Structured Data for AI

Structured data provides explicit, machine-readable information about your content. While AI can infer meaning from text, structured data removes ambiguity and ensures accuracy.

In this guide

Schema.org basics for AI visibility
Essential schema types for businesses
JSON-LD implementation patterns
Testing and validation

15 min read Prerequisite: Semantic HTML

Why Structured Data Matters for AI

AI systems can read and understand your content, but structured data provides verified facts they can cite with confidence:

Without Structured Data

"The page mentions $29 somewhere. Is that the price? A discount? Something else?"

With Structured Data

"The product price is explicitly $29/month with a 14-day free trial."

Essential Schema Types

Organization

Define your company as a recognized entity:

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Acme Corp",
  "url": "https://acme.com",
  "logo": "https://acme.com/logo.png",
  "foundingDate": "2019",
  "address": {
    "@type": "PostalAddress",
    "addressLocality": "Austin",
    "addressRegion": "TX"
  },
  "sameAs": [
    "https://twitter.com/acme",
    "https://linkedin.com/company/acme"
  ]
}

Product / SoftwareApplication

Define your products with clear attributes:

{
  "@context": "https://schema.org",
  "@type": "SoftwareApplication",
  "name": "Acme CRM",
  "applicationCategory": "BusinessApplication",
  "operatingSystem": "Web",
  "offers": {
    "@type": "Offer",
    "price": "29",
    "priceCurrency": "USD",
    "priceValidUntil": "2025-12-31"
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.5",
    "reviewCount": "127"
  }
}

FAQPage

Perfect for Q&A content AI can directly cite:

{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [{
    "@type": "Question",
    "name": "What is Acme CRM?",
    "acceptedAnswer": {
      "@type": "Answer",
      "text": "Acme CRM is a customer relationship management platform designed for small B2B sales teams."
    }
  }]
}

Article / BlogPosting

For content pages with authorship and dates:

{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Guide to CRM Selection",
  "author": {
    "@type": "Person",
    "name": "Jane Smith"
  },
  "datePublished": "2025-01-15",
  "dateModified": "2025-01-20",
  "publisher": {
    "@type": "Organization",
    "name": "Acme Corp"
  }
}

Implementation

Add structured data as JSON-LD in your page's <head> section:

<head>
  <script type="application/ld+json">
  {
    "@context": "https://schema.org",
    "@type": "Organization",
    "name": "Your Company",
    ...
  }
  </script>
</head>

Testing Structured Data

Google Rich Results Test

Test your structured data at search.google.com/test/rich-results

Schema.org Validator

Validate against the schema spec at validator.schema.org

Key Takeaway

Structured data = verified facts.

While AI can infer information from text, structured data provides explicit, unambiguous facts. Start with Organization and Product schemas, then expand to FAQPage and Article for content.

Sources

Getting Started with Schema.org: Official structured data documentation
Introduction to Structured Data | Google: Google's structured data guidelines
JSON-LD Specification: W3C standard for linked data in JSON