What is AI visibility?

Why it matters now

For twenty years, being discovered online meant ranking in Google's ten blue links. That model is changing. A growing share of buying research now happens inside AI chat interfaces, where the question "best CRM software" becomes "what's the best CRM for a startup like mine?" — and the response is a single synthesized answer naming three to five brands.

There is no page two of an AI answer. Brands that aren't named don't rank lower; they simply don't appear. For any business that depends on organic discovery — SaaS, e-commerce, agencies, local services — this is a new channel that can't be seen through traditional SEO tools, because rank trackers measure links, not answers.

How AI assistants decide what to recommend

AI recommendations are shaped by two layers. The first is the model's training data: the accumulated text of the web, where brands that are widely discussed, reviewed and compared are more strongly represented. The second, increasingly dominant layer is live retrieval: when you ask a modern assistant a buying question, it searches the web and builds its answer from the sources it finds and trusts — review platforms, comparison articles, community discussions, and industry publications.

This second layer is the practical lever. If the sources an AI engine cites for your category consistently mention your competitors and not you, the answer will too.

How AI visibility is measured

Because AI answers are generated fresh each time, a single check proves nothing — the same question can produce different brand lists across runs. Meaningful measurement requires sampling the same questions repeatedly across engines and scoring on frequency. The core metrics are:

• Mention rate — the share of sampled answers, across your category's buying questions, in which your brand appears.
• Answer position — where you appear when mentioned; being named first carries far more weight than being an afterthought.
• Share of AI voice — your mention rate relative to competitors across the same questions, showing who "owns" the category's answers.
• Citation presence — whether your website itself is cited as a source, distinct from your brand being named.

These roll up into a single AI Visibility Score that can be tracked over time. You can read exactly how we compute ours on our methodology page.

How to improve AI visibility

The most reliable known lever is closing citation gaps: identifying the specific sources AI engines already cite in your category — review sites, comparison pages, communities — that don't mention your brand, and earning presence there. Beyond that, clear and factual on-site content (what you do, who it's for, how you compare) helps engines represent you accurately, and genuine authority signals — reviews, coverage, community discussion — compound over time.

This discipline is sometimes called GEO (Generative Engine Optimization) or AEO (Answer Engine Optimization). Whatever the name, the loop is the same: measure where you stand, fix the highest-impact gaps, and verify the score responds.