Is your company known to AI, or findable by it?
Updated September 2026
Those are two different things, and the difference matters. An ungrounded answer comes from the model's memory, so being known is being remembered. A grounded answer comes from a live search, so being findable is being retrievable at the moment the engine looks. You want to be both, but you can only build one of them directly.
Grounding is the difference between a closed-book and an open-book answer. Closed book, the model answers from what it absorbed during training, which can be stale or simply wrong. Open book, it runs a live search, reads current sources, and cites them. A large share of everyday assistant answers are still closed-book, answered from memory without a live search, and whether the engine bothers to search often depends on how familiar your brand already is.
This is why findability is the lever you control. You cannot easily rewrite what a model memorized, but you can make sure that when it does search, your content is legible, current, and corroborated enough to be retrieved and trusted. The live index refreshes quickly, with Google's AI answers rewriting roughly every two days, while a model's memory only updates every few months, so fresh, findable content is what reaches an answer between those slow memory updates.
In our own testing, engines answering from memory have named the wrong founding year and even the wrong country for a company, then corrected themselves once forced to search, a clean illustration of why being findable beats hoping to be remembered.