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What is AI share of voice?
AI share of voice is the proportion of generative responses that mention your brand among all mentions of players in your sector across the same prompt set. If on 100 sector-related prompts LLMs cite your brand 20 times, competitor A 35 times, and competitor B 15 times, your AI share of voice is approximately 28% of total mentions. It's a relative, competitive metric: it doesn't just tell you if you're present, but what position you occupy in the landscape AI describes for your sector.
Why AI share of voice matters in 2026
In a world where a growing share of purchase decisions involve a research phase via LLMs, AI share of voice represents your brand's visibility in prospects' consideration journey. A prospect asking Perplexity "what are the best X solutions in my sector" will receive a response directing them toward 3 to 5 brands. If you're not among them, you don't exist in that journey. AI share of voice is also more stable than SEO share of voice: Google positions vary daily, while LLMs' citation preferences evolve more slowly and respond more to foundational authority than short-term tactics.
What we observe at Vydera on sector benchmarks
The first AI share of voice benchmarks we conduct almost always reveal a correlation between a brand's informational density on the web and its AI share of voice. Players who produce the most structured content on the right questions, who have the most mentions in authoritative sources, dominate this share. And SEO market leaders aren't always AI share of voice leaders. This is one of the most interesting opportunities for secondary players who want to gain visibility without the market leader's SEO authority.
How to measure your AI share of voice
- Define a sector prompt set: the typical questions your prospects ask LLMs to find solutions like yours.
- Test these prompts on major LLMs and list all brands cited in each response.
- Calculate the number of mentions per brand and divide by total mentions to get each one's share.
- Track monthly evolution and analyze prompts where you're absent: these are your priority action areas.
Sources and references
Go further
We conduct AI share of voice benchmarks for our clients. To find out where you stand against competitors in AI responses, contact us. Our analyses are on Vydera Lab.
Is AI share of voice stable over time?
More stable than SEO share of voice, but not fixed. LLMs are updated, their training corpora evolve, RAG systems access recent content. An AI share of voice builds slowly and degrades slowly, except in the case of a major model update or a radical change in a competitor's content production. That's why monthly measurement generally suffices to track trends.
On how many LLMs should you measure your AI share of voice?
At minimum on the 3 main ones: ChatGPT (with and without web), Gemini, and Perplexity. Each model has its own sources and citation biases: your share of voice can be very different across platforms. Adding Claude and Google AI Overviews gives a more complete picture. The key is to identify the LLMs where your sector is active and concentrate measurement and actions on those platforms.
AI share of voice vs AI citation rate: what's the difference?
AI citation rate is an absolute metric: how often you're cited on a prompt set, independent of competitors. AI share of voice is a relative metric: what share of total citations in your sector you receive. Both are complementary. Citation rate measures your absolute visibility level; share of voice situates that visibility in the competitive landscape.
Can you improve your AI share of voice quickly?
On LLMs with real-time web access (Perplexity, ChatGPT web, Gemini grounded), well-structured, published, and indexed content can generate visible improvements in 4 to 8 weeks. On models without web access, changes happen during model updates, which is less controllable. The most effective strategy: saturate the informational space with structured content and authoritative mentions to be present in both real-time RAG and upcoming training corpora.
