Definition
E-E-A-T stands for Experience, Expertise, Authoritativeness and Trustworthiness, the framework Google's Search Quality Rater Guidelines use to judge whether content and its creators are reliable for a given topic. It began as E-A-T; Google added Experience on December 15, 2022, to credit first-hand involvement such as having used a product or visited a place. Of the four, Google says trust matters most.
The current guidelines are the September 11, 2025 edition, which added examples of rating AI Overviews and expanded the YMYL definitions. They describe Trust as 'the most important member of the E-E-A-T family because untrustworthy pages have low E-E-A-T no matter how Experienced, Expert, or Authoritative they may seem.' The other three contribute to trust in different combinations. A review from someone who owned the product for a year shows experience; a tax explanation from a certified accountant shows expertise; being the source other experts cite shows authoritativeness. Not every page needs all three.
E-E-A-T is not a score in Google's algorithm. Google's page on creating helpful, reliable, people-first content says 'E-E-A-T itself isn't a specific ranking factor', but that its systems use 'a mix of factors that can identify content with good E-E-A-T', giving even more weight to such content on YMYL topics. Raters do not affect individual rankings either; Google compares their ratings to its results to check whether ranking changes work.
For AI search, the link is direct for Google and indirect elsewhere. Google's May 2026 guide to generative AI features says AI Overviews and AI Mode are 'rooted in our core Search ranking and quality systems', so the signals that reflect E-E-A-T in Search also shape which pages those features retrieve. ChatGPT, Claude and Perplexity do not publish their source-ranking criteria, but they retrieve from the same web and tend to cite pages with clear authorship, primary data and a reputation in their field.
Google's 'Who, How, and Why' questions are the most practical way to apply E-E-A-T:
- Who: is it clear who created the content, with bylines that lead to author pages showing relevant background?
- How: does the page explain how the content was produced, such as how many products were tested and how, or how AI tools were used?
- Why: was it created mainly to help people who come to the site directly, rather than to attract search traffic?
Google also warns that fabricating creator profiles, for example with AI-generated headshots, invented names or false credentials, is deception that makes a page untrustworthy. On October 1, 2026 Google updated its guidance on using generative AI content to bring it in line with the rater guidelines.
Teams act on E-E-A-T by building real author authority, publishing first-hand evidence and original data with information gain, keeping About, contact and editorial policy pages accurate, and correcting errors visibly. Our guide on whether your website is cited in AI Overviews shows how to check where those efforts show up. See helpful content for Google's wider people-first standard.
Examples of E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness)
- A camping gear site adds a 'How we test' section to every review listing the nights spent outdoors, the temperatures recorded and photos from each trip, turning generic summaries into first-hand evidence.
- A personal finance publisher replaces its 'Editorial Team' byline with named writers, each linked to an author page listing certifications, and adds 'Reviewed by' credits from a chartered financial planner.
- A software company deletes 200 AI-drafted blog posts attributed to a fictional persona after reading Google's guidance that fabricated creator profiles are a form of deception.
- A dermatology clinic's articles cite the clinical guidelines they follow, show the reviewing physician's board certification and date of last review, and link to a corrections policy.
