Grounding
Connecting an AI model's answer to external sources, such as live search results, so its claims rest on retrieved evidence rather than memory alone.
A model on its own answers from what it learned in training, which can be stale or wrong. Grounding gives it fresh material at the moment of the question, usually by running a web search and handing the results to the model. Google uses the term directly: Gemini can be grounded with Google Search.
Why grounding matters for AEO
Grounding is the door AEO walks through. You can't quickly change what a model memorized in training. You can change what it finds when it searches. Grounded answers are also where citations come from, since the engine links the pages it used.
- Grounded answers reflect the current web and cite sources.
- Ungrounded answers reflect training data and usually cite nothing.
- Most assistants decide per question whether to search, so the same brand can be grounded in one answer and recalled from memory in the next.
How to win grounded answers
- Be retrievable: let the search crawlers in and make sure key pages are indexed.
- Be relevant: answer the question, and its sub-questions, in plain language.
- Be quotable: specific claims, numbers you can back up, dates that show freshness.
Grounding is one form of retrieval-augmented generation. Our methodology explains why Elite Answers collects answers with web search turned on.
Somewhere, right now, an AI is recommending your client's competitor.
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