AI searchability
AI searchability describes how findable, retrievable, and accurately described a business is when someone asks an AI assistant a question instead of typing a query into a search engine. It covers whether a model can identify the business as a distinct entity, whether it has sources to draw on, and whether the description it produces matches reality.
How it differs from search engine optimization
Traditional search returns a ranked list of documents, and optimization work centers on which page occupies which position. AI assistants return a synthesized answer assembled from retrieved sources and model memory. There is no single ranked list to occupy, so the practical questions change: is the brand mentioned at all, is it described correctly, and which sources shaped that description.
What determines it
- Entity clarity. A consistent name, category, location, and set of official profiles so the business resolves to one entity rather than several ambiguous ones.
- Structured data. Schema.org markup that states machine-readable facts directly in the HTML rather than leaving them to be inferred.
- Source coverage. Independent pages that describe the business — press, directories, documentation, and reference sites — since retrieval draws on third-party sources as well as owned ones.
- Crawlability. Content served in the initial HTML response, with robots rules and sitemaps that permit AI crawlers to reach it.
- Consistency over time. Facts that do not contradict each other across sources, so a model is not choosing between competing claims.
How it is measured
Measurement works by asking assistants the questions customers actually ask, then recording whether the brand appears, how it is characterized, which competitors appear alongside it, and which sources are cited. Repeating those prompts over time shows whether changes to entity data and source coverage move the outcome. This is the problem Optimly works on.
Related
See AI brand measurement for the companion explainer on how brand representation in AI systems is quantified.
Further reading
Apurva Luty writes about AI search behavior and brand representation at Signal/Noise. See also her biography and press coverage.