In the last two years the gesture of searching has changed. You no longer type a keyword and choose among ten links: you ask ChatGPT, Gemini, Perplexity or Google's AI Overview and read an answer.
This is true in industrial B2B as well. The purchasing manager, the technical director, the CEO — increasingly the first search is done with a conversational assistant, not a search engine. And when they talk to you, they already come with a short list someone else wrote for them.
The question every company should ask today is no longer "am I on Google's first page?" but: "when AI answers a question about my market, does my name appear?"
From link list to single answer
A traditional search engine returns options and leaves the user to choose. A generative engine does the work for them: it reads sources, synthesizes, chooses who to cite and returns a reasoned answer, often with two or three company names inside.
The consequence is stark. In classic search there are ten positions and a long tail of residual visibility. In a generative answer there are very few slots, and if you're not in, you're not second: you simply don't exist for that user. There is no page two.
That's why a discipline of its own has emerged, GEO — Generative Engine Optimization: the set of activities that make a company readable, citable and recommendable by generative AI systems.
Why generative engines don't work like Google
They don't rank pages, they build statements
Google ranks documents. A generative model recomposes fragments from different sources to build a sentence that is true and useful. It doesn't reward the "optimized" page: it rewards content that states something clear, verifiable and easy to extract.
Third-party sources matter as much as your site
Your site is only one source, and for the model it's also the least neutral. Industry directories, vertical publications, trade associations, marketplaces, fairs, LinkedIn, reviews and public papers weigh heavily. Visibility in AI is gained inside and outside your domain.
Identity consistency matters
Models work by entity: company name, sector, products, HQ, key people. If your legal name is written five ways, the system struggles to associate you reliably.
There is no stable position
Two users asking the same question can get different answers. You don't measure a "position": you measure citation frequency over a set of real questions, repeated over time.
Click is no longer the unit
Many answers end in the conversation: the user never visits your site but leaves with an opinion about you. Traditional analytics doesn't see it.
The factors that decide if AI cites you
- Clarity and structure. Explicit answers to explicit questions, self-contained paragraphs, stated data.
- Real question coverage. Not keywords: the questions your customer actually asks AI.
- Authoritative third-party presence. Trade press, vertical directories, signed content, partnerships.
- Identity data consistency. Same names, descriptions, references everywhere; structured data on site.
- Technical accessibility. Content reachable by AI crawlers, no involuntary barriers.
- Proof. Cases, numbers, references, certifications.
The EGTEK system: AI measurement and hands-on support
EGTEK's Communication unit has built a structured, replicable system: a method that applies the same way to a manufacturer, a service company or a local business. Four phases:
1. AI visibility audit
We build the set of questions your customers really ask — by problem, product category, geography, competitor comparison — and query them systematically on the main generative engines through a proprietary AI tool. Result: a snapshot of how many questions you appear in, how AI describes you, which sources it cites, who appears instead of you.
2. Action plan
From the snapshot a prioritized list: content gaps, errors to fix at source, third-party sources to cover, technical and identity corrections.
3. Production and coverage
Content is written, published and distributed where models actually read. We don't produce volume: we produce citable material.
4. Continuous monitoring and hands-on support
AI answers change: coverage must be maintained. We re-measure the same question set at regular intervals with a dedicated contact — tool to measure, people to decide.
How we measure result
- Coverage: on how many relevant questions the company is mentioned.
- Citation share: how much space vs competitors.
- Accuracy: how correct and up-to-date AI's statement is.
- Contact quality: how many prospects arrive pre-oriented and how much the sales cycle shortens.
Want to know what AI says about your company?
We run the AI visibility audit on your market and discuss it on a call.
Let's talk — a call to understand if the topic is relevant to your growth phase.
Let's talk