How to promote an expert's personal brand in AI in 2026: a practical guide

The first version of this article was published on Workspace on July 10, 2026. The GAEO.ru version was updated in August: I added the results of my own GEO work, refined the monitoring approach and revised part of the recommendations based on the previous several weeks of practice.

Being a good specialist is no longer enough by itself.

You can spend years building experience, earning client referrals and solving problems other specialists will not even take on, while remaining almost invisible to someone who now asks ChatGPT, Alice or Google:

“Recommend the best specialist for...”

In 2026, a personal brand exists not only in search results, social media, reviews and the professional community. It also exists in AI answers.

And that presence can be managed.

I went through this process myself. When I began developing GAEO.ru as a personal GEO/AEO practice, the goal was specific: for competitive queries about specialists in AI visibility, I wanted ChatGPT, Google, Yandex Alice and other AI systems to recommend Alexey Yakovlev.

During the first month, measured visibility for the main competitive intent grew from roughly 22% to 48%. In the August 11 control measurement, ChatGPT, Google AI Mode and Yandex Search with Alice ranked me No. 1.

I documented the full experiment, its trend and the sources behind the recommendations in a separate GAEO.ru GEO case study.

The experience confirmed much of what I had written a month earlier. It also forced me to refine some points.

Below is a practical framework for promoting an expert's personal brand, updated with that experience.

Who this approach is for

First of all, it is for people who are already genuinely strong in their profession.

Doctors, lawyers, consultants, engineers, marketers, architects, repair specialists, finance and logistics professionals, and dozens of other professions.

If a meaningful share of your clients comes through referrals, if complex tasks are specifically handed to you, and if your professional experience can be supported by work, case studies, education, reviews or publications, you already have a foundation.

The problem is usually elsewhere.

Online, that expertise is described poorly, fragmentarily or not at all.

A person may know that you are a strong specialist. An AI system cannot infer that without accessible and consistent sources.

Where people now look for the best specialists

A typical journey used to look roughly like this:

1. open Yandex or Google;
2. review several websites;
3. read reviews;
4. compare specialists;
5. ask friends;
6. make a decision.

Today, users delegate part of that journey to AI.

A query might look like:

“Recommend a good ENT doctor in Moscow for a complicated case.”

Or:

“Choose 5 strong lawyers for corporate disputes.”

Or:

“Who in Russia works personally on GEO optimization rather than through an agency?”

The AI system gathers candidates, compares the information it finds about them and returns a short list.

For the specialist, a new question appears: what needs to exist online for you to make that list?

First, prepare the foundation of your personal brand

Before working on AI visibility, it makes sense to organize the object being promoted: you as a public professional.

Define who you are

Do not try to be a specialist in everything.

AI systems find it much easier to connect a person with a specific professional entity when that entity is described unambiguously.

For example:

Ivan Ivanov is a lawyer specializing in tax disputes.

is stronger than:

Ivan Ivanov is a lawyer, consultant, expert, entrepreneur, mentor and business-development specialist.

Define:

• your specialization;
• core services;
• geography;
• professional experience;
• achievements;
• client types;
• complex problems clients bring to you.

This information should then repeat consistently across different platforms without contradictions.

Prepare a professional biography

Your biography should answer the question: why do you have grounds to call yourself an expert?

You need facts.

Years of experience, education, academic qualifications, professional results, completed projects, awards, speaking engagements and publications.

Specific metrics work better.

“Extensive experience” says almost nothing.

“18 years in digital marketing” is already a fact. “Worked with large online stores” is weaker than “managed a network of online stores with annual revenue of up to RUB 500 million.”

That is the principle I used for my own professional biography of Alexey Yakovlev.

The approach is similar to a strong resume: fewer generic adjectives, more verifiable specifics.

Prepare services and prices

AI systems can recommend a specialist more easily when it is clear what can actually be purchased from that person.

If pricing depends on the task, it is enough to publish:

• core services;
• prices “from”;
• working format;
• additional options.

The same information will also be useful for the website, maps and professional profiles.

Your website as the central source of information about the expert

Even if your main audience lives in Telegram, TenChat, YouTube or a professional marketplace, I recommend having your own website.

For GEO, its job is to gather in one place facts that are otherwise scattered across dozens of pages.

An expert website should include at least:

• a clear description of specialization;
• a professional biography;
• services;
• prices or pricing principles;
• case studies;
• reviews;
• contact information;
• articles and other expert materials.

