Person Schema for Authors and Team Members: Build AI Trust

Why Person Schema Matters for AI

When ChatGPT, Gemini, or Perplexity decides whether to cite your content, one of the first things they evaluate is: who wrote this, and are they credible?

This is not speculation. AI models are trained on Google's E-E-A-T framework (Experience, Expertise, Authoritativeness, Trustworthiness), and author identity is a core component of that framework. Google's own Search Quality Rater Guidelines dedicate entire sections to evaluating content creators. AI models that use web retrieval -- particularly Google Gemini and Perplexity -- carry these signals forward into their citation decisions.

The problem is that most websites present author information only as visible text. A byline that says "Written by Dr. Sarah Chen, Data Scientist at Acme Corp" is readable by humans, but AI crawlers parsing your HTML see it as just another string of text. They cannot reliably distinguish an author name from a photo caption or a testimonial quote.

Person schema solves this. It provides a machine-readable identity card for each author, explicitly declaring: this is a person, this is their name, this is where they work, these are their verified social profiles, and these are the topics they are qualified to write about.

The practical impact is significant. When AI models can verify that an author exists as a recognized entity -- with consistent identity across LinkedIn, their employer's website, and the articles they've written -- the trust score for that content increases. This is the same principle behind Organization schema: structured data makes entities verifiable, and verifiable entities get cited more.

If you are new to structured data in general, start with our JSON-LD basics for AI SEO guide before continuing. The rest of this article assumes you understand what JSON-LD is and how to add it to a page.

Complete Person JSON-LD: Every Property Explained

Here is a fully populated Person schema for an author. We will break down every property below:

{
  "@context": "https://schema.org",
  "@type": "Person",
  "@id": "https://example.com/team/sarah-chen#person",
  "name": "Dr. Sarah Chen",
  "url": "https://example.com/team/sarah-chen",
  "image": {
    "@type": "ImageObject",
    "url": "https://example.com/images/team/sarah-chen.webp",
    "width": 400,
    "height": 400
  },
  "description": "Data scientist and AI researcher with 12 years of experience in machine learning, natural language processing, and search systems. Author of 30+ peer-reviewed papers on information retrieval.",
  "jobTitle": "Head of AI Research",
  "worksFor": {
    "@type": "Organization",
    "@id": "https://example.com/#organization",
    "name": "Example Corp",
    "url": "https://example.com"
  },
  "sameAs": [
    "https://www.linkedin.com/in/sarahchen",
    "https://twitter.com/sarahchen_ai",
    "https://github.com/sarahchen",
    "https://scholar.google.com/citations?user=abc123"
  ],
  "knowsAbout": [
    "Machine Learning",
    "Natural Language Processing",
    "AI Search Optimization",
    "Information Retrieval",
    "Python",
    "Technical SEO",
    "Schema Markup",
    "Large Language Models"
  ],
  "alumniOf": {
    "@type": "CollegeOrUniversity",
    "name": "MIT",
    "url": "https://www.mit.edu"
  },
  "award": "Best Paper Award, ACL 2024",
  "nationality": "US"
}

Property-by-property breakdown

@id -- A unique, persistent URI for this person. Use the format https://yoursite.com/team/name#person. This identifier must be the same everywhere you reference this person in structured data. It is what ties all the schema together across pages.

name -- The person's full name exactly as it appears on their author pages, bylines, and social profiles. Consistency matters: if LinkedIn says "Dr. Sarah Chen" and your byline says "Sarah Chen", AI models may treat these as two different entities.

url -- The canonical URL of the person's author page or team profile on your site. This page should exist and contain substantive information about the person.

image -- A professional headshot. Use the ImageObject type with explicit width and height. AI models that process visual data use this to verify identity across platforms.

description -- A 1-3 sentence summary of the person's expertise and credentials. Write it as a factual statement, not marketing copy. This text may be directly consumed by AI models when evaluating author authority.

jobTitle -- The person's current role. Be specific: "Head of AI Research" is better than "Team Member."

worksFor -- Reference your Organization schema using its @id. This creates a bidirectional link between the person and your organization's entity.

sameAs -- An array of URLs pointing to the person's verified profiles on external platforms. This is one of the most important properties for AI trust. Read our detailed guide on the sameAs property for platform-specific best practices. Include:

• LinkedIn profile (highest priority)
• Twitter/X profile
• GitHub profile (for technical authors)
• Google Scholar (for academic authors)
• Wikidata entry (if available)
• Crunchbase profile (for founders/executives)

knowsAbout -- An array of topics the person has expertise in. This is covered in detail in the next section.

alumniOf -- Educational background. Use the CollegeOrUniversity type with a name and url.

award -- Notable awards or recognitions. Strengthens authority signals.

