How do AI models find information about brands?

AI assistants pull from two places:

1. Training data — what the model learned when it was built, which favors well-established, widely referenced brands.
2. Live retrieval — many assistants now fetch current web pages at answer time (retrieval-augmented generation) and cite them directly.

The model then synthesizes an answer and surfaces the sources it judged most authoritative, clear, and relevant. Pages that are well-structured, accurately attributed, and recently updated are easier to retrieve and cite.

The nuance: each engine retrieves differently and weights freshness and authority in its own way, which is why visibility has to be measured per engine rather than assumed to be uniform.