EEAT and AI: how to strengthen your expertise signals for LLMs
Cyril Cretin
Founder RadarLLM.ai
Google uses EEAT (Expertise, Experience, Authority, Trust) to evaluate content credibility. AI engines apply similar trust criteria — especially for YMYL topics (health, finance, legal). Strong EEAT signals mean more LLM citations.
This guide shows you how to strengthen each EEAT pillar specifically for AI visibility. No vague theory: concrete signals, an actionable checklist, and a 5-step action plan.
The 4 EEAT pillars decoded for AI
Each pillar accounts for 25 points in the EEAT score. AI has no visual cues — it relies entirely on structured signals. Here’s what each pillar concretely means for LLMs.
AI engines look for verifiable proof that the author masters their subject. Content signed by an identified expert with documented qualifications will be cited first by LLMs.
AI detects first-hand content. Real testimonials, documented case studies, and "we tested" language are strong credibility signals.
AI measures your external reputation. Authoritative backlinks, press mentions, and citations from other trusted sources boost your authority in the eyes of LLMs.
Trust is the foundational pillar. Without HTTPS, legal notices, or a visible privacy policy, AI considers your site untrustworthy and will not cite you.
Why EEAT matters more for AI than for Google
Google has visual cues to evaluate trust: bounce rate, time on page, site design. AI engines have none of that. They rely exclusively on structured signals — Schema.org, HTML markup, metadata, and inbound links.
YMYL impact: enhanced filtering by AI
On YMYL topics (health, finance, legal), AI applies even stricter filtering than Google. Medical content without an identified, qualified author will never be cited by an LLM. AI would rather return no answer than cite an untrustworthy source on these topics.
The "Citation Cliff": the freshness drop-off
Outdated content loses AI trust fast. Pages not updated for over 90 days see their citation rate drop drastically. AI considers publication and modification dates as key trust signals.
EEAT checklist for AI visibility
Review each signal. Every missing element is an opportunity to strengthen your credibility in the eyes of AI.
RadarLLM automatically checks all 12 signals during the Expert audit and assigns an OK/KO score to each.
5-step EEAT action plan
Follow this priority order. Technical trust is the prerequisite, expertise and experience improve quickly, and authority is built over time.
Audit your current EEAT score
Start by measuring your EEAT score with a tool like RadarLLM. Identify the weakest pillars and missing signals. Without a diagnosis, every action is blind.
Create complete author pages
Every author needs a dedicated page with bio, photo, qualifications, links to social profiles and publications. Add Person schema in JSON-LD with credentials and sameAs.
Strengthen the technical trust layer
Verify HTTPS, add complete legal notices, privacy policy, contact page with verifiable information. Implement Organization schema with sameAs.
Enrich content with real-world experience
Add case studies, client testimonials with Review schema, real work photos. Replace generic content with original data and field-tested insights.
Build external authority progressively
Publish on LinkedIn, participate in podcasts, seek press mentions. Every verifiable external mention strengthens your authority in AI’s eyes. This is the longest pillar to build.
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