Connecting Person to Article Schema

Person schema on its own establishes an author's identity. But the real power comes from linking that identity to the content they create. This is done through the author property in your Article schema.

Here is how a TechArticle schema references a Person:

{
  "@context": "https://schema.org",
  "@type": "TechArticle",
  "headline": "How to Optimize robots.txt for AI Crawlers",
  "author": {
    "@type": "Person",
    "@id": "https://example.com/team/sarah-chen#person",
    "name": "Dr. Sarah Chen",
    "url": "https://example.com/team/sarah-chen",
    "jobTitle": "Head of AI Research",
    "knowsAbout": ["AI Search Optimization", "Technical SEO", "Schema Markup"]
  },
  "datePublished": "2026-03-15",
  "dateModified": "2026-03-20",
  "publisher": {
    "@type": "Organization",
    "@id": "https://example.com/#organization",
    "name": "Example Corp"
  }
}

The critical element is the @id reference. By using the same @id value (https://example.com/team/sarah-chen#person) in both the standalone Person schema and the Article's author property, you create an explicit link in the knowledge graph. AI models processing your site can now:

1. Identify the article's author unambiguously
2. Look up the author's full credentials from their Person schema
3. Check the author's knowsAbout against the article's topic
4. Verify the author's identity through sameAs links to external platforms

This chain of verification is exactly what E-E-A-T is about, and it is exactly what AI models evaluate when choosing sources to cite. For a deeper understanding of how E-E-A-T drives AI citations, see our E-E-A-T guide.

Pro tip: You can include a minimal Person object in the Article schema (just @id and name) and place the full Person schema separately on the same page or on the author's dedicated page. As long as the @id matches, AI and search engines will merge the data.

The knowsAbout Property: What to Include and Why

Of all Person schema properties, knowsAbout deserves special attention. It is the property that most directly tells AI models: this person is qualified to write about this topic.

When an AI model retrieves an article about "AI search optimization" and finds that the author's knowsAbout includes "AI Search Optimization", "Large Language Models", and "Information Retrieval", it has a structured, unambiguous signal that the author has relevant expertise. Without this property, the AI has to infer expertise from the article text alone -- which is unreliable.

What to include

Aim for 8-15 topics per person. Be specific enough to be meaningful, but broad enough to cover the person's actual scope:

"knowsAbout": [
  "AI Search Optimization",
  "Technical SEO",
  "Schema Markup",
  "JSON-LD",
  "Natural Language Processing",
  "Python",
  "Information Retrieval",
  "Large Language Models",
  "Content Strategy",
  "E-E-A-T"
]

Guidelines for choosing topics

1. Match real expertise -- Only list topics the person has genuinely published about or worked in. AI models can cross-reference this against actual content and social profiles. Listing "Quantum Computing" for a marketing manager will hurt credibility, not help it.

2. Use established terminology -- Prefer terms that appear on Wikipedia, in Google's Knowledge Graph, or as Schema.org types. "Machine Learning" is better than "ML stuff." "Search Engine Optimization" is better than "SEO magic."

3. Align with article topics -- Ensure there is overlap between knowsAbout values and the topics of articles the person authors. If the person writes about AI SEO, their knowsAbout should include AI-related terms.

4. Include both broad and specific terms -- "Data Science" (broad) plus "Time Series Forecasting" (specific) is stronger than either alone. The broad term captures general queries; the specific term captures niche authority.

5. Update regularly -- As a person's expertise evolves, update their knowsAbout. Stale data is better than no data, but current data is best.

Author Pages Strategy

Every author on your site should have a dedicated author page (e.g., yoursite.com/team/sarah-chen). This page serves as the canonical source for the Person entity and is where AI models go to verify author identity.

What an effective author page includes

• Full name and professional headshot -- matching exactly what appears in schema and bylines
• Job title and organization -- mirroring the jobTitle and worksFor schema properties
• Bio paragraph -- 100-200 words covering experience, expertise, and credentials
• Links to social profiles -- matching the sameAs URLs in schema
• List of articles by this author -- with links, creating an explicit content-to-author connection
• The full Person JSON-LD -- placed in the <head> or <body> of the page

The author page URL is what you use for the Person's url property, and it should be internally linked from every article byline. This creates a clear crawl path that AI bots follow: article byline links to author page, author page contains full Person schema with sameAs links to external profiles.

For more on how author bios influence AI trust beyond schema, see our guide on author bios and AI trust.