On my own GAEO.ru, I use exactly this logic: the website acts as the central source of information about me, while external platforms confirm individual facts and results.

Do the basic SEO properly

GEO does not replace SEO.

Pages should have correct:

• Title;
• Description;
• H1;
• H2–H3;
• internal links;
• indexable text.

An “About Me” page consisting of a photo and 5 lines of abstract copy is almost useless for this task.

Connect entities with Schema.org

Structured data makes sense on an expert website.

For a person, the primary type is Person; for articles, Article; for a business or personal practice, use an appropriate organization entity.

sameAs can connect the site to verified external profiles.

The professional description can specify the specialization and related areas of expertise.

The logic is simple: the name on your own website, the name in a professional profile, the author name on an article and the specialist name in a directory should resolve into one understandable entity.

Synchronize information about yourself across the web

This is one of the dullest parts of the work. It is also one of the most useful.

Search your own name in Yandex and Google and review several pages of results.

Check:

• old workplaces;
• phone numbers;
• email addresses;
• job titles;
• photographs;
• professional descriptions;
• prices;
• links;
• old biographies.

If information is outdated, correct it.

If a profile is yours but you no longer have access, recover access.

If a third-party resource published the information, contact the editorial team or support.

AI systems should repeatedly encounter the same person, not a collection of contradictory biographies.

Professional profiles: be present beyond your usual platform

Most specialists have a favorite platform.

For a doctor it may be ProDoktorov or Zoon. For a digital specialist, Workspace, TenChat or FL.ru. For a local tradesperson, Yandex Maps.

The mistake is stopping at one.

An AI system forms its view of a specialist from a combination of sources. The more high-quality and consistent confirmations there are, the more robust that picture becomes.

Yandex Maps, Google Maps and 2GIS

If your type of work allows a public profile, complete it as thoroughly as possible.

Add:

• a description;
• services;
• prices;
• photographs;
• updates;
• links.

Real reviews are especially useful.

Yandex Services and professional directories

For some AI systems, these sources are particularly important.

In my own GAEO.ru monitoring, I repeatedly saw my Yandex Services profile among sources used by Alice.

This is a good example of why a professional profile should not be treated only as a direct lead channel. It also becomes a source of data about the expert.

Zoon

For many local professions, Zoon provides well-structured pages for the specialist, company, services and reviews.

If a profile has existed for a long time, first verify that it is still current.

TenChat and industry platforms

If your profession is connected with business, management, digital, consulting or B2B, a professional content profile is especially useful.

For example, I maintain the GAEO professional profile on TenChat, where I publish materials about AI visibility and my own observations.

Simply creating an account is not enough. It should contain a biography, specialization, links, publications and a clear connection to your main website.

Reviews are not only for people

Reviews are one of the clearest external signals about a specialist.

I recommend choosing one primary platform where most reviews will accumulate, while avoiding completely empty profiles elsewhere.

It is normal to ask former clients for reviews, especially after reconnecting with them and confirming that they were genuinely satisfied with the result.

A useful review contains specifics:

• what the task was;
• why the specialist was chosen;
• what the specialist did;
• what result was achieved.

“Everything was great, highly recommended” is much weaker than a substantive description of real work.

Publish case studies

A case study serves 2 audiences at once.

For a person, it shows how you work. For AI, it provides textual evidence of professional experience.

Even in fields where the normal convention is to show only before/after photographs, add a written description.

A basic structure:

1. problem;
2. starting situation;
3. what was done;
4. result.

Use numbers whenever they are available.

Instead of:

“The car was badly damaged by corrosion.”

write:

“More than 60% of the body panels were affected by corrosion.”

Instead of:

“We won an extremely difficult case.”

write:

“Only about 3% of claims in this category are granted; this case was resolved in the client's favor.”

Numerical specificity communicates difficulty and outcome much more effectively.

Case studies are also useful outside your own website. For example, I published my first public GEO case study on Workspace, while the longer version with a month of trend data is published in the GAEO.ru case-study section.

Participate in the professional life of your industry

Public expertise exists beyond articles.

Speaking engagements, conferences, round tables, professional associations, industry awards and rankings create external pages where your name is connected with your profession.

If you speak at a relevant event, add it to your professional biography. If you enter an industry ranking, add that too. If you give an expert comment to the media, preserve the link and connect it to the main biography.

