AI share of voice is the percentage of AI-generated answers to a defined set of buyer questions that name your brand, measured per engine, over a stated sample. Some people have started calling it share of model; same idea. It is the successor to a metric marketers have carried for a century: share of voice once meant your slice of the ad space, then your slice of the search results, and now it means your slice of the answers. This page is the definition, the formula, the honest way to measure it, and the three ways the number gets faked.
Why this metric exists
A growing share of buying research ends inside an answer instead of on a results page. ChatGPT, Claude, Perplexity, and Google's AI results name a handful of brands per question, and every answer that skips you is a room your competitor had to themselves. Traffic cannot measure this, because there is no click to lose. Rankings cannot measure it, because generated answers have no stable positions. What can be measured is presence: of all the times the machines answered your buyers' questions, how often were you in the answer? That is AI share of voice.
The formula
AI share of voice = answers naming your brand ÷ total sampled answers × 100, computed per engine.
A worked example, at the scale a real measurement needs: take 25 buyer questions, ask each one 8 times across 3 engines, and you have 600 sampled answers. If your brand appears in 84 of them, your AI share of voice is 14 percent. If your nearest competitor appears in 210, theirs is 35 percent, and now the number means something: not "we are invisible" but "we hold 14 against their 35, and here are the exact questions where the gap lives."
Three definitions keep the counting honest, because being in an answer happens at three different strengths:
- A mention. Your brand is named in the answer. The baseline unit.
- A citation. Your page is linked as a source the answer stands on. Stronger: the machine built its answer out of you.
- A recommendation. You are named as the pick. The strongest form, and the one deals follow.
A share of voice built by blending these into one number flatters everyone. Count them separately and the metric starts telling the truth.
What makes the number honest
The same discipline as any real AI visibility measurement: AI answers are non-deterministic, so a single run is an anecdote. The honest version states its sample size on the page, samples across days rather than in one burst, reports each engine separately because they behave differently and serve different buyers, and keeps the raw answers so every count can be re-derived. A share of voice without a sample size is a vibe wearing a percentage sign.
The three ways the number gets faked
- The screenshot. One conversation, one engine, one day, presented as a state of the world. Answers vary run to run; a screenshot is one coin flip sold as a probability.
- The blended average. One number across all engines. If ChatGPT names you constantly and Perplexity never does, the average hides exactly the fact you needed, because those two engines are read by different buyers on different questions.
- The generous count. Citations, mentions, and passing references all counted as presence. If the answer named you as "an alternative some users mention," you were mentioned; you were not recommended. The difference is the deal.
What moves it
Slowly and measurably: being the canonical answer for specific questions your buyers ask, which is publishing and positioning work, not a trick; presence on the third-party pages engines actually cite; and defending your branded questions first, since a wrong answer about you by name loses deals you had already won. The starting point is always the same: a measured baseline, because a share of voice can only be claimed to have moved if someone froze where it started.
What AI share of voice is not
- Not a rank. There is no position two inside a generated paragraph.
- Not traffic. The metric exists precisely because the lost deals leave no click behind.
- Not one number. It is a set of numbers, per engine, per question group, with a date on each.
Common questions
What is a good AI share of voice? Category-dependent, and mostly the wrong question. In young categories the machines often name almost nobody, so the first brand to earn consistent mentions can hold a majority of the answers that name anyone. The right question is trajectory: your number this month against your dated baseline, per engine.
How is AI share of voice different from mention rate? Mention rate is per question: of N samples of one question, how many named you. Share of voice aggregates across the whole question set and includes the field: who else is in the answers, and how often. One diagnoses a question; the other describes a market.
Which tools measure AI share of voice? Self-serve trackers run roughly $29 to $500 a month; the full market pricing is documented here. The method matters more than the tool: whatever you use, the number should arrive with its sample size, its engines, and its dates printed next to it. Ours do.
To find out your number, write to daksh@khannasllc.com with your domain in the subject line. That is the entire intake process.