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Why Structured Data for AI?

AI systems process millions of web pages to understand entities and relationships. Without structured data, they must infer this information from unstructured text—a process prone to errors and uncertainty.

When you implement Schema.org markup correctly, you're giving AI systems a direct, machine-readable declaration of:

Identity

Who you are as an entity (person or organization)

Credentials

Verifiable expertise and qualifications

Relationships

Connections to other known entities

Content Attribution

Who created what and when

Important: AI Systems Cross-Reference

Modern AI systems don't just read your structured data—they verify it by cross-referencing with external sources. Your Schema.org claims should match what can be found on LinkedIn, Crunchbase, Wikipedia, and other authoritative platforms.

Organization Schema

The Organization schema is your foundation. It establishes your company as a recognized entity that AI can reference and verify. Key elements include:

@idA unique identifier URL that other schemas can reference

sameAsLinks to your presence on other platforms (LinkedIn, Twitter, Crunchbase, Wikipedia)

descriptionUse the exact same description across all platforms for consistency

foundingDateEstablishes longevity and credibility

Organization Schema Example

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://www.yoursite.com/#organization",
  "name": "Your Company Name",
  "url": "https://www.yoursite.com",
  "logo": {
    "@type": "ImageObject",
    "url": "https://www.yoursite.com/logo.png"
  },
  "description": "A clear, consistent description of what your company does.",
  "foundingDate": "2020",
  "founder": {
    "@type": "Person",
    "name": "Founder Name"
  },
  "sameAs": [
    "https://twitter.com/yourcompany",
    "https://linkedin.com/company/yourcompany",
    "https://www.crunchbase.com/organization/yourcompany",
    "https://en.wikipedia.org/wiki/Your_Company"
  ],
  "contactPoint": {
    "@type": "ContactPoint",
    "email": "contact@yoursite.com",
    "contactType": "customer service"
  }
}

Person Schema for Authors

Every content author should have a Person schema that establishes their expertise. This is crucial for E-E-A-T signals. AI systems use this to verify that your authors are real people with verifiable credentials.

The Verification Loop: When AI encounters an author name, it attempts to verify the person exists by checking sameAs links. If your author's LinkedIn profile matches their bio on your site, confidence increases dramatically.

Person Schema Example

{
  "@context": "https://schema.org",
  "@type": "Person",
  "@id": "https://www.yoursite.com/team/jane-doe#person",
  "name": "Jane Doe",
  "jobTitle": "Chief Technology Officer",
  "worksFor": {
    "@id": "https://www.yoursite.com/#organization"
  },
  "alumniOf": {
    "@type": "CollegeOrUniversity",
    "name": "Stanford University"
  },
  "knowsAbout": [
    "Machine Learning",
    "Data Science",
    "Software Architecture"
  ],
  "sameAs": [
    "https://linkedin.com/in/janedoe",
    "https://twitter.com/janedoe",
    "https://orcid.org/0000-0000-0000-0000"
  ]
}

Key Person Schema Fields for AI

knowsAbout: List specific areas of expertise (helps AI match content to author)
sameAs: Include LinkedIn, ORCID, Twitter, personal site URLs
alumniOf: Educational credentials AI can verify
worksFor: Reference your Organization schema with @id
jobTitle: Professional role that establishes authority

Article Schema

Article schema connects your content to its author and publisher, establishing the chain of trust that AI needs to cite confidently. Critical for blog posts, guides, and any content you want AI to reference.

Article Schema Example

{
  "@context": "https://schema.org",
  "@type": "Article",
  "headline": "Your Article Title",
  "description": "A clear summary of the article content.",
  "author": {
    "@id": "https://www.yoursite.com/team/jane-doe#person"
  },
  "publisher": {
    "@id": "https://www.yoursite.com/#organization"
  },
  "datePublished": "2025-01-15",
  "dateModified": "2025-01-15",
  "mainEntityOfPage": {
    "@type": "WebPage",
    "@id": "https://www.yoursite.com/blog/article-slug"
  },
  "image": {
    "@type": "ImageObject",
    "url": "https://www.yoursite.com/images/article-image.jpg"
  },
  "citation": [
    {
      "@type": "CreativeWork",
      "name": "Source Document Title",
      "url": "https://authoritative-source.com/document"
    }
  ]
}

Required Fields

• headline
• author (reference Person schema)
• publisher (reference Organization)
• datePublished
• dateModified

AI-Boosting Fields

• citation (sources you reference)
• about (topic entities)
• mentions (entities discussed)
• speakable (for voice assistants)
• isAccessibleForFree

Product Schema

If you offer products or services, Product schema helps AI understand and recommend them. Reviews and ratings are particularly important—they provide the social proof AI uses to make recommendations.

Product Schema Example

{
  "@context": "https://schema.org",
  "@type": "Product",
  "name": "Your Product Name",
  "description": "What your product does and who it's for.",
  "brand": {
    "@id": "https://www.yoursite.com/#organization"
  },
  "offers": {
    "@type": "Offer",
    "price": "99.00",
    "priceCurrency": "USD"
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.8",
    "reviewCount": "150"
  },
  "review": [
    {
      "@type": "Review",
      "author": {
        "@type": "Person",
        "name": "Customer Name"
      },
      "reviewRating": {
        "@type": "Rating",
        "ratingValue": "5"
      },
      "reviewBody": "Detailed review content..."
    }
  ]
}

Connecting Entities with @id

The @id attribute is how you build a connected knowledge graph. Instead of duplicating information, you reference entities by their unique identifier.

Entity Reference Pattern

Define entity once:

"@id": "https://yoursite.com/#organization"

Reference it elsewhere:

"publisher": { "@id": "https://yoursite.com/#organization" }

This creates a web of interconnected entities that AI can traverse. When processing your article, it can follow the author reference to understand their credentials, then follow to your organization to understand the publishing entity.

Testing & Validation

Before deploying structured data, validate it using these tools:

Google Rich Results Test

Validates schema and shows how Google interprets it

Schema.org Validator

Official Schema.org validation tool

JSON-LD Playground

Debug and visualize JSON-LD structure

Pro Tip: After implementing structured data, monitor your AI visibility with CitePulse to see how the changes impact your citation rate across different LLMs.

See Your Schema in Action

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Continue Learning

Entity Authority

Building knowledge graph presence

Citation Optimization

Content that AI wants to cite

Structured Data for AI: The Technical Blueprint

In This Guide