Expertise
AI visibility
What do AI systems say about you when nobody from your company is in the room?
What it means
AI visibility is how often and how accurately a company appears in answers generated by AI systems, and which sources those systems rely on to describe it. It covers three separate things that get collapsed into one number: whether you appear at all, whether the description is right, and who is named instead of you.
Why it matters
Most teams discover their AI visibility by accident. A prospect repeats something odd on a call, or a competitor turns up in an answer where a founder expected their own name. The instinct is to buy a tool and watch a score, which tells you the number moved without telling you why, and a number with no cause attached cannot be acted on.
What you control
- In your hands
- The evidence you publish, and how consistent it stays across every source you can edit.
- Not in your hands
- The answer itself. You can change what a system reads. You can never change what it says.
What we do
- Build the prompt set from the questions your buyers ask, in their words, not the category's.
- Sample across ChatGPT, Gemini, Perplexity, Copilot and AI Overviews, repeatedly, because a single answer is noise.
- Record the cited sources, not only the mentions. The sources are the surface you can influence, and most of them are not your website.
- Sort findings by kind: absence, staleness, distortion or vagueness. Each has a different fix and a different cost.
How we use the framework
AI visibility measures Internet Reality. On its own that is a thermometer. Set against what the company actually is and what it says about itself, it becomes a diagnosis, which is what the Digital Reality Gap framework is for.
See the full frameworkCommon questions
Should we buy an AI visibility tool?
If you need to watch a number over time, defend a budget or catch movement early, yes. They do that job well. They will not tell you why you are absent from an answer, which is usually the question you actually have.
How often does it need measuring?
Quarterly for the pattern, monthly if you are actively changing things. Answers vary between runs, so measuring more often mostly buys you noise.
Does AI visibility affect revenue?
It affects who reaches you already convinced and who arrives with a misconception. The attribution chain is broken by design, since a conversation with a model leaves no trace on your site, so treat direction over quarters as the signal rather than any single month.
Start with what the market can see.
A conversation is enough to know whether there is a gap worth closing.