E-E-A-T stands for experience, expertise, authoritativeness and trustworthiness. Google uses the idea to describe the kind of content its systems try to reward, and Google says that "of these aspects, trust is most important." For AI search the logic is the same, with one extra step at the front: an AI system can only cite a page it can read, and it can only prefer a page whose trust signals it can see.
This guide explains what E-E-A-T actually is (and what it is not), what Google, Microsoft and OpenAI say about earning a place in AI answers, and a practical way to build trust that both people and AI systems can read. Where it helps, we use this site as a worked example, including the original robots.txt study we published alongside this update. If you have not checked whether AI crawlers can reach your pages, start with the free AI crawler checker; the best E-E-A-T in the world does not help a page that bots cannot fetch.
What changed in this update
- : Rewritten. Replaced claims that E-E-A-T is a "trust gate" or ranking factor with Google's own wording, added Google's Who, How and Why questions, Bing's February 2026 content advice, the new AI visibility reports, a section on original research with our own study as the example, and a measurable checklist. Removed images that showed unsourced "AI E-E-A-T" signals.
- : First published.
Key Takeaways
- E-E-A-T is not a ranking factor. Google says so directly. It is a description of content its systems try to find with many signals.
- Trust is the center. Experience, expertise and authority "contribute to trust", in Google's words.
- Google's AI features use normal Search. There are "no additional technical requirements" beyond being indexed with a snippet.
- Show who, how and why. Bylines, methods, sources and dates are trust signals people and machines can both read.
- Original data is the strongest signal you control. It gives others something to cite that only you have.
What E-E-A-T is, in Google's own words
Google added the extra "E" for experience to its quality rater guidelines on 15 December 2022 (Google Search Central Blog), but the core idea has not changed. In its guide to helpful content, Google says its systems "identify a mix of factors that can help determine which content demonstrates aspects of experience, expertise, authoritativeness, and trustworthiness, or what we call E-E-A-T" (Google, helpful content guide).
| Letter | Question it asks | What it looks like on a page |
|---|---|---|
| Experience | Has the author actually done or used the thing? | First-hand tests, screenshots, real data, "we tried this and here is what happened" |
| Expertise | Does the author know the subject deeply? | Correct detail, clear explanations, credentials where they matter |
| Authoritativeness | Is the site or author a known source on this topic? | Others cite and link to it; it has a clear focus |
| Trustworthiness | Is the page accurate, honest and safe to rely on? | Sources, dates, corrections, contact details, no deception |
Two sentences from Google matter most. First: "Of these aspects, trust is most important. The others contribute to trust, but content doesn't necessarily have to demonstrate all of them." Second: "While E-E-A-T itself isn't a specific ranking factor, using a mix of factors that can identify content with good E-E-A-T is useful."
Google also says these signals carry more weight on "Your Money or Your Life" topics, where content "could significantly impact the health, financial stability, or safety of people". A page about medicine or money needs stronger evidence of expertise than a page about houseplants.
How E-E-A-T applies to AI search
AI search adds a step, not a new rulebook. Here is what each major platform actually says.
Google AI Overviews and AI Mode
Google says the same "foundational SEO best practices" apply to AI features as to Search. To be shown as a supporting link, "a page must be indexed and eligible to be shown in Google Search with a snippet", and "there are no additional technical requirements" (Google, AI features). Its list of practices includes allowing crawling "in robots.txt, and by any CDN or hosting infrastructure", internal links, page experience, important content "available in textual form", and structured data that "matches the visible text on the page".
Google also says AI Overviews and AI Mode "may use a query fan-out technique", running several related searches to build an answer. That rewards pages that cover a topic well enough to answer the follow-up questions, not just the first one.
Microsoft Copilot and Bing
When Microsoft launched AI Performance in Bing Webmaster Tools in February 2026, it published its own advice for pages that want to be cited (Bing Webmaster Blog): "Strengthen depth and expertise", "Improve structure and clarity" with clear headings, tables and FAQ sections, "Support claims with evidence" with "examples, data, and cited sources", "Keep content fresh and accurate", and "Reduce ambiguity across formats". That list is very close to E-E-A-T, written for AI answers.
ChatGPT
OpenAI does not publish ranking factors for ChatGPT search. It says any public site can appear, that OAI-SearchBot must not be blocked, and that ChatGPT adds utm_source=chatgpt.com to referral links so you can measure the result (OpenAI publishers FAQ). Be wary of anyone who claims to know more than that.
A common myth
You will read that AI engines use E-E-A-T as a "binary trust gate" or that a specific file or schema type unlocks citations. No AI company says this. What they do say is simpler: be crawlable, be clear, show evidence, and keep content current.
Step zero: AI systems must be able to read you
Trust signals are invisible to a crawler that is blocked. Before anything else, confirm that the AI search crawlers can reach your pages: OAI-SearchBot for ChatGPT search, Claude-SearchBot for Claude, PerplexityBot for Perplexity, and Googlebot and Bingbot for Google's and Microsoft's AI features.
