The share of all brand mentions inside AI-generated answers that belong to your brand versus competitors. For agencies, it is the headline metric that proves whether AI visibility work is actually paying off.
Also known as AI SOV, AI visibility share, share of model
AI Share of Voice measures how often a brand gets named in AI assistant answers compared to its competitors. You take a fixed set of buyer questions, run them through assistants like ChatGPT, Gemini, and Perplexity, count every brand mention across the responses, and express your brand’s slice as a percentage of the total. If your brand is named in 30 out of 100 tracked answers and all brands combined are named 100 times, your AI Share of Voice is 30 percent.
It is the AI-era cousin of the share of voice marketers have tracked in advertising and search for decades. The difference is the surface. Instead of measuring presence in paid impressions or a list of blue links, it measures presence inside the synthesized answer an assistant gives a buyer who asked for a recommendation. As more research starts with a chatbot, that slice of the answer becomes the thing worth measuring.
For two years agencies have done AI visibility work with no clean number to point at. AI Share of Voice is that number.
It makes invisible work reportable. Getting cited by an assistant used to be a vague win. A tracked percentage turns it into a metric you can put on a dashboard and defend in a renewal conversation.
It is competitive by design. Because it is measured against rivals, it answers the question clients actually ask: are we winning the AI recommendation, or is a competitor getting named first?
It points to the next action. When you can see which questions you lose and which sources the assistant cited instead, you know exactly what content to build and which publications to earn, rather than guessing.
A B2B software client wants proof that their AI optimization spend is working. The agency builds a tracked set of fifty real buyer questions, things like “best CRM for field sales teams,” and runs them across ChatGPT, Gemini, and Perplexity every week, counting how often each brand is named and recommended. The client starts at twelve percent AI Share of Voice, trailing two competitors who keep getting cited first. Over the next quarter the agency restructures the client’s comparison pages, earns mentions on the review sites the assistants lean on, and tightens the product’s positioning language. By the quarterly review the client sits at thirty-one percent and leads the category. That single number, not a keyword position, becomes the headline of the business review, and it is the clearest evidence the retainer has paid for itself.
The automations and agents module of the workshop teaches you how to build AI workflows that compress the busywork without taking the craft out of the studio.