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Grounding

Grounding is the technique of tying an AI model's output to verifiable external sources, such as retrieved documents, live search or a knowledge base, so answers are anchored in real data instead of the model's memory alone.

Grounding is how an AI engine keeps its answers honest. Instead of generating from memory alone, which is the path to hallucination, a grounded system retrieves real sources at query time and builds the answer on top of them. Retrieval-Augmented Generation (RAG) is the most common grounding method.

Grounding is why citations exist. When ChatGPT, Perplexity, or Google AI Overviews footnote a source, that source is the grounding material, the evidence the engine chose to stand on.

For brands, grounding is the whole game. Your content is either eligible to be grounding material (extractable, authoritative, structurally clean) or it isn't. Becoming the source an engine grounds its answer in is the operational definition of citation share.

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