What Is Share of Voice in AI Search?

Share of voice in AI search is a metric that measures how often your brand appears in AI-generated responses compared to your competitors for a defined set of queries. If 100 people ask ChatGPT, Perplexity, or Google AI Overviews about topics relevant to your business, share of voice tells you what percentage of those responses mention or cite your brand versus competing brands.

Why Share of Voice Matters in AI Search

In traditional marketing, share of voice has long been a predictor of market share. Brands that are talked about more tend to sell more. The same principle applies to AI search - brands that AI models cite more frequently get more visibility, more referral traffic, and more implicit trust from users.

The difference is that AI search share of voice is a newer metric that most brands are not yet tracking. According to Search Engine Land, LLM-driven referral traffic grew 800% year over year, making AI share of voice increasingly important as a competitive metric.

For startups, measuring share of voice in AI search reveals opportunities that traditional metrics miss. You might discover that a competitor ranks above you in Google but never appears in ChatGPT responses for the same queries. Or you might find that your content gets cited by Perplexity for queries you had not specifically targeted.

How Share of Voice Is Calculated

The basic formula is straightforward:

AI Share of Voice = (Your brand mentions in AI responses / Total AI responses for target queries) x 100

In practice, the calculation involves several components:

Query set definition. You define a set of queries relevant to your business - typically 50 to 200 keywords covering your core topics. These should include both branded queries ("what is [your product]") and category queries ("best [product category] for startups").

Multi-platform measurement. AI share of voice should be measured across multiple platforms since each model may cite different sources. A brand might have strong share of voice in Perplexity but weak share of voice in ChatGPT. Monitoring across all major AI search engines gives you the complete picture.

Citation type tracking. Not all mentions are equal. A direct citation with a link carries more weight than a passing brand mention without a source link. Some tools differentiate between citation types to give a more nuanced share of voice score.

Tools for Tracking AI Share of Voice

Several platforms have emerged specifically to track share of voice in AI search:

Peec AI monitors AI-generated answers for your target keywords and calculates your share of voice compared to competitors across ChatGPT, Perplexity, Google AI Overviews, and other platforms.

Profound provides share of voice analytics and identifies the specific content and authority signals driving your competitors' AI visibility. Profound raised a $20 million seed round in June 2025 to expand their AI search analytics platform.

Otterly.ai tracks your AI brand visibility and provides competitive analysis showing how your brand's share of voice compares to competitors over time.

Semrush AI Visibility Toolkit integrates AI share of voice tracking alongside traditional SEO metrics, giving you a combined view of your search presence across both traditional and AI search.

How to Improve Your Share of Voice

Improving your AI share of voice requires consistent execution across content, technical, and distribution channels:

Publish authoritative content on your core topics. AI models cite sources that thoroughly and specifically address user queries. Cover your core topics deeply rather than broadly.

Include statistics and citations. The Princeton GEO research found that content with cited statistics saw up to 40% higher visibility in AI-generated responses. Every piece of content should include 2-5 data points with linked sources.

Build cross-platform mentions. AI models assess brand authority partly by how often your brand appears across the web. Active presence on Reddit, LinkedIn, and industry forums creates the web of references that strengthen your authority signal.

Update content regularly. AI search engines weight freshness heavily. A content refresh schedule - updating key pages monthly with new data and insights - keeps your content competitive for AI citations.

Monitor and respond to gaps. When monitoring shows competitors being cited for queries you should own, analyze their cited content. Identify what they have that you do not - whether that is specific data, clearer structure, or stronger authority signals - and create or update your content to close the gap.

Share of Voice Benchmarks

Because AI brand monitoring is a relatively new practice, industry-wide benchmarks are still forming. However, early data from monitoring platforms suggests:

• Category leaders typically achieve 20-40% share of voice for their core queries
• Strong contenders hold 10-20% share of voice
• Emerging players start at 1-5% and can grow to 10%+ within 3-6 months of focused GEO effort
• Absent brands are at 0% - meaning AI models never cite them for relevant queries

For startups, the most actionable benchmark is your own baseline. Measure your current share of voice, then track improvement over time as you publish optimized content and build authority signals.