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What is Schema.org for AI? Definition and business implications
Schema.org is a standard structured semantic markup vocabulary (most often JSON-LD) that AI engines use to understand the nature of a web page: defined term, FAQ, article, product, event. Properly implemented, it multiplies by two to four the probability of being cited by generative answer engines.
Schema.org is a joint initiative by Google, Microsoft, Yahoo, and Yandex launched in 2011 to standardise semantic markup of web pages. The vocabulary today counts more than 800 distinct types. Five types are particularly useful for GEO. DefinedTerm and DefinedTermSet: for glossaries, indicate to engines that the page defines a term. FAQPage: for question-answer pages, makes Q/A pairs direct candidates for citation. HowTo: for practical guides, allows step-by-step citation. Article and NewsArticle: for editorial content, signal author, date, publishing organisation. Organization and Person: to identify entities and feed the knowledge graph. The dominant format in 2026 is JSON-LD embedded in the HTML script tag, simpler to maintain than microdata or RDFa alternatives.
Concrete example
A B2B media platform publishes about 40 new articles per month. Before systematic Schema.org markup: near-zero presence in AI Overviews and Perplexity. After implementing an editorial pipeline integrating JSON-LD Article + Person (author) + Organization markup: each article is automatically marked up at publication, end-of-article FAQs receive a FAQPage, guides receive a HowTo. Six months later: 31 citations identified in Google AI Overviews, 12 in Perplexity, 8 in Claude.ai. The initial pipeline deployment cost was 8 developer-days, with no recurring editorial production overcost.
See also
Further reading
Sources
- Schema.org official documentation, DefinedTerm, FAQPage, HowTo, Article specifications, 2026. https://schema.org/
- Schema Markup Validator, official validation tool, 2026. https://validator.schema.org/