Handling Multiple Authors

For co-authored content, set the Article schema's author property to an array:

{
  "@context": "https://schema.org",
  "@type": "TechArticle",
  "headline": "Complete Guide to AI Search Optimization",
  "author": [
    {
      "@type": "Person",
      "@id": "https://example.com/team/sarah-chen#person",
      "name": "Dr. Sarah Chen",
      "url": "https://example.com/team/sarah-chen",
      "jobTitle": "Head of AI Research",
      "knowsAbout": ["AI Search Optimization", "NLP", "Large Language Models"]
    },
    {
      "@type": "Person",
      "@id": "https://example.com/team/james-kowalski#person",
      "name": "James Kowalski",
      "url": "https://example.com/team/james-kowalski",
      "jobTitle": "Senior SEO Engineer",
      "knowsAbout": ["Technical SEO", "Schema Markup", "Site Architecture"]
    }
  ],
  "datePublished": "2026-03-22"
}

Each Person in the array should have its own complete @id, name, url, and relevant properties. The array format signals to AI models that both authors contributed expertise, and the combined knowsAbout values cover a broader topical range -- which can strengthen the content's authority for multi-disciplinary topics.

When to use multiple authors:

• Research papers or data-heavy guides combining different expertise
• Content that spans multiple domains (e.g., technical implementation + content strategy)
• Collaborative case studies

When not to use multiple authors:

• Do not list editors or reviewers as authors. Use the editor or reviewedBy properties instead.
• Do not add authors who did not substantively contribute to the content.

Person Schema for Team and About Pages

Your about or team page is the perfect place to establish Person entities for every team member, not just authors. Here is how to structure schema for a team page with multiple people:

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://example.com/#organization",
  "name": "Example Corp",
  "url": "https://example.com",
  "member": [
    {
      "@type": "Person",
      "@id": "https://example.com/team/sarah-chen#person",
      "name": "Dr. Sarah Chen",
      "url": "https://example.com/team/sarah-chen",
      "jobTitle": "Head of AI Research",
      "image": "https://example.com/images/team/sarah-chen.webp",
      "sameAs": [
        "https://www.linkedin.com/in/sarahchen",
        "https://twitter.com/sarahchen_ai"
      ],
      "knowsAbout": ["Machine Learning", "NLP", "AI Search Optimization"]
    },
    {
      "@type": "Person",
      "@id": "https://example.com/team/james-kowalski#person",
      "name": "James Kowalski",
      "url": "https://example.com/team/james-kowalski",
      "jobTitle": "Senior SEO Engineer",
      "image": "https://example.com/images/team/james-kowalski.webp",
      "sameAs": [
        "https://www.linkedin.com/in/jameskowalski",
        "https://github.com/jkowalski"
      ],
      "knowsAbout": ["Technical SEO", "Schema Markup", "Site Architecture"]
    }
  ]
}

This approach does two things simultaneously:

1. Establishes Person entities for each team member with full credentials
2. Links those people to your Organization entity via the member property, reinforcing the bidirectional relationship between people and the company

The member property on the Organization side complements the worksFor property on the Person side. Together, they create a strong organizational entity graph that AI models can traverse when evaluating content authority. For a complete guide to Organization schema, see Organization Schema for Authority.

Common Mistakes

Based on our analysis of structured data across thousands of sites, these are the most frequent Person schema errors:

1. Inconsistent names across schema and profiles -- If your schema says "Dr. Sarah Chen" but your LinkedIn says "Sarah Chen, PhD", AI models may not connect them. Pick one canonical format and use it everywhere.

2. Missing @id property -- Without an @id, there is no way to reference the same Person entity across multiple pages. Every Article schema that mentions this author creates a disconnected entity instead of reinforcing a single one.

3. Empty or missing sameAs -- The sameAs property is how AI models verify that a person exists outside your website. Without it, your Person schema is an unverified claim. Always include at least LinkedIn. See our sameAs property guide for details.

4. Using Organization as author instead of Person -- Some sites set the Article author to their company name. While technically valid, AI models give stronger E-E-A-T credit to identifiable human authors. Use Person for the author and Organization for the publisher.

5. knowsAbout that does not match content topics -- If an author's knowsAbout lists "Graphic Design" and "Photography" but they are writing about SEO, the mismatch can actually weaken trust signals. Align expertise claims with published content.

6. No dedicated author page -- Person schema without a corresponding author page at the url creates a dead reference. AI crawlers follow the URL and expect to find a page about that person. A 404 damages trust.

7. Duplicate Person entities with different @id values -- If the same person appears with two different @id URIs (e.g., one on the blog and one on the about page), AI treats them as two separate people. Use a single @id everywhere.