E-E-A-T for AI search: the trust pages and author signals
E-E-A-T stands for Experience, Expertise, Authoritativeness and Trust. It is a set of guidelines used by Googles quality raters to evaluate pages. It isn’t a ranking factor. You can’t get a score from Google for E-E-A-T as they don’t hold any data. However you can include the signals that Quality raters and AI engines look at. This includes having named authors with real bios, an about page mentioning your company name and people, method page, cited statistics and consistent company information. If you’ve been told that E-E-A-T is important for AI then this guide will help you understand what pages and signals to include this quarter. We’ve listed them below in order, shown what they should look like on an AI start-up website and what we found.
Published 4 November 202614 min read
Key takeaways
- Google added “experience” to E-A-T in December 2022. The framework lives in the rater guidelines, and Google says those guidelines don’t directly influence ranking.
- Google calls trust the most important member of E-E-A-T. Pages that look untrustworthy rate low however expert they seem.
- No vendor can measure your E-E-A-T. Tools can check whether the signals behind it are present on your site.
- For AI answers, the practical goal is facts an engine can verify: who you are, who wrote the page and where each figure comes from.
- Start with the About page, then author bios on your most-read articles, then a methodology page.
What is E-E-A-T, and what is it not?
E-E-A-T is the shorthand Google’s Search Quality Rater Guidelines use for four qualities of a page and its creator: experience, expertise, authoritativeness and trust. Google added the first “E”, for first-hand experience, on 15 December 2022. The same announcement said the rater guidelines are used to evaluate Google’s ranking systems and “don’t directly influence ranking.”
Google’s guide to creating helpful, reliable, people-first content asks the same questions in plain words. Who created the content? How was it made? Why does it exist? That guide also says E-E-A-T itself isn’t a specific ranking factor.
Three things follow, and each one is worth repeating to anyone selling you an E-E-A-T fix:
Trust sits at the centre. The guidelines call it the most important member of the family, because an untrustworthy page rates low however experienced or expert it looks. Experience, expertise and authoritativeness matter mainly as evidence for trust.
That is why no vendor, including us, can measure your E-E-A-T. Any number labelled “E-E-A-T score” is a proxy built from signals a tool can observe, such as bylines, contact details and policy pages. Our glossary of modern search metrics explains why vendor composites only make sense as a trend inside one tool. For a fuller definition, see E-E-A-T explained.
Does E-E-A-T matter for AI search?
For AI search, E-E-A-T is important for giving you good results. Search engines will look at the signals in E-E-A-T to find accurate sources. No AI providers will publish a rule for E-E-A-T, but they can look at your website and see if it matches other sources.
By stating who you are, who writes for you and where your stats originate from, your website will give the search engines less reason to use a third-party source. If there are discrepancies or no facts then brands often become vague, confused with another similar brand, or a competitor with clearer facts will be quoted.
This affects AI and software companies the most as there are so many similar product names. If your product is an AI writing assistant or AI sales agent, there are hundreds of products with the same category name. Having one clear legal name, product name, founding team and official profiles across your website means that the search engine will not guess and will have a clear description.
Entity consistency is the part of E-E-A-T specific to AI. Make sure that your website, professional networks, reviews, app stores etc. have the same company name, product name and short description. To keep your facts in one place, check out our adviora’s client knowledge base guide.
Which trust pages should you add first?
Add trust pages in the order a careful reader checks a source: who is behind the site, how to reach them, who wrote this, and how they know. The table runs in that order:
Check rows 1, 3 and 4 most closely. The gaps that show up there are easy to miss from the inside: an About page that talks about a mission but never names the company, articles credited to “Admin”, and figures with no stated method. For the full set of seven trust pages and what each must contain, see the trust pages every website needs.
Which author signals matter for E-E-A-T?
Who Author Signals
- Author Signals help tell us who wrote the article. They give us a real name, proof of what they’ve done and matching author tags. You should make sure:
- Each article includes a real name. No ‘Admin’, ‘Editor’ or just company name.
- Each author has a bio page which shows what they’ve done and not just their role. Include links to their professional profiles.
- Any pages which require extra review (comparisons, pricing, financial/legal/technical) include a named reviewer.
- All articles have two dates. When it was first published and last reviewed/updated.
- Matching author tags. The author listed matches the byline. This will link through to their bio page.
Experience is often the easiest to miss. If your author bio just lists their role (e.g Head of Content) this doesn’t tell your reader why they should trust them. But if they list what they’ve done with robots.txt (audited robots.txt files for SaaS sites), then you know why you can trust them. Try to write bios around what they’ve done. If there are any proofs of what they’ve done, include links to them (presentations, published research, open source, named projects).
Even if you use AI to write your content, author signals don’t matter. Google’s guidelines state they don’t care about whether the content was written using a tool. What will impact trust is if no one has checked the article or would put their name to it.
