AI share of voice: the formula and a worked example
By Vladimir Boldyrev · LLMBrandScan · Published July 21, 2026
The formula
AI SoV = (your brand's mentions ÷ total brand mentions in the sample) × 100
It's the same arithmetic as classic advertising Share of Voice, applied to a different kind of “voice” — how often each brand gets named across a sampled set of AI answers, instead of how much ad spend or media coverage each brand commands.
A worked example
Say you run 10 category questions (“best expense-tracking app for freelancers,” etc.) across 5 engines, 3 samples each — 150 total AI answers. Across those 150 answers, brands get mentioned a combined 210 times (some answers name more than one brand; some name none). Your brand is named 42 times.
| Brand | Mentions | AI SoV |
|---|---|---|
| You | 42 | 20% |
| Competitor A | 63 | 30% |
| Competitor B | 46 | 22% |
| Everyone else | 59 | 28% |
42 ÷ 210 = 20% AI Share of Voice — behind Competitor A's 30%, ahead of Competitor B's 22%. That single number is a snapshot; the useful version reports it as an observed range (e.g. “18-23% across this sample”) with a Strong / Emerging / Noisy signal label, since a different sample of 150 answers would land somewhere nearby but not identical.
Where the concept comes from
AI Share of Voice is the percentage of brand mentions, across a set of sampled AI answers in a category, that belong to a given brand — calculated as that brand's mention count divided by the total mention count of every brand named across the same sample, summing to 100% across the full competitive set. It is a direct adaptation of the classic marketing metric Share of Voice, and echoes Les Binet's Share of Search (a brand's search-query volume divided by total category search volume), which the IPA's EffWorks research showed could predict market-share movement roughly a year ahead for some categories. AI Share of Voice inherits that positioning: a fast, sampled, behavioral proxy for standing in a category — not a survey of what every buyer sees, and not a claim about actual market share, only a leading indicator drawn from AI answers.
Why this metric specifically is worth tracking
Unlike raw mention count, Share of Voice is inherently comparative — it tells you your standing relative to competitors in the same category, not just whether you showed up at all. Paired with first-mention rate (which brand a model names first), it's the closest AI-native equivalent to the “excess share of voice predicts future market-share growth” relationship classic marketers already rely on. See a full worked report in our sample scan.
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