicitly declares what a page is about, what type of content it contains, who published it, and how its elements relate to one another. Where natural language text requires an AI to interpret meaning, structured data provides direct, unambiguous declarations that AI systems can process reliably without inference.
The Schema.org Standard
Schema.org is the global vocabulary for structured data on the web, developed and maintained collaboratively by Google, Microsoft, Yahoo, and Yandex. It defines over 800 types of entities — Article, Organization, FAQPage, Product, Event, Person, and hundreds more — with standardized properties for each. A page that declares itself as an Article with a specific author, publisher, datePublished, and topic is providing the same information in a format every major AI and search system can read the same way.
How AI Systems Use Structured Data
AI search systems use structured data at two levels. First, for content classification: knowing that a page is an Article vs. a Product page vs. a FAQPage changes how the AI processes and potentially cites the content. Second, for entity resolution: an Organization schema that declares a company's legal name, address, and service type allows AI systems to recognize that company as a specific entity in their knowledge representation — making it easier to associate the company's content with relevant queries.
The Most Important Schema Types for AI Visibility
For AI search citation, the highest-impact schema types are FAQPage (enables direct Q&A extraction), Article (establishes content authority and publication metadata), Organization (defines the publishing entity), and HowTo (for instructional content). All should be implemented as JSON-LD in the page head. The Omni structured data implementation service deploys all of these on every relevant page type.