GEO·AEOFoundationsUpdated 2026.04.28

Grounding

Also known as그라운딩Retrieval Grounding

In one line

Grounding is the practice of anchoring an LLM's answer to external evidence — retrieved documents, search results, structured data — to push factual accuracy higher.

Going deeper

Grounding is the umbrella term for techniques that force an LLM to lean on outside evidence — retrieved documents, live search, structured data — instead of relying on its training memory. RAG is the canonical pattern, and citation-based AI search is grounding in disguise.

Why marketers care: if your content is not in the pool the model grounds against, accurate citations are impossible. You want clean facts on your own site and consistent information on external surfaces — Wikipedia, press, reviews — so the grounding result stabilises.

Grounding is not a silver bullet. If sources are wrong or out of date, the answer follows them. Models also paraphrase sources in ways that subtly drift. Periodically auditing how the AI grounds claims about your brand is part of running a GEO program.

Related terms

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