A page ranking concerns the page. An AI recommendation is a conclusion about the company. That is why growing SEO and paid traffic does not determine whether a system will identify the brand as the right choice. AI needs grounds to understand the company, verify its credibility and connect it with a specific customer situation.
Why doesn't AI recommend my company despite strong SEO?
SEO primarily answers the question: which page should be shown? Advertising buys exposure for a specific message. An AI recommendation answers a different question: which company should be recommended in this situation, and why that one?
A company can therefore rank well, generate clicks and run effective campaigns, yet still be absent from an answer to “Recommend a trusted company in my area”. This is not a contradiction. A search result organises resources, while an AI answer synthesises information and forms a conclusion about a brand.
SEO remains an important search visibility channel and helps content remain accessible to Google systems. However, it does not automatically mean that the company will be selected in an AI answer. Google explicitly states that even meeting requirements and best practices does not guarantee that content will appear in AI features. Source: Google Search Central.
Why does AI recommend competitors instead of my company?
Consistency: the system should recognise that scattered information refers to the same company. Simply being present online is not enough if the company's image is ambiguous or internally inconsistent.
Independent confirmation: a company's own statement shows how the brand describes itself. A recommendation has a stronger basis when the company's image is confirmed outside its own communication as well.
Expert knowledge: a company name makes the company findable, but concrete knowledge gives a reason to use it in an answer. A company can therefore be visible as an entity while remaining invisible as a competent source for a specific customer problem.
These three gaps look similar from the outside — the company is missing from the recommendation — but they represent different problems. Randomly increasing the amount of content or mentions may therefore fail to address the real cause.
If a company is already regularly recommended by different AI systems but still receives no enquiries, the problem may lie further along the customer journey — in the offer, trust or conversion rather than visibility itself.
How can I check whether AI recommends my company?
One answer is an observation, not a diagnosis. Generative systems can produce incomplete, variable or incorrect answers; OpenAI explicitly notes that language models can still generate convincing-sounding false information. Source: OpenAI.
That is why a company's visibility should not be judged by a single prompt or screenshot. What matters is a repeatable pattern of answers relating to real customer choice situations and the change observed over time. Only such a pattern makes it possible to distinguish a one-off result from a lasting problem.
What do the results of the KAN project for Serwis-Pro show?
We ran the first KAN project on our own business — the Serwis-Pro brand, which provides window and door service in Poznań and the surrounding area. Over six months we carried out three measurements using the same 14 questions across four AI systems
The share of answers explicitly recommending the company was 32.1% in the first measurement, 55.4% after three months and 75.0% after six months. These are results of the KAN project, while the measured indicators concern the visibility of the Serwis-Pro brand in AI answers. In the first measurement, 2 of the 4 systems tested recommended the company; after three months, 3 of 4; and after six months, 4 of 4. This result relates to a specific project, industry and market — it is not a promise of an identical result for every company
See the results of the KAN project for Serwis-Pro →
Where should you start to improve a company's visibility in AI?
The same symptom — a company missing from an AI answer — can result from an ambiguous brand image, insufficient confirmation, overly general knowledge or a combination of these causes. Starting with a ready-made package of actions would mean treating the symptom without identifying the problem.
KAN's task is first to determine exactly where the company is losing visibility, and only then build a direction of work that addresses the cause found. This does not replace SEO or advertising. It adds a new customer choice point to marketing — an answer formed before the customer visits a website or clicks an ad.
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