Example: E-E-A-T on an AI startup’s site
This example is illustrative; the company is fictional. A seed-stage startup sells an AI agent that books meetings for sales teams. Buyers who ask an AI assistant about it get a vague answer, and one assistant confuses it with an older product that has a similar name. A trust review of the site finds this:
These do not require any new technologies. It requires someone to determine what is true about the company, document this in one place, and make it visible to both readers and engines. Then the company monitor the same buyer questions using AI assistants to see if the information becomes accurate.
What we found on adviora.ai, and what we are changing
We ran the same review on our own site on 15 October 2026, and it found the problems this guide warns about. We publish them because a guide on trust should show its own working.
We claim no ranking or citation result from these changes, and we won’t until we have measured one the way our methodology describes. We will update this table, with dates, as each fix goes live.
Which pages need the strongest E-E-A-T signals?
Pages which impact on a person’s money, health, safety or large decisions should have the best signals. Google refer to these as Your Money or Your Life (YMYL) pages, and their People-Centric Content guidelines note that 'We give additional importance to content demonstrating high-e-e-at on topics that could have a significant impact on health, financial security, safety, or societal well-being.'
- For software or AI businesses, the YMYL pages may be:
- Pricing, refunds and cancellations – they’ll impact on how much the customer will pay.
- Comparisons and alternatives – advising them to purchase.
- Security, privacy and data – particularly if you’re using any AI tools that access peoples’ emails, calendars, documents, or customer data.
- Tax, payroll, legal, health guides – if your product impacts on any of these.
You should include information about who has written and peer reviewed the content, precise pricing information and terms, and include a date for any figures. If you include who has reviewed the content and a date for the pricing information on your comparisons page it will be more trustworthy than an advert.
How to check your own site’s E-E-A-T signals
A basic E-E-A-T signal check needs a browser and about an hour, and it shows you where to start. Work through these steps:
- Open your five most-read articles. Does each one have a named author, with a bio page that says what that person has done?
- Open your About page. Does it name the legal entity, the location and the people who run the company?
- Search your company name. Do your website, your professional network profiles and your main review or app listings describe you the same way?
- Pick three statistics on your site. Can a reader see where each one came from, and when?
- Open your pricing and comparison pages. Is a reviewer named, and are prices and terms dated?
- Ask two or three AI assistants what your company does. Note what they get wrong, and which sources they cite instead of you.
- Run the free AI visibility check to see what four AI engines say about you today, with a fix list for your site.
Fix what you find in the order of the trust table above. Recheck the AI answers a month later with the same questions, so you are comparing like with like.
How Adviora checks your trust signals
Adviora checks whether the signals behind E-E-A-T are present on your site, and tracks how AI engines describe you over time. It does not measure Google’s E-E-A-T, because nobody can.
The trust score in the platform is our own measure, not Google’s, and it only makes sense as a trend over time. The Trust Foundation pack re-runs entity questions in six AI engines and Google AI Overviews 30 days after delivery. It cannot promise how engines will describe you afterwards; read what we can’t promise.
For the full order of fixes beyond trust signals, see how to get cited by AI search.
Common E-E-A-T mistakes
Most E-E-A-T mistakes come from treating it as a checklist of badges instead of a set of facts a reader can verify. Watch for these:
- Buying an “E-E-A-T score” or a plugin that promises to raise one.
- Author bios that list a job title but nothing the person has actually done.
- An About page that describes the mission but never names the company or its people.
- Different company descriptions on the website, professional networks and review platforms.
- Statistics with no source, or a source with no date.
- Article markup that names a different author from the visible byline.
- Fake reviewers: listing a credentialed expert as reviewer when they never saw the page.
E-E-A-T and Trust Foundation pack →
Frequently asked questions
No. Google says that E-E-A-T is not an explicit ranking factor, and your rater guidelines do not have a direct impact on rankings. It is used to assess whether Google’s systems are delivering quality results, but the factors that it is based on (such as clear authorship and accurate information) will impact how people and engines perceive your page.
No tool can measure your E-E-A-T, because Google does not compute a score for it. Tools, including our Adviora's can check whether the signals behind E-E-A-T are present: named authors, contact details, policy pages and sourced figures. Treat any such number as a trend inside one tool.
No AI provider publishes an E-E-A-T rule. Google says its AI features rest on the same systems as Search. In practice, clear authorship and consistent company facts give any engine verifiable information to describe you with, instead of relying on third parties.
Fix the About page first, then the author bios on your most-read articles. Those two answer the first questions a careful reader, or a model, asks about a source: who runs this company, and who wrote this page.
Not by itself. Google judges whether content is helpful and who stands behind it, not which tool drafted it. AI-assisted content hurts trust when nobody with real experience checks it, adds to it or puts their name on it.
No one can give a reliable timeline. Trust pages and bylines take days to publish, but search engines and AI assistants re-crawl and re-evaluate on their own schedules. Recheck the same AI questions about a month after each change, and judge the trend over several months.
Digital Marketing Manager
Digital Marketing Manager at Adviora, specializing in technical SEO, Answer & Generative Engine Optimization (AEO/GEO), digital analytics, and organic growth strategies.
More from Vimal Raj