E-E-A-T for AI

E-E-A-T for AI is the application of Google's Experience, Expertise, Authoritativeness, and Trustworthiness framework to content optimized for AI search surfaces.

Google formalized E-E-A-T as a quality signal for ranking. AI surfaces have absorbed similar evaluation criteria, often weighted more heavily: AI synthesizers are hesitant to cite sources that lack visible author credentials, recent dates, or clear authoritative tone.

Practical E-E-A-T for AI means: a visible author byline with role, the author's credentials, a recent `updatedAt` date, a clearly-attributed source list, and structured data (Article + Person schema) that exposes the author identity to crawlers.

FAQ

Does E-E-A-T matter for AI search?

Yes — arguably more than for Google organic. AI synthesizers actively avoid citing sources that lack clear expertise signals because hallucination risk is higher. Shipping author metadata is one of the cheapest GEO levers.

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