Structured Data for AI

Definition

Structured data for AI extends the traditional SEO use of Schema.org markup to specifically target AI model comprehension. While structured data was originally designed to help search engines display rich results, it now serves a dual purpose: helping AI models understand what your content is about and how to accurately represent it in generated responses.

Key schema types for AI optimization include: Article (authorship and publication metadata), FAQPage (question-answer pairs that AI can directly extract), HowTo (step-by-step processes), DefinedTerm (glossary definitions), and Organization (brand identity and authority signals).

Why It Matters

AI models use multiple signals to understand web content, and structured data is one of the most reliable. A page with proper JSON-LD gives AI systems explicit, machine-readable information about entities, relationships, and content types. This reduces the risk of hallucination and misattribution.

The DefinedTerm schema type is particularly underused. Almost none of the major SEO tools use it for their glossaries, despite it being the most semantically appropriate markup for term definitions. Implementing it gives AI models a clear signal that your page is a definitive reference for a specific term.

How Acta AI Handles This

Examples

A glossary page uses DefinedTerm schema:

{
  "@context": "https://schema.org",
  "@type": "DefinedTerm",
  "name": "Generative Engine Optimization",
  "description": "The practice of optimizing content for AI search engines.",
  "url": "https://withacta.com/glossary/generative-engine-optimization",
  "inDefinedTermSet": {
    "@type": "DefinedTermSet",
    "name": "SEO & GEO Glossary",
    "@id": "https://withacta.com/glossary"
  }
}

This tells AI models explicitly that this page is the definitive definition of "Generative Engine Optimization" within a broader glossary set.