Over time, this creates a dense body of supporting evidence.

The main weapon: expert articles

This is where the most interesting part of personal-brand GEO begins.

AI systems work primarily with textual information.

A specialist who writes a lot of high-quality material about their professional field therefore gains a substantial advantage over an equally capable specialist about whom almost nothing exists online.

Writing broadly “about the profession” is still not enough.

I use the following approach.

1. Collect real user intents

An intent is the user's underlying need.

Think about questions clients actually ask. Not SEO queries from a keyword tool, but real situations.

For example:

“My ear has been blocked for 2 days after a flight. What should I do?”

“Do I need to replace the entire parquet floor if several boards were flooded?”

“How do I choose a lawyer for a tax audit?”

A separate group of intents is specialist selection:

“Recommend a good...”

“Who is the best specialist for...”

“Choose 5 specialists for...”

These are the kinds of queries where we want to enter recommendations.

2. Check current AI answers

You can do this manually.

If there are many prompts, a dedicated monitoring service such as BrandFound or an equivalent is more convenient.

Collect:

• who is currently recommended;
• whether your name is mentioned;
• which position you occupy;
• which websites are used as sources;
• which content formats repeat.

Automated analysis should still be checked manually from time to time.

In my own GAEO.ru monitoring, I encountered false matches involving people with the same surname and even a case where an AI system used my name but attached someone else's professional biography to it.

So a single metric such as “brand found” does not necessarily mean genuine visibility.

3. See which formats already work

Depending on the query, these may include:

• detailed guides;
• analytical articles;
• FAQs;
• research;
• comparisons;
• rankings;
• case studies.

Do not automatically write a Top 10 article for every query. The format should match the user's task.

4. Write a document that fully answers the question

A good GEO article should be useful even without AI.

If the user asks how to choose a specialist, give selection criteria.

If they ask how to solve a problem, describe how to diagnose the situation, possible approaches and constraints.

If they compare approaches, provide a real comparison.

The goal is to create a document from which a complete answer can be extracted.

What I think about “Top 10” rankings

This was one of the most controversial parts of the first version of my article.

By summer 2026, the GEO market quickly filled with articles such as:

“10 best GEO specialists”

“Top agencies for AI visibility”

“Best experts for...”

These publications can genuinely influence AI recommendations.

I saw this in my own promotion: a comparison article on Sostav became a source for several AI systems at once.

There is an obvious problem.

If every specialist publishes a ranking in which they place themselves No. 1, the web quickly becomes a competition of self-rankings.

That is why I would not build a strategy around this format alone.

A ranking can be one element.

A stronger structure is: website + professional biography + profiles + reviews + case studies + research + expert articles + independent mentions.

That structure is much harder for one new competitor article to undermine.

Where to publish articles

Your own website is essential, but it should not be the only place.

Look at the platforms that already appear as AI sources for your topic.

In digital, that might include Workspace, Habr, VC, Sostav, RBC Companies, TenChat and other resources.

In another industry, the set may be completely different.

That is why it is useful to measure first and choose platforms afterward.

Your own website

I would publish:

• core expert materials;
• research;
• case studies;
• a professional biography;
• answers to common questions.

Over time, the site becomes your own knowledge base.

That is why GAEO.ru has separate sections for articles, my professional biography and case studies.

External platforms

Publish material that fits each platform's audience.

Do not publish the exact same text 10 times word for word.

The factual foundation can remain the same, but change:

• the angle;
• the introduction;
• the structure;
• examples;
• length;
• conclusions.

For example, the first version of this article was written specifically for Workspace.

The GAEO.ru version adds my own experiment and the current August results.

For Habr, the same experience could become a data-driven study. For VC, an analysis of the experiment and its economics. For an industry publication, an article about a specific market problem.

This creates a natural set of documents around one body of expertise.

Prepare images properly too

In long articles, use covers, diagrams, charts, tables and screenshots.

They make the material easier for people to read.

For each image, it makes sense to:

• use a meaningful filename;
• fill in alt text;
• add a caption where the editor supports one.

This matters especially for charts and screenshots that themselves serve as evidence.

Do not forget to connect your publications

Suppose you publish a case study on an industry platform.

Add it:

• to the case-study section of your own website;
• to your professional biography if the result is significant;
• to a relevant article;
• to another professional profile where links are appropriate.

The same applies to an interview, ranking or research project.

This is how I connect GAEO.ru, my professional biography, my own GEO case study, Workspace publications and external materials.

