E-E-A-T Signals and AI Visibility

When Google's E-E-A-T guidelines were written, artificial intelligence was not yet so widespread. But AI systems also look at similar signals when measuring trustworthiness — and most of these are already what you apply for Google.

Yazar: GeoSkoru Editörü · Kategori: Araştırma · Yayın tarihi: 14 Mart 2026

E-E-A-T, the four criteria defined by Google in the guide prepared for its quality raters: Experience (Experience), Expertise (Expertise), Authoritativeness (Authority) and Trustworthiness (Trust). These concepts emerged before systems like ChatGPT were designed. But when AI systems need to perform trustworthiness evaluation, they seem to turn to very similar signals.

How Does Artificial Intelligence Measure Trustworthiness?

AI systems behave much more cautiously, especially in content in the 'YMYL' (Your Money or Your Life) category — medicine, law, finance, security. In these categories, your signals must be very strong to be considered a reliable source. In other categories, although the bar is a bit lower, author identity, publication date, and institutional information are still critical.

E

Experience — Real-life practice on the subject

E

Expertise — Depth of technical and academic knowledge

A

Authoritativeness — Being recognized as a reference in the field

T

Trustworthiness — Transparency, accuracy, and accountability

Experience Signal: Tangible Evidence

The experience signal is the newest added dimension of E-E-A-T. When Google added this criterion in 2022, it wanted to emphasize the difference between 'real-life experience' and 'theoretical knowledge'. A drug interaction article written by a doctor carries a very different trustworthiness signal than an article on the same subject penned by a content writer.

For your site, this means: Embody your authors' experience within the content. Instead of vague phrases like 'Over the years, we have seen that...', use specific, measurable references like 'In 200 Turkish e-commerce sites we analyzed, we observed this:'.

Author Pages: A Detail Not To Be Missed

When evaluating content, AI systems try to find out who the author is and whether they are trustworthy. To do this, you need to have data about the author on your site. For every content creator, the following should be present: Name and photo, short biography (area of expertise and background), link to LinkedIn or other professional profiles, a list of content authored by that writer.

Important detail: General phrases like 'I covered this in this article' or 'I researched all of it' in author biographies generate very weak signals. Verifiable details like 'I worked as a product manager in the fintech sector for 5 years, and now I run my own consulting company' are much stronger.

Trust Signal: Transparency is Mandatory

The trust signal is the E-E-A-T dimension most easily detected by AI systems. Because transparency either exists or it doesn't: Is there a contact page, a physical address, an about us page, a privacy policy, is it clearly stated if there are ads in the content? If the answer to these questions is 'no', your trust score decreases.

  • About Us page: Company history, team, mission. Real team photos, not stock photos.
  • Contact page: Email, phone, physical address (if any). A form alone is not enough.
  • Legal pages: Privacy policy, cookie policy, terms of use.
  • Citing sources: Link original sources to statistical and research data.
  • Correction policy: If you make corrections for erroneous content and state this clearly, it's a big trust signal.

Etiketler: E-E-A-T, GEO, AI görünürlük, güvenilirlik