TL;DR. E-E-A-T = Experience, Expertise, Authoritativeness, Trust. AI engines give weight to pages with named authors, full credentials, reviewer blocks, and visible review dates. Anonymous "Content Team" bylines get deprioritized. Three concrete fixes per page: author byline + schema, reviewer block, review date. Fix time: 1 hour per page.
What E-E-A-T demands for AI
AI engines inherit Google's E-E-A-T framework but weight it differently. On Google, E-E-A-T affects ranking on YMYL topics (your money, your life). On AI engines, it affects extraction across all topics, because the engine has to decide which source to trust when it synthesizes.
A page with an anonymous byline and no review date competes against pages that have named, credentialed authors. Guess which one gets cited.
The 3-signal checklist
Signal 1: Author byline with credentials. Every page has a named author. Preferably a real person with:
- Full name (not just first name)
- Title and credentials (MBA, PhD, CFA, specific certifications)
- Link to an author page with more bio
- Optional: photo, LinkedIn link
Anti-pattern:
"By Rankscale Content Team"
Pattern:
"By Patrick Schmid, Co-founder & CMO at Rankscale. 6 years working in SEO and 2 years in GEO."
Signal 2: Reviewer block (for high-stakes content). On comparison pages, pricing pages, legal / compliance / medical / financial content, add a reviewer block: "Reviewed by [Name, Credentials] on [Date]." The reviewer is a second named person with subject-matter expertise. On a "best CRM" comparison, a reviewer might be a CRM implementation consultant. On a pricing page for a regulated product, a compliance officer.
Signal 3: Review date visible on the page. Not just "published 2024-01-15." Also "Last reviewed: April 2026." Review date is the E-E-A-T equivalent of dateModified. It tells engines "a named human re-checked this recently." Refresh cadence from lesson 5.5 should include a review date update, not just a content update.
Author schema (JSON-LD)
Every Article schema should include the author:
{
"@context": "https://schema.org",
"@type": "Article",
"author": {
"@type": "Person",
"name": "Patrick Schmid",
"url": "https://rankscale.ai/team/PatrickSchmid",
"jobTitle": "Co-Founder and CMO",
"sameAs": [
"https://www.linkedin.com/in/patrick-schmid-563634132/"
]
},
"reviewedBy": {
"@type": "Person",
"name": "Reviewer Name",
"url": "https://rankscale.ai/authors/reviewer"
}
}sameAs on the author object is the same trick as sameAs on your Organization: it disambiguates the author entity across LinkedIn, Twitter, and wherever else they exist online.
The author page (one per author)
Every named author needs a dedicated author page at /authors/[name] containing:
- Photo
- Full name and credentials
- Bio paragraph (100–150 words)
- Areas of expertise
- Link list of everything they have written on your site
- External links: LinkedIn, Twitter, personal site
This is the page AI engines use to verify the author is a real, verifiable expert. Without it, the byline is just a name.
What NOT to do
- Do not make up authors. AI engines cross-check authors against LinkedIn and publication history. Fake authors get flagged.
- Do not reuse the same "Content Team" byline across 200 pages. That is not E-E-A-T, that is stock photo of credibility.
- Do not set review date once and never update. If your review date is 18 months old, the page has a Freshness Gap, not an E-E-A-T fix.
Do this now:
Open your priority page. Replace any generic byline with a named author. Add a "Last reviewed: [Month Year]" line. Add author schema to the JSON-LD. Ship.
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