What Is an AI-Visibility Audit? What It Checks and What the Report Shows

An AI-visibility audit is a check of how a brand shows up in AI-generated search, ChatGPT, Google's AI Overviews, Perplexity, and other AI assistants, compared to its competitors. It answers a question that didn't exist a couple of years ago and is now near the top of many marketing teams' lists: when our customers ask AI for a recommendation in our category, are we in the answer, and if not, who is? This guide explains what an AI-visibility audit checks, what the report looks like, how it differs from a traditional SEO audit, and who runs one and why.

For the broader picture, see AI visibility for agencies. For the tools that produce these audits, AI visibility tools.

What an AI-visibility audit checks

The components, in roughly the order they matter:

1. Presence. For the queries that matter to the brand (its category, "best X," the questions its buyers ask), is the brand named in the AI's answer at all, or is it invisible?
2. Share of voice. Of the brands the AI mentions for those queries, how often is it the audited brand versus competitors? This is the headline number: not just "are we there" but "how much of the answer space is ours."
3. The competitor set. Which brands the AI recommends instead. Often the most uncomfortable and most useful part of the audit, because it names the brands winning the consideration the audited brand isn't.
4. Citations. Which pages and sources the AI pulls from when it builds the answer. These are the levers: to change what the AI says, you change what these sources say.
5. Sentiment and accuracy. When the brand is mentioned, is the AI describing it correctly and favourably, or repeating something outdated or wrong?
6. Coverage across engines. Whether the brand's standing is consistent across ChatGPT, Perplexity, Gemini, Google's AI Overviews, or strong on some and weak on others.
7. The brand's own footprint. How the brand's own pages perform as cited sources, and where they're not being picked up.

Not every audit reports all seven in the same depth, but presence, share of voice, the competitor set, and citations are the core.

What the report looks like

A good AI-visibility report turns those checks into something a marketer (or a prospect on a sales call) can act on:

• A clear visibility read: how visible the brand is across the queries tested, as a rate and against competitors.
• A competitor leaderboard: the brands AI tools cite for the topic, ranked, so you can see exactly who's ahead.
• The brand's own status: found (and where), or not found (and that's the gap). The "not found while three competitors are" finding is the one that drives action.
• Citation detail: the sources behind the mentions, so you know what to influence.

You can see what one looks like by running a domain through it:

AI-visibility audit vs traditional SEO audit

They're complementary, not competing:

• A traditional SEO audit checks technical health (crawlability, speed, indexation, schema), on-page factors, backlinks, and keyword rankings. It tells you why your pages do or don't rank in the list of links.
• An AI-visibility audit checks presence and citations in AI-generated answers. It tells you whether your brand shows up in the answer, and who shows up instead.

A site can pass a traditional SEO audit with flying colours and still be invisible in AI answers (different surface, different signals), and the reverse can happen too. Most brands that are serious about search want both: the technical-and-rankings picture and the AI-answer picture.

How an AI-visibility audit is produced

The mechanics: a tool runs a set of relevant queries through the AI engines, parses the answers to see whether the brand is mentioned and how, identifies which sources the answers cite, and compares the brand against the competitors that come up. Doing this by hand, asking the questions, reading the answers, tracking the mentions, would take hours per brand and would be hard to keep consistent. Purpose-built tools do it in about a minute and produce a structured report. (Tools compared: AI visibility tools; the embeddable, white-label kind agencies use: the best white-label SEO audit tools for agencies.)

Who runs one and why

• Agencies run AI-visibility audits as a free tool on their own site (a lead magnet), as a prospecting opener on a prospect's domain, and as a paid deliverable for clients, often the first step of an AI-search service line. (Playbook: how to offer AI-visibility audits as an agency service; positioning: becoming an AI SEO agency.)
• In-house marketing teams run one as a baseline before doing AEO and GEO work, because you can't tell whether the work is moving the number if you didn't measure the starting point.

For agencies specifically, the audit is the wedge: it's cheap or free to run, it answers a question prospects are curious about, and the report becomes the sales conversation. An embedded version on your site (with a booking calendar inside the report) turns that into a lead-capture flow, not just a tool. (More on that: embeddable SEO audit widgets.)

FAQ

Related reading

• AI visibility for agencies: the hub, including how the audit fits the wider AI-search picture.
• AI visibility tools: the tools that produce AI-visibility audits, compared.
• Answer engine optimization, LLM SEO, and how to rank in AI Overviews: the work you do once the audit shows the gap.
• How to offer AI-visibility audits as an agency service, becoming an AI SEO agency, and embeddable SEO audit widgets: turning the audit into a service and a lead-capture flow.

To see an AI-visibility report for any brand, run the domain through the free AI-visibility checker.