What is AI visibility?
Your customers are asking ChatGPT, Gemini, and Perplexity to recommend businesses like yours. This page explains what drives the outcome and what you can do about it.
From search to recommendation
A decade ago, getting found meant ranking on Google. Today, a growing share of discovery happens through AI engines. Someone asks ChatGPT "who is the best accountant in Manchester?" and gets three names back, no links required. Whether your business is one of those three names is your AI visibility.
Unlike search rankings, which are binary (you rank or you don't), AI visibility is a spectrum. A business can appear in every response but always third, or appear in only half of responses but always first. The AI Visibility Score captures both dimensions: how often you appear, and how prominently.
Why it matters now
Gartner projected that traditional search engine volume will decline by 25% by 2026 as consumers shift to AI assistants for discovery and recommendations. Research from Princeton's KDD 2024 showed that businesses cited in AI responses receive significantly higher consideration rates than those found through traditional search. Users treat AI recommendations as curated advice rather than paid placements.
For most local and professional services businesses, the window to establish AI visibility before competitors do is now. Early movers earn a compound advantage: the more you're cited, the more authoritative sources mention you, the more you're cited.
How AI decides who to recommend
AI engines go through four stages when answering a recommendation query:
Retrieval
The engine pulls candidate information from its training data, its knowledge base, or via live web retrieval (depending on the engine and mode).
Ranking
Candidates are ranked by relevance, entity clarity, source authority, and query match. Well-structured, consistently named businesses rank higher.
Synthesis
The engine writes a response that may name one, three, or five businesses (or none). The synthesis step introduces variation: the same engine won't always give identical answers.
Citation
Some engines add source links; others name businesses inline. Being named in the response text, with or without a link, is what we measure as a citation.
The three visibility signals
Visibility Rate
45%How often your business appears in AI responses at all, across all engines and query variations.
Position Score
35%Where you appear when you do show up. First position carries the most weight; each subsequent position is discounted.
Sentiment Score
20%The tone of language AI engines use when mentioning your business: positive, neutral, or negative.
AI visibility vs traditional SEO
| Dimension | Traditional SEO | AI Visibility / GEO |
|---|---|---|
| Target platform | Google (blue links) | ChatGPT, Gemini, Perplexity, AI Overviews |
| Primary signal | Backlinks + keyword match | Entity clarity + authoritative citations + sentiment |
| Measurement | Rank position (1 to 100) | Visibility Rate, Position, Sentiment (0 to 100 score) |
| Response format | List of links | Conversational recommendation |
| User intent | Discovery + navigation | Decision + recommendation |
| Structured data impact | Moderate (rich results) | High (entity recognition) |
What hurts your AI visibility
Inconsistent entity information: different names, addresses, or categories across platforms.
No structured data (schema markup) on your website.
Thin or AI-generic content that doesn't directly answer real customer questions.
Low or stagnant review volume on major platforms.
No mentions on authoritative sources in your category (press, associations, industry directories).
How to improve
Add LocalBusiness and FAQPage JSON-LD schema to your website.
Audit and unify your entity information across all platforms.
Publish content that directly answers the questions your customers ask AI engines.
Build a review strategy: request, respond, and maintain recency.
Earn citations on high-authority sources: local press, industry associations, reputable directories.
How Clartiv measures it
Clartiv runs 12 to 24 semantically varied queries about your business across four AI engines, twice per measurement cycle, and averages the results. We measure Visibility Rate, Position Score, and Sentiment Score for each engine, then combine them into a single 0 to 100 composite score.
Full details, including the formula, query fan-out methodology, and computation pipeline, are on the Methodology page.