AI Positioning

You measure the effectiveness of AI positioning differently from classic SEO - instead of a Google ranking, what counts is your brand's share of AI responses. The core metrics are the number of times your site is cited in language-model answers, the number of brand mentions, and share of voice - your share of AI responses relative to competitors.

In practice we monitor several things:

• which questions your brand appears on in ChatGPT, Gemini, Perplexity and Google AI Overviews,
• in what context you are cited - as a source, a recommendation or a mention,
• how your visibility changes over time and how you compare with competitors,
• which pieces of content end up in AI answers most often.

Classic ranking reports do not show this traffic, which is why we combine AI SEO measurement with search data - since 65.9% of citations in AI Overview come from the TOP 3 organic results, we track Google positions and presence in AI answers together.

You optimise content for language models so that AI easily grasps its meaning and treats it as a credible source worth citing. The question-and-answer format works best - with a specific answer placed at the start of the section, plain language and a logical structure of H2 and H3 headings.

In practice, AI-ready content:

• answers the real questions users ask, not elaborate keyword phrases,
• opens each section with a concise, specific answer the model can quote,
• is semantically coherent and covers the subject thoroughly rather than superficially,
• rests on data, sources and real experience in line with E-E-A-T.

ChatGPT, Gemini and Perplexity pick their sources slightly differently, but they all reward the same things: clarity, expertise and context. So we do not write "for the algorithm" - we create content a human and a language model will understand equally well.

E-E-A-T stands for Experience, Expertise, Authoritativeness and Trustworthiness. It is the set of signals search engines and AI models use to judge whether content is reliable and trustworthy. The higher your E-E-A-T, the greater the chance artificial intelligence will cite your site in an answer.

Language models cite sources they trust, which makes E-E-A-T one of the key filters in AI SEO today. We build it through:

• content backed by data, sources and real experience,
• clear authorship and an expert publishing context,
• brand presence in credible, industry sources,
• a coherent thematic cluster around your core entity.

E-E-A-T signals do not work overnight - this is authority built consistently. But trust, once earned, is hard to take away, and it is exactly what decides who gets cited in AI responses and who gets left out.

AI crawlers are the bots that visit your site and fetch its content so language models can use it in their answers. If a crawler cannot reach the content or cannot understand it, your site has no chance of appearing in AI responses - which is why technical availability is the foundation of the whole strategy.

So that AI models read your site smoothly, we look after:

• content availability to AI crawlers (GPTBot, Google-Extended, PerplexityBot among others) and correct robots settings,
• page load speed and good Core Web Vitals,
• a clean HTML structure and a clear H1-H2-H3 heading hierarchy,
• correct indexation and schema.org structured data, which explains the context of the content to machines.

Technical optimization for AI crawlers is work "under the hood" - users never see it, but without it the rest of the AI SEO work will not deliver. It is the price of entry into the race for citations.

AI positioning makes sense wherever customers look for information and compare offers before deciding - and today they increasingly do that in ChatGPT, Gemini, Perplexity and Google AI Overviews. The biggest winners are industries where a purchase is preceded by research and where trust in the source genuinely affects the choice.

We see the greatest potential in:

• e-commerce and online stores - 55% of consumers use generative AI to research products,
• expert and regulated services (law, finance, medicine), where authority and credibility count,
• local industries - 96.03% of citations in Polish AI Overview come from local, Polish-language sources,
• B2B sectors and technical niches, where the customer is after a specific, exhaustive answer.

In practice, AI positioning works in any industry where it pays to be cited as a credible source. The bigger the role research plays in a customer's decision, the more you gain from being present in AI responses.

A brand entity is the coherent, unambiguous "thing" AI models recognise as your company - together with what you do, what you are an expert in and which subjects you are associated with. Artificial intelligence does not think in single keywords but in entities and the relations between them, so a well-defined entity increases the chance that it is your brand the model cites in its answer.

We strengthen the brand entity through:

• a consistent description of the company and its specialisation across every source (site, listings, publications),
• a thematic cluster around one well-defined entity rather than loose, unrelated content,
• structured data (Organization and NAP among others) that tells machines unambiguously who you are,
• mentions and citations in credible, industry sources that build your authority.

The clearer and more consistent the entity, the more confidently AI associates your brand with a given subject - and that translates into citations. A strong entity works like an address where artificial intelligence will always find a credible answer related to your industry.

AI-generated content is not penalised in itself - the problem is low quality, not the tool. Language models and Google AI Overviews judge whether content is comprehensive, expert and credible, not whether AI helped produce it. Text produced en masse, unsupervised and without value does lower the chance of being cited, though - because artificial intelligence prefers reliable sources.

That is why we treat AI in SEO as support, not as a replacement for an expert:

• we use AI to analyse data and produce content at scale,
• but every text goes through expert review for relevance and E-E-A-T compliance,
• we verify facts, sources and originality instead of publishing raw model output,
• we bet on quality and context, not on the sheer number of generated words.

The AI SEO audit also checks the risks attached to machine-generated material published without supervision. The conclusion is simple: AI speeds the work up, but it is expert, polished content that decides whether artificial intelligence cites your site in particular.