E-E-A-T stands for Experience, Expertise, Authoritativeness and Trust. It comes from Google’s guidelines for the human raters who evaluate search quality, and it has been misrepresented in both directions: treated as a magic ranking dial by some, dismissed as irrelevant by others.
What it actually is
A description of what Google’s algorithms are trying to approximate. There is no E-E-A-T score in the system. What exists are many signals that, combined, attempt to identify content produced by people who know what they are talking about. So E-E-A-T is not a factor you optimise; it is an outcome you demonstrate.
Where it matters most
In YMYL topics, meaning content that could affect health, financial wellbeing or safety. In those categories the bar is visibly higher, which is why medical content by an anonymous writer struggles regardless of how well optimised it is. In lower-stakes categories the effect is real but far weaker.
Signals worth implementing
Name your authors, with genuine credentials and a bio page that establishes why they can speak on the subject. Add first-hand experience, since the extra E was added specifically to reward people who have actually done the thing rather than summarised those who have. Cite sources for claims that need them. Show review dates and who reviewed the content. Keep an about page that clearly explains who you are, and contact details a real person answers.
The connection to AI search
These same signals govern whether AI answer engines cite you. Machines need clear entity information and credible attribution before quoting a source, so E-E-A-T work is increasingly doing double duty. Two of my clients earned AI Overview citations on the back of exactly this kind of clarity, in banking and in technical robotics.
What it is not
It is not a plugin, a score, or a schema property. Adding author schema to content written by nobody in particular achieves nothing. The signals only work when they are true, which is the least convenient and most reliable thing about them.