What is grounding in AI answers?
Grounding means anchoring an AI answer in external sources retrieved at the time of the request, usually through a web search. The model bases its statements on those sources and can show them as references, instead of answering only from its training data.
Without grounding, a language model answers from what it learned in training. That knowledge stops at a cutoff date and carries no evidence. With grounding, the system runs a search before answering, reads the results and writes the answer on that basis. OpenAI, Google and Perplexity offer search features for this in their products and APIs.
For a website's visibility, grounding is the route by which current content gets into answers. The page has to be in the search index being used and loadable by the retrieving crawler. A page whose server blocks that crawler drops out of this route.
Grounding reduces made-up statements but does not prevent them. A model can summarize a source wrongly or attribute a claim to a source that does not contain it.
What it means for your website
In practice: first check whether the AI vendors' crawlers are allowed and able to load the page, since robots.txt and firewall rules decide that. Then look at a real answer with sources to see which pages the system actually read and whether yours is among them.
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Sources
This entry contains no figures and relies on generally documented terms.
Terms help you understand. Whether AI crawlers can reach your site is something you measure.
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