How to prove website expertise to AI models: analyzing author pages

There is less original content on the internet

When generation costs pennies, it is cheaper to rewrite someone else's article than to conduct your own research. As a result, for any query, there are a dozen texts retelling each other in a loop. They contain zero new knowledge.

My position is simple: all content on the website must be authored. Articles, glossary terms, FAQs, introductory texts on service pages. Not because an AI model cannot write, but because it cannot visit a project, catch an indexing bug, and tell how it ended. Yandex states the same in the Webmaster guidelines: AI models can be an author's assistant, but should not replace them.

What search engines actually check

There are many myths here, so I rely on primary sources.

Yandex described the EPOS framework in its guidelines: expertise, usefulness, originality, substance. Moreover, these same aspects affect both ranking in Search and getting into Alice AI answers. Expertise comes first and means the confirmed competence of the author and the specialization of the website.

Google has a different logic in form, but the same in essence. Since 2023, the company has been repeating that it looks at content quality, not how it was created. Penalties are issued for scaled content abuse: mass production of pages to manipulate search results, regardless of who wrote them. The March 2026 update knocked exactly such projects out of search results.

A separate note on detection. Yandex has a public AI detector, but Yandex has never stated a connection between its results and rankings. So I would not use the thesis "the search engine will recognize generation and demote the website". The problem is not in recognition, but in the fact that recycled text fails in originality and substance, and that is enough.

How a search engine reads an author page

The mechanics look like this. The robot visits the article, reads the microdata and heading structure, and sees the specified author. Then it follows the link to this person's page. And there it either finds a real specialist with a biography, social networks, and contacts, or it finds nothing.

In the second case, the signature under the article remains a declaration. In the first, a verifiable fact appears: the material was written by a specific person, they have a footprint outside your website, and they vouch for what is written with their name. Website expertise for AI models is built precisely from such details, and not from the phrase "a team of professionals with 10 years of experience" on the homepage.

Technically, the connection is built through schema.org: Article links to Person, Person is tied to Organization, entities are connected via @id. Disconnected markup blocks, where the article knows nothing about the author, and the author knows nothing about the company, do not solve this task.

The main mistake on employee pages

I regularly see the same pattern. The author page exists, but it only has a last name, first name, and a line about which section the person is responsible for. Who they are, what they did before, how to contact them – nothing.

This is not just about search signals, it is about the reader. A person has a question about the article. There are no comments on the site. There is nowhere to write to the author. Through the contact form, they will reach a manager who did not write the article and will not give a substantive answer. The dialogue ends where it could have started.

What should be on the page to make it work:

• real biography and experience, not a one-line job title
• links to social networks and professional profiles
• direct contact to reach this specific person
• list of the author's materials with internal linking to them
• specialization: what topics they are responsible for

What happened on our project

On the Foton website, each article had an author with a separate page. I will be honest right away: we did not make a separate measurement of exactly how this affected AI search results. It is impossible to separate the contribution of author pages, technical fixes, and regular content publication after the fact, and I do not want to pass off correlation as causation.

What we have in fact: the site actively gets into the AI search results of both Yandex and Google. Author pages there were part of the overall work, along with the technical audit, semantics and systematic publication of materials month after month.

Where to start

If there are no author pages on the site yet, I would follow this order. First, one full-fledged page of a key specialist, not five empty cards just to tick a box. Then connected markup that links the articles, the author, and the organization. Next, the author's signature on all new materials and its gradual addition to the old ones.

And the main thing, without which the rest makes no sense: behind the signature there must be a person who actually wrote the text and can answer for every fact in it. It is easy to check this – ask the author a question about their own article.