Imagine a potential customer skipping a traditional search engine and asking ChatGPT, “Who provides this service in Latvia?” The answer names three companies and gives a short reason for each. Yours is not among them. Changing that requires more than website settings: the company needs a clear story and credible sources that an AI system can discover.
From a list of results to a finished answer
Traditional search usually offers a list of links and lets the user choose. AI search tools can collect information from multiple sources, synthesise it, and present a conclusion immediately. A company therefore needs to do more than earn a position on a results page; it needs to become a clearly understood and credible source.
“The SEO question was how to reach the first page. The AI visibility question is how to become a credible source when the user receives the answer directly.” — Helmuts Medinieks
SEO still provides the foundation. Google’s own guidance for AI search features says that established technical and content-quality practices continue to apply and that no special AI file or markup is required.
Why the company website is not enough on its own
The website is the company’s primary source. It should accurately explain the offer, experience, evidence, and answers to customer questions. But what a company says about itself is not independent validation.
A trade publication, a named expert comment, a guest article, or a podcast with a published transcript adds outside context. Several relevant sources can help connect a company with a specific topic. That is why expert content and public relations complement website and SEO foundations in AI visibility work.
What GEO research says about content
The paper GEO: Generative Engine Optimization, accepted at KDD 2024, systematically tested how content changes affected source visibility in generated answers.
Under the study’s experimental conditions, GEO methods improved source visibility metrics by as much as 40%, although results varied by domain and query type. Citing authoritative sources, adding relevant quotations, and using concrete statistics performed well, while mechanical keyword additions did not improve results.
This is not a universal promise that one tactic will produce a 40% gain for every company. The useful conclusion is narrower: specificity, evidence, and sources can help, but the approach must fit the market.
What this means in practice
First, define what makes the company different
If the value proposition could describe every competitor, an AI tool has no clear reason to distinguish this company. “Quality services, a personal approach, and an experienced team” are too broad. Start with a specific customer problem, solution, market, and evidence.
Make the company description consistent
Create one core description and apply it across the website, LinkedIn, Google Business Profile, directories, and media materials. Every sentence need not be identical, but the company category, offer, and main expertise should not contradict one another.
Create content people can understand and verify
Choose questions customers genuinely ask and answer them directly. Use clear headings, short complete paragraphs, specific examples, dates, named authors, and links to credible sources. “The process takes six to eight weeks” is more informative than “the process is fast.”
There is no need to invent an “AI writing style.” Google says its AI search features require no special structured data or text format. Useful, people-first content remains the foundation.
Build visibility beyond your own website
Trade media, expert commentary, guest articles, partner publications, podcast transcripts, and thoughtful comparisons can build external credibility. Select sources that are genuinely relevant to the company’s subject and audience, and keep the company name and expertise consistent.
Measure repeatedly
Create five to ten commercially relevant customer questions. Test them monthly in ChatGPT, Gemini, Claude, and Perplexity, recording mentions, descriptions, cited sources, and competitors. Also verify that the website’s technical settings allow access to the bots used for search.
Three things not to rely on
One “AI optimisation” file. No single file makes a website visible in AI answers. Google explicitly says its AI search does not require special files or markup. Quality content and technical accessibility matter more than an experimental checklist.
Mass-generated content. Article volume alone does not create authority. A smaller body of original material grounded in company experience, data, and expert judgement is more useful.
Guarantees. Nobody can guarantee a particular mention or position in an AI answer. Systems, indexes, and answers change. The work can strengthen the underlying conditions and measure a trend, not promise a fixed outcome.
The context of smaller-language markets
Smaller languages have fewer high-quality industry sources than English. That creates both a constraint and an opportunity: strong local content can become an important reference point sooner, while an English version can broaden the context in which the company is found.
Both languages should tell the same company story. The wording can be adapted to each audience, but the offer, expertise, and central facts should not conflict.
Frequently asked questions
Short answers about content and PR
How long does AI visibility work take to show results?
A meaningful trend usually forms over months rather than days. Timing depends on the starting point, competition, publishing pace, and source quality, so progress should be measured regularly.
Is SEO no longer necessary?
It is still necessary. Technical access, indexability, and useful content remain foundational. AI visibility work adds clearer positioning, author credibility, and relevant external sources.
Are structured data enough?
No. Accurate structured data can help systems understand a page, but they do not replace real information, evidence, and a credible external presence.
Where should a company start on a limited budget?
Check bot access, standardise the core company description, and create a small number of strong pages that answer priority customer questions. Then choose one or two relevant formats for external publication.
Summary
AI visibility is not a new technical channel that can simply be switched on. It grows from clear positioning, useful expert content, credible external mentions, a technically accessible website, and repeated measurement. Improving these foundations helps people and AI systems find, understand, and more confidently recommend a company.
If the company still does not appear in answers, review the seven common AI visibility mistakes.