E-E-A-T
Originally a Google Search quality guideline, E-E-A-T has become increasingly relevant to AI systems as well, which favor citing sources that demonstrate real-world experience, subject-matter expertise, and verifiable credibility.
It is not a score anyone can measure directly, which is why it gets discussed vaguely. In practice it shows up as concrete, checkable things: a named author with a real professional profile, a visible review date, citations to primary sources, and an organisation that can be identified as a genuine entity rather than an anonymous website. Each of those is either present or absent — which makes E-E-A-T far more actionable than its reputation suggests.
Strong E-E-A-T signals — like author bios, credentials, and organizational transparency — directly influence whether an AI system trusts your content enough to cite it.
A glossary entry written and reviewed by a named author with verifiable credentials and a linked professional profile demonstrates stronger E-E-A-T than an anonymous, uncredited page.
What is E-E-A-T?
Experience, Expertise, Authoritativeness and Trustworthiness — the framework Google, and increasingly AI systems, use to judge whether a source is credible.
