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AI visibility is how often, and how prominently, AI assistants such as ChatGPT, Gemini or Claude name a brand when people ask about its category. It is a property of answers, not of rankings or traffic: a brand is visible when it appears in the text the assistant writes, and more visible when it is named first, or named across many different buyer questions.
Outside marketing, "AI visibility" also means ML observability: monitoring what a deployed model is doing, its drift, its latency, its failure modes. Both meanings are in use and the models themselves mix them up. In our own study, gpt-4.1-mini answered "best AI visibility tools" with ML observability tools (Weights and Biases, Fiddler, WhyLabs, Arize) in 49 of 50 runs, while Gemini named brand-visibility tools (Otterly, Profound, Peec, Semrush) in 31 of 50.
Because of that, on this site we say "AI search visibility" or "brand visibility in AI answers" whenever the short phrase could be misread, and we keep "AI visibility" for contexts where the brand meaning is already clear.
When a buyer asks an assistant for a shortlist, the answer is the shortlist. There is no second page of results and no position ten. A brand that is not named in the answer is not in that buyer's consideration set, whatever its search ranking is. AI visibility is the measurement that tells a team whether that is happening, on which questions, and against which competitors.
The audit reads a brand's own site, derives the questions its buyers would ask, sends those questions to three model APIs without web search, and counts in how many answers the brand is recommended without having been named in the question. The result is reported as counts with their total, such as "recommended in 3 of 12 open questions", and as a three-band verdict. There is no 0 to 100 score on screen, because a single number hides the variation between runs. The full method is on the methodology page.
Measured
49 of 50
runs in which gpt-4.1-mini answered "best AI visibility tools" with ML observability tools, not brand-visibility tools.
How it was measuredNo. SEO is about where a page ranks in a list of links. AI visibility is about whether a brand is named inside a generated answer. The same content can help both, but the measurement is different: one counts positions, the other counts mentions across answers.
Only by name. ML observability monitors how a model behaves in production. Brand visibility in AI answers measures whether a brand shows up when people ask assistants about its category. When a search for "AI visibility tools" returns Arize or WhyLabs, that is the observability meaning.
No. One prompt is one sample of one question. Visibility is a map over the questions buyers actually ask, and each question needs more than one run before the answer can be trusted. See the pages on buyer-intent prompts and on how many runs are needed.
Other definitions
The free audit reads your site, derives your buyer questions and measures them on three model APIs. No signup, no card.