Grounding means connecting a language model's output to external information it was given at answer time, such as web search results, a company knowledge base or a database. A grounded answer can point to where each claim came from. Google's Gemini API offers grounding with Google Search, and AI search products like ChatGPT search, Perplexity and Google's AI features all ground answers in retrieved web pages to varying degrees.
Why grounding exists
LLMs generate text from patterns learned in training. Without outside information they can produce statements that sound right but are false, often called hallucinations, and they know nothing after their training cutoff. Grounding reduces both problems by giving the model current, specific evidence and asking it to answer from that evidence.
Grounding lowers the risk of errors without removing it. A model can still misread a source, combine facts wrongly or cite a page that does not fully support the claim.
Grounding in AI search
In an AI search product, grounding usually follows the retrieval-augmented generation