E-E-A-T in the AI Context
Google introduced E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) as a framework for human quality raters to evaluate content. In traditional SEO, E-E-A-T influences rankings indirectly through human judgment signals.
For AI systems, E-E-A-T operates differently—and more directly. LLMs use these signals as a "Certainty Score" that determines their confidence in citing your content. The critical difference: you must translate these human concepts into machine-readable signals that AI can parse and verify programmatically.
For Human Evaluators
E-E-A-T is evaluated subjectively based on reading content, checking credentials, and assessing overall quality.
For AI Systems
E-E-A-T must be encoded in structured data, entity connections, and verifiable attributes that machines can parse.
Experience
First-hand knowledge that distinguishes original insight from aggregation
AI systems are trained to distinguish between content that demonstrates genuine first-hand experience versus content that merely summarizes other sources. Experience signals tell the AI: "This author has actually done/used/tested what they're writing about."
How to Signal Experience to AI
- Include specific case studies with real results and metrics
- Share original data from your own research or operations
- Document your methodology when presenting findings
- Use first-person accounts of product usage or implementation
- Include timestamps and dates that prove ongoing engagement
- Add images, screenshots, or videos demonstrating actual use
Pro Tip: When writing product reviews or recommendations, include specific details that only someone who actually used the product would know. AI systems are increasingly sophisticated at detecting generic, templated content.
Expertise
Verifiable credentials and demonstrated knowledge depth
AI systems evaluate expertise by checking whether author credentials can be verified and cross-referenced. Unlike humans who might take credentials at face value, AI actively looks for connections to establish that claimed expertise is real.
Person Schema
Implement Person schema for all content authors with:
- • Full name and professional title
- • sameAs links to LinkedIn, ORCID, Twitter
- • jobTitle and worksFor attributes
- • alumniOf for educational credentials
- • knowsAbout for areas of expertise
Organization Schema
Your organization's expertise signals include:
- • Industry certifications and accreditations
- • Years in operation (foundingDate)
- • Number of employees and customers
- • Awards and recognitions
- • Published research and patents
The Verifiability Requirement
Simply claiming expertise isn't enough. AI systems attempt to verify claims by cross-referencing with external sources. If your author's LinkedIn doesn't match your author bio, or their credentials can't be found elsewhere, the expertise signal is weakened or ignored entirely.
Trustworthiness
Transparency, accuracy, and consistent reliability
Trustworthiness is the foundation of all E-E-A-T signals. AI systems are specifically designed to avoid hallucination—presenting false information as fact. They prioritize sources that demonstrate transparency and factual accuracy.
Cite Your Sources
Back up factual claims with links to primary sources. AI systems check whether your facts can be verified and whether you cite authoritative sources.
Be Transparent About Limitations
Acknowledge what you don't know or where uncertainty exists. AI systems are wary of content that claims absolute certainty on complex topics.
Maintain Factual Accuracy
Regularly audit your content for outdated or incorrect information. AI systems may have access to more recent data and can detect inaccuracies.
Clear Privacy & Editorial Policies
Published privacy policies, editorial guidelines, and correction policies signal organizational trustworthiness.
E-E-A-T Implementation Checklist
Use this checklist to systematically build machine-readable E-E-A-T signals across your digital presence:
EExperience Signals
- Add case studies with specific metrics and results
- Include original research data and methodology
- Document hands-on product/service experience
- Add user-generated content and testimonials
- Include dated, timestamped content showing ongoing engagement
EExpertise Signals
- Implement Person schema for all authors with sameAs links
- Link author profiles to LinkedIn, ORCID, professional sites
- Add credentials, certifications, and educational background
- Create comprehensive author bio pages
- Include knowsAbout attributes in Person schema
AAuthority Signals
- Pursue press coverage and industry publication features
- Apply for industry awards and certifications
- Build relationships with .edu and .gov institutions
- Create Wikipedia-worthy content and seek inclusion
- Get quoted as an expert in news articles
TTrust Signals
- Cite authoritative sources for all factual claims
- Publish clear privacy policy and terms of service
- Add datePublished and dateModified to all content
- Include editorial guidelines and correction policies
- Implement secure site (HTTPS) and transparent contact info
Measure Your E-E-A-T Impact
CitePulse tracks how your E-E-A-T signals translate into actual AI citations. See which trust signals are working and where to focus your optimization efforts.
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