AI Visibility Glossary

Share of Model

Share of model is the percentage of AI-generated answers that name or recommend your brand instead of competitors across a defined prompt set — the generative-era successor to share of voice. The formula: your weighted brand mentions divided by total eligible mentions, multiplied by 100, measured where ChatGPT, Gemini, and Perplexity compose each answer.

Last updated: 2026-07-22 · Definition · by Italo Campilii
Definition

Share of model quantifies your brand’s slice of AI-generated answers — how often, and how prominently, an engine names and recommends you versus competitors across a defined prompt set.

What is share of model?

Share of model is your brand’s slice of the answer. As buyers shift from ten blue links to assistants, the response itself has become the new digital shelf space. When someone asks ChatGPT or Gemini for a recommendation in your category, share of model is how much of that answer belongs to you — and how much goes to rivals. Engines compose answers from a small set of sources they trust, so presence inside the response has to be earned in those sources first.

Acromatico blends Miami photography craft with AI studio precision to benchmark your share of model, surface citation gaps, and give engines clearer, better-sourced reasons to recommend your brand.

Why does share of model matter?

Most purchase journeys now begin with a question to an assistant, not a search box. If a model never names you, those buyers never see you — no matter how strong your classic rankings are. Share of model makes that invisible layer measurable, so you can compete where recommendations are actually formed, track whether your work moves the number, and prove you are landing inside the answer.

How do you calculate share of model?

Share of model = (your weighted mentions ÷ total eligible mentions) × 100

Worked example: across a 100-prompt set, all tracked brands earn 200 eligible mentions in total and 34 of them are yours — your share of model is (34 ÷ 200) × 100 = 17%.

Credible measurement documents three things up front: the prompt set, the named model versions, and the dates. Prominence weighting matters because a brand cited first and described in detail counts for more than a passing name-drop.

Because models update frequently and outputs vary with phrasing, treat share of model as a comparative metric — your visibility for specific prompts at a specific time, not a fixed market share. Track it on a schedule, against the same competitors, and the trend becomes the signal worth reading.

How do you improve share of model?

Close the gaps the measurement reveals:

Then re-run the same prompt set and compare. Share of model grows through iteration and evidence, not volume alone — the same measure-and-refine loop behind our AI SEO / GEO work.

How is share of model different from share of voice?

Share of voice measured your slice of search results and ad impressions; share of model measures your slice of AI-generated answers. The mechanics differ — search ranks pages, while models compose answers from the sources they trust — but both are comparative: your number only means something next to your competitors’, tracked on the same prompt set over time.

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