Indexing delay in AI is the time gap between a change to information on a website and its being reflected in the answers of generative search engines. There are three causes, and each has a different length. If the system answers from the search index, the delay corresponds to the pace at which the page is recrawled, that is, days to weeks. If it answers from a cached response, the reflection depends on the set cache validity period. And if it draws on what the model learned during training, the information may not be updated at all until a newer version of the model arrives. In practice, this means keeping critical data such as prices and conditions on a page that changes often and is easily accessible, and when changing a name or offer, expect a transitional period in which both versions will be in circulation.
See also: Semantic caching, Content freshness signal, False brand mention in AI.