This is not a theoretical risk. In our study of the top 10,000 sites, 7.4% of 4,962 valid robots.txt files block OAI-SearchBot and 7.3% block Claude-SearchBot, often by accident through a shared "block AI" list. CDN rules and firewalls block more. Our guide to why AI bots cannot crawl a site checks all seven layers, and the AI crawler diagnostic tests a page as each bot.
Readability matters too. Most AI crawlers do not run JavaScript, so author names, dates and sources loaded by a script may never be seen. Put them in the HTML the server sends.
Who, How and Why: Google's three questions
Google suggests evaluating content by asking who created it, how, and why. These three questions are the most practical way to build E-E-A-T, because each one maps to something you can put on the page.
Who created it
Google asks: "Is it self-evident to your visitors who authored your content? Do pages carry a byline, where one might be expected? Do bylines lead to further information about the author?" It "strongly encourage[s] adding accurate authorship information".
Google is just as clear about the opposite. "Fabricating creator profiles (such as by using AI-generated headshots, made-up names, or false credentials to make content appear as if it was written by human experts) is a form of deception", and it is "a signal of a low-quality page." A real name with a modest bio beats an invented expert every time.
How it was created
Google says it helps readers "to know how a piece of content was produced", for example how many products were tested and how. For AI-assisted content, it asks whether the use of automation is "self-evident to visitors through disclosures or in other ways". A short "How we checked this" note, like the one at the top of this article, answers that question in a few lines.
Why it was created
Google calls this "perhaps the most important question". Content should exist "primarily to help people". It warns against "writing to a particular word count because you've heard or read that Google has a preferred word count", adding: "No, we don't." And it warns against "changing the date of pages to make them seem fresh when the content has not substantially changed." Freshness means real updates, recorded honestly.
Experience: show that you did the thing
Experience is the easiest signal to fake in words and the hardest to fake in evidence. Google asks whether content shows "first-hand expertise and a depth of knowledge (for example, expertise that comes from having actually used a product or service, or visiting a place)".
- Show the test, not just the result. "We fetched 10,000 robots.txt files" is stronger than "many sites block AI bots".
- Include what went wrong. Real tests have surprises and limits. Writing them down is a sign of real work.
- Use your own screenshots, logs and numbers. Stock images and generic charts add nothing a reader cannot get elsewhere.
- Name the date and the conditions. "On 5 October 2026, with our own user agent" tells a reader exactly what you saw.
This page's companion, the AI crawler robots.txt study, is our worked example. It states the list we used, the date, the parser rules, the denominator, and five limitations, and it offers the raw counts as a CSV. A reader can check every number.
Expertise: be correct in the details
Expertise shows most clearly in details that a non-expert gets wrong. In our field that means knowing that Google-Extended is a robots.txt token with no crawler behind it, that ChatGPT-User may not follow robots.txt, or that a crawler obeys only one group in a robots.txt file. Google asks: "Does the content have any easily-verified factual errors?"
- Quote primary sources for every fact that a reader might doubt, and link them.
- Prefer exact wording from the source over a paraphrase when the detail matters.
- Say when something is not documented. "The operator has not said" is more expert than a confident guess.
- Fix errors visibly. A correction in a change log builds more trust than a silent edit.
Authoritativeness: become the source others cite
Authority is mostly given to you by others: links, mentions and citations from people who know the topic. Google asks whether someone researching the site would "come away with an impression that it is well-trusted or widely-recognized as an authority on its topic". You cannot fake that, but you can make it more likely.
- Publish something only you have. Original data, a free tool, or a test nobody else ran. Our guide to original data for AI visibility explains why this works.
- Stay focused. Google asks whether a site "has a primary purpose or focus". Depth in one area beats a little on everything.
- Make citing you easy. Offer a clear suggested citation, a stable URL and downloadable data.
- Earn mentions where your audience reads, such as industry newsletters, podcasts and conferences.
Trustworthiness: the signals people and AI can both read
Trust is where most of the practical work happens. These signals are visible to a person, written in the HTML for a crawler, and in many cases repeated in structured data.
| Signal | What to show | Machine-readable form |
|---|---|---|
| Author | A real name, a short relevant bio, a link to a profile page | author with Person in Article or BlogPosting JSON-LD |
| Publisher | Who owns the site, how to contact them | publisher with Organization; an About and contact page |
| Dates | Published and updated dates, both visible | datePublished and dateModified |
| Sources | Links to primary sources next to claims; a sources list | Plain links in the HTML |
| Method | How the content was made, including any AI use | A visible note; nothing special needed |
| Change log | What changed and when | A visible list; keep dateModified in step with it |
| Corrections | How to report an error, and past corrections | A visible policy page |
Google says structured data should match "the visible text on the page" (Google, AI features guide). So never put an author, date or rating in JSON-LD that the reader cannot see. Our schema markup generator builds Article and Organization markup that you can check against your page.
<script type="application/ld+json">
{
"@context": "https://schema.org",
"@type": "BlogPosting",
"headline": "E-E-A-T for AI Search: Build Authority for AI Citations",
"datePublished": "2026-03-27",
"dateModified": "2026-10-05",
"author": { "@type": "Organization", "name": "Horatos.ai", "url": "https://horatos.ai" },
"publisher": { "@type": "Organization", "name": "Horatos.ai", "url": "https://horatos.ai" }
}
</script>For a deeper look at author pages, read our guide to author bylines and credentials.
Write so your content is easy to cite correctly
AI answers quote short passages. A page that is clear at the passage level is easier to quote accurately, which is good for you and for the reader of the answer. This is also what Bing recommends: "Clear headings, tables, and FAQ sections help surface key information and make content easier for AI systems to reference accurately."
- Answer the question in the first sentence under each heading. Then explain.
- Put each number next to its source and date. A figure that travels without its source becomes a rumor.
- Use tables for comparisons. They keep related facts together.
- Define terms once, clearly. Then use them the same way throughout.
- Avoid ambiguity across formats. Bing advises aligning "text, images, and video so they consistently represent the same entities, products, or concepts".
Original research: the strongest E-E-A-T signal you control
Google's first content question is whether a page provides "original information, reporting, research, or analysis". Its quality rater guidance stresses effort and originality, and says that "attribution or giving credit to other sources doesn't replace the need for original effort" (Google, helpful content guide). Original data covers experience, expertise and authority at once.
You do not need a research budget. Options that most businesses can run:
- A survey of your customers or newsletter readers, with the questions and sample size published.
- An analysis of public data, as we did with robots.txt files from the Tranco list.
- A benchmark of tools or products you use, with the method written down.
- Anonymized data from your own product, with permission and care for privacy.
Publish the method and limits with the results, and offer the data. In our study, the limitations section explains that 2,202 of the 10,000 domains did not resolve as websites, so our denominator is 4,962 valid files, not 10,000. Saying that plainly is part of what makes the numbers trustworthy.
Common E-E-A-T mistakes in AI search
| Mistake | Why it hurts | Fix |
|---|---|---|
| Invented author personas or AI headshots | Google calls it deception and a low-quality signal | Use real people, even with short bios |
| Changing dates without changing content | Google lists it as a warning sign | Update dates only with real changes, and log them |
| Statistics with no source | Readers and AI answers cannot verify them | Link the source in the same sentence |
| Schema that says more than the page | Google says structured data must match visible text | Mark up only what readers can see |
| Blocking AI search crawlers | Trust signals cannot be read | Allow OAI-SearchBot, Claude-SearchBot, PerplexityBot |
| Writing to a word count | Google says it has no preferred word count | Write until the reader's question is fully answered |
| Claiming secret "AI ranking factors" | No AI company publishes any | Quote what platforms actually say |
Measure whether it is working
For the first time, the major platforms give site owners data on AI visibility. Use it to judge your E-E-A-T work by results, not by feel.
- Google Search Console: the Generative AI performance report, rolled out to all sites on 31 August 2026, shows impressions in AI Overviews and AI Mode by page (Search Console Help, AI report).
- Bing Webmaster Tools: AI Performance shows citations in Copilot and Bing AI answers, cited pages and grounding queries (Bing).
- Google Analytics: sessions from chatgpt.com, perplexity.ai, copilot.microsoft.com, gemini.google.com and claude.ai.
- Your logs: visits from AI search crawlers to the pages you improved. Our monitoring guide shows how.
Compare a page's numbers for a month before and after a substantial update. If impressions and citations rise for pages where you added evidence, sources and original data, you know which changes to repeat.
An E-E-A-T checklist for AI search
- □AI search crawlers and Googlebot can reach the page (robots.txt, CDN, firewall).
- □The main text, author and dates are in the server HTML, not loaded by JavaScript.
- □A real author byline links to a profile with relevant background.
- □A short "how we made this" note explains tests, sources and any AI use.
- □Every statistic links to its source in the same sentence.
- □Published and updated dates are visible, and a change log lists real updates.
- □Structured data matches what is visible on the page.
- □The page offers something original: data, a test, a tool or first-hand experience.
- □Each section answers its heading in the first sentence.
- □You check Search Console and Bing AI reports monthly for this page.
To check the technical items quickly, run the AI crawler checker for access and the GEO audit for on-page signals.
Sources and further reading
Every claim above links to the page it came from. These are the primary sources, all read or re-read on 5 October 2026. Where we give a figure from our own data, it comes from our robots.txt study of the top 10,000 sites, and the raw counts are in the downloadable CSV.
- Google Search Central: Creating helpful, reliable, people-first content
- Google Search Central Blog: E-A-T gets an extra E for Experience (15 December 2022)
- Google Search Central: AI features and your website
- Search Console Help: Generative AI performance report (31 August 2026)
- Bing Webmaster Blog: Introducing AI Performance in Bing Webmaster Tools (10 February 2026)
- OpenAI Help: Publishers and developers FAQ
- OpenAI: Overview of OpenAI crawlers
- Tranco: a research-oriented top sites ranking