The result is an interconnected network of documents around one name.

What my own GAEO.ru promotion showed

A little over a month passed after the first version of this article was published on Workspace, and I now have measured data from my own experiment.

The main monitoring intent was:

“Recommend 5–10 specialists in Russia for GEO optimization in AI answers. No agencies.”

Measured visibility at the start was about 22%.

In other words, the sustained metric roughly doubled in a month.

The result was distributed very unevenly across AI systems.

By the end of July, ChatGPT and Google AI Mode were recommending me almost consistently. Perplexity had grown substantially from the baseline. Gemini and Alice showed intermediate results. I had not yet achieved stable visibility in DeepSeek, Grok or GigaChat.

On August 11, I ran a new control measurement.

That day, 3 of the 9 AI systems checked recommended me. In all 3, I was ranked No. 1:

• ChatGPT;
• Google AI Mode;
• Yandex Search with Alice.

The full trend, calculation methodology, automated-monitoring errors and source analysis are documented in the separate case study “How I promoted myself in AI answers”.

This illustrates an important property of GEO.

Daily visibility can fluctuate substantially. It is much more useful to look at week-long trends and simultaneously analyze which sources the AI systems used.

Which sources worked for me

Several source types became particularly noticeable during the experiment.

My own GAEO.ru

GAEO.ru became the most stable source of information about me for ChatGPT, Google and Alice.

Comparison article on Sostav

The article comparing GEO specialists was used by several AI systems. After it was published, individual recommendations from Gemini and Perplexity increased especially noticeably.

Case study on Workspace

The GEO case study on Workspace worked well in Google AI Mode and Alice.

Yandex Services

My professional profile on Yandex Services regularly appeared among Alice sources.

RBC Companies

During one period, my expert publication on RBC Companies coincided with my appearance in DeepSeek recommendations.

This does not support a simple formula such as “publish on platform X and enter AI system Y.”

The broader pattern is clear, however: different AI systems use different external sources.

Sustainable promotion therefore requires several types of platforms.

How to measure personal-brand promotion

Do not stop at a screenshot of one successful answer. It looks good in a presentation but says little about durability.

I would monitor at least 4 things.

Visibility

In what share of checked answers does the specialist appear at all?

Position

Being No. 9 out of 10 is different from being the first recommendation.

Sources

Where does the AI system get its supporting evidence? This is particularly useful because sources often show what the promotion is still missing.

Trend

Compare periods. Answers to the same prompt can change even during one day, so conclusions are better based on a series of measurements.

What an expert ultimately needs to do

If the entire guide is reduced to a working sequence, it looks like this.

Step 1. Describe yourself

Specialization, biography, achievements, services and prices.

Step 2. Build your own website

It becomes the central source of information.

Step 3. Find and correct information about yourself online

Remove contradictions.

Step 4. Create and complete the main external profiles

Maps, professional platforms and directories.

Step 5. Start collecting reviews systematically

Especially substantive ones.

Step 6. Publish case studies

With facts and numbers.

Step 7. Find real user intents

What your potential clients actually ask AI systems.

Step 8. Run a baseline measurement

Who already appears and which sources are being used?

Step 9. Publish expert materials

On your own website and strong external platforms.

Step 10. Measure results and repeat the cycle

See which sources started working, where visibility improved and which intents need further reinforcement.

Conclusion

Promoting a personal brand in AI is in many ways similar to building a professional reputation properly.

The difference is that now the reputation must be readable and correctly assembled not only by a person. An AI system must understand it too.

Being an excellent specialist with satisfied clients is not enough.

Your experience needs to become accessible facts: biography, services, case studies, reviews, articles, speaking engagements, profiles and other documents. These facts should agree with one another and clearly refer to the same person.

Then GEO begins: studying intents, monitoring recommendations, analyzing sources and systematically strengthening the signals AI systems still lack.

My own experiment showed that this works: during the first month, visibility for a competitive GEO intent grew from roughly 22% to 48%, and in the control measurement I reached No. 1 in ChatGPT, Google AI Mode and Yandex Search with Alice.

The full experiment, trend chart and specific sources are collected in the Alexey Yakovlev GEO case study.

There is no final stopping point.

As new publications, competitors and sources appear, recommendations will change.

Personal-brand visibility in AI is therefore no longer a one-off optimization of a profile or website. It is ongoing work on your public expertise.