What is Grounding in AI?
Last updated 2026-06-19
Grounding is the practice of tying an AI answer to actual sources the model retrieves, rather than relying only on its training memory. Grounded answers tend to cite, which is exactly where a brand can earn its place.
Grounding reduces guesswork
An ungrounded answer is the model recalling patterns, which is where wrong claims creep in. A grounded answer is anchored to documents the model can point at. For brands, grounding is an opportunity. If your facts are the clearest source, you become the anchor.
How to be the source models ground on
- State facts plainly and keep them current
- Structure pages so passages are easy to extract
- Earn presence on sources assistants retrieve from
- Offer a clean, machine-readable version of key content