What actually determines whether AI search mentions your B2B brand
AI answer engines cannot be controlled, but the evidence they draw on can be improved. A practical breakdown of the factors B2B companies can influence.
Generative Engine Optimization (GEO)
B2B buyers increasingly research problems, categories and vendors through AI assistants and AI-generated search answers. We help your brand become easier for those systems to discover, understand, trust and reference.
Role in the growth system
Discipline group: Search & Authority

AI search does not replace search engine optimization. It changes what visibility means. Instead of ten links, a buyer may see one synthesized answer that names a handful of vendors, cites a few sources and ignores everyone else.
No one can control what a language model says. What you can influence is the evidence those systems find: how clearly your company is described, how consistently it is corroborated elsewhere, and how easy your content is to retrieve and quote.
What has changed
In a traditional results page, a buyer chooses which sources to read. In an AI-generated answer, the system has already chosen — and often summarized your category, named the vendors worth considering and framed the trade-offs before the buyer visits a single website.
For B2B companies this matters most at two moments: when a buyer is trying to understand a problem, and when they ask which solutions to consider. Being absent, misdescribed or described only by competitors at those moments is a real commercial cost.
How answers are assembled
Different AI products work differently and change often. Broadly, answers that reference current information follow a pattern like this — and each stage is a point of influence.
Being honest about it
Scope
The companies AI systems describe well are usually the companies that describe themselves clearly — and are described consistently by others.
How we work
The problem, category, comparison and vendor-selection questions your buyers are likely to ask.
Record current mentions, descriptions, accuracy and cited sources across platforms.
Identify gaps in content, clarity, corroboration and technical access that explain the baseline.
Prioritize changes to your site, structured data and off-site presence by likely commercial impact.
Repeat the prompt set on a schedule. Treat changes as directional evidence, not guarantees.
Measurement
AI answers vary between sessions, users and model versions, so single observations mean little. We look for patterns across repeated tests and triangulate with commercial data.
How often you are mentioned or cited across the prompt set, and how that compares with competitors.
Whether AI systems describe your product, audience and differentiators correctly.
Visits from AI assistants and answer engines where referral data is available.
Branded search trends and “how did you hear about us” responses that mention AI tools.
Services are not silos
AI & LLM Search Visibility is one entry point into a wider growth system. These are the disciplines it most often depends on — and that often surface during the work.
Related insights
AI answer engines cannot be controlled, but the evidence they draw on can be improved. A practical breakdown of the factors B2B companies can influence.
AI Search · Explainer
What GEO is, how AI answer engines assemble responses, which factors B2B companies can influence, and how to measure AI search visibility without overstating it.
Questions
GEO is the practice of improving how a brand and its content are discovered, understood and cited by generative AI systems, including AI assistants and AI-generated search answers. It builds on SEO fundamentals and adds a focus on entity clarity, retrievable content structure and third-party corroboration.
It overlaps substantially. Many AI answer systems retrieve information from search indexes and the open web, so strong SEO remains a foundation. The differences are in emphasis: how explicitly your content answers questions, how consistently your brand is described across sources, and how visibility is measured.
No. Nobody can guarantee what an AI system will say. We improve the evidence available to those systems and measure the effect over time. Anyone promising guaranteed AI placement is promising something they do not control.
llms.txt is a proposed convention, not an established standard, and there is limited public evidence that major AI products rely on it. It is inexpensive to add, and we will implement it where it makes sense, but it is not a strategy on its own.
With a fixed set of buyer prompts tested repeatedly across platforms, recording mentions, descriptions and citations. We combine that with AI referral traffic, branded search and self-reported attribution, and we treat the results as directional rather than precise.
Start a conversation
Start with a conversation about your category, your buyers and the questions they are asking. We will tell you what we would test first.
Prefer email? hello@definitegrowth.com