What is Schema for AI?
Schema for AI is the practice of deploying Schema.org structured data (JSON-LD) with the specific intent of improving an LLM's ability to parse, attribute, and cite a page — not just to earn Google rich results. The high-leverage types in 2026 are DefinedTerm (glossary pages), FAQPage (questions answer engines lift verbatim), Article with full author/publisher graphs (provenance LLMs trust), Speakable (extraction cues for voice and answer engines), Quotation (attributed pull-quotes the model can lift cleanly), and Person/Organization (entity disambiguation). Schema for AI is one of the few GEO levers a brand fully controls — earned media takes months, but a clean schema deployment ships in a week and immediately raises retrieval accuracy. Crackle PR ships DefinedTerm, FAQPage, Article, Speakable, Quotation, Person, and Organization schema on every client authority surface — schema for AI is one of the few GEO levers a brand fully controls, and it ships in a week instead of a quarter.
“Schema for AI is the cheapest GEO lever in the stack. You can't outspend Bloomberg on earned media this quarter — but you can out-structure them by Friday.”
Related terms
Schema.org Structured Data
JSON-LD markup that tells search engines and AI exactly what your content is about.
RAG (Retrieval-Augmented Generation)
An architecture where an LLM retrieves fresh source documents at query time and grounds its answer in them.
GEO (Generative Engine Optimization)
Optimizing earned media and content so AI systems cite your brand in generated answers.
AI Source Ranking
The implicit ranking LLMs apply when selecting which retrieved sources to cite in an answer.
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