AI visibility
AI visibility is the degree to which a brand appears in AI-generated answers: whether it gets named, how it gets described, and whether its content gets cited when buyers ask engines relevant questions. It is the AI-search equivalent of rankings, measured by testing prompts across engines.
What is AI visibility?
AI visibility answers a simple question: when someone asks an AI engine about your category, are you in the answer? It has three layers. Presence: the brand is named at all. Framing: the description is accurate and favourable, for the use cases you actually win. Citation: the engine quotes or links your content as a source. A brand can have any of these without the others, and each layer is earned differently.
How it works
AI visibility is measured by asking engines the questions buyers actually ask, repeatedly and across engines, then recording who appears and how. Because answers vary between runs, a single test proves nothing; visibility is a rate over many runs, not a screenshot. It is improved with the standard GEO inputs: clear answers-first content on your own site, consistent entity information, and citations on the third-party sources each engine retrieves for your category.
Why it matters
Every AI answer in your category that leaves you out routes buyers to whoever was named instead, and you never see the loss. drio agency starts every engagement by measuring exactly this, then treats visibility as the first half of the job: the second half is converting the buyers who find you through it into booked meetings.
Key takeaways
- AI visibility has three layers: being named, being described accurately, and being cited as a source.
- It must be measured as a rate over repeated prompt tests, because single answers vary run to run.
- Visibility differs per engine, so a brand can be strong in ChatGPT and absent from Perplexity at the same time.
Frequently asked
- How is AI visibility measured?
- AI visibility is measured by running the commercial prompts in a category against each engine many times and recording how often the brand appears, how it is described, and whether its content is cited. Repeated runs matter because engines are probabilistic and one answer can be a fluke in either direction. The output is a share per engine and per prompt set, tracked over time, rather than a single blended score.
- Can a brand rank well in Google and still have poor AI visibility?
- Yes, and it is common. Classic rankings reward pages that attract clicks, while AI engines reward content they can extract and quote, plus mentions on the third-party sources they trust for a category. A brand can hold strong positions in Google and still never be named when a buyer asks ChatGPT or Perplexity who to choose. The only way to know is to test the actual buying prompts in each engine.
Related terms
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