What is an AI visibility score?
It is the headline number in most AI visibility tools. The name is shared, but the math is not. Two definitions, read on the vendors' own pages:
- Semrush: "A benchmark score (0–100) showing how often your brand appears in AI-generated answers compared to competitors" (Semrush, read 1 November 2026). Its metrics page does not explain the calculation.
- Peec AI: "The Visibility Score measures the percentage of AI responses that mention your brand", calculated as responses that mention you divided by total responses, times 100 (Peec AI docs).
So a Semrush score is an index relative to competitors, while a Peec score is a plain share of answers. A 40 in one tool and a 40% in the other are not the same thing.
How is an AI visibility score calculated?
| Semrush AI Visibility score | Peec AI Visibility Score | |
|---|---|---|
| Scale | 0 to 100 | 0% to 100% |
| What it measures | How often you appear, compared with competitors | Share of tracked answers that mention you |
| Formula published | Not on its metrics page | Yes: mentions divided by responses, times 100 |
| Source | Semrush KB | Peec AI docs |
Read on each vendor's site, 1 November 2026.
Some first-party tools give no score at all. Bing Webmaster Tools reports counts, such as total citations and cited pages, and says its average cited pages figure does not indicate "ranking, authority, or the role of any page within an individual answer" (Bing, 10 February 2026).
Why does an AI visibility score matter for B2B SaaS?
It gives a team one number to report each month and a trend line to watch. That matters as buying moves into AI chats. G2's 2026 survey of 1,076 B2B decision-makers found that 51% of B2B software buyers now start their research in an AI chatbot more often than in Google.
The score is only as good as the prompts behind it. If the prompt set does not match what your buyers ask, a high score can still mean you miss the questions that lead to a sale.
What does an AI visibility score look like? (hypothetical example)
This example is hypothetical, using a Peec-style percentage. A team tracks 200 answers a month. 46 name its product, so the score is 23%. The next month it adds 50 new prompts about a feature it is weak on, and the score drops to 19%. Nothing changed in the market. Only the prompt set did. Keep the set fixed, and add new prompts as a separate group.
How should you read an AI visibility score?
- Compare it only with itself over time, in the same tool, with the same prompts.
- Read it next to AI share of voice: a high score with a low share can mean every answer names many brands.
- Look at the sources behind the answers, not only the number. Most come from pages you do not own. Foundation and AirOps looked at 5.1 million AI responses for 50 B2B brands. On category questions that did not name the brand, only 2.24% of citations went to the brand's own pages.
- Expect noise. Answers also change from run to run. In Prefer's study of 960 answers (measured 13 September 2026), two runs of the same question overlapped by 37% in the sites they cited on ChatGPT and 35% on Gemini, against 96% on Perplexity.
AI visibility score vs AI visibility
AI visibility is the idea: how present your brand is in AI answers. The score is one tool's attempt to put a number on it. AI visibility tracking is the process of measuring it. Tools that report a score are compared in the best AI visibility tools, and the LLM SEO guide covers what to do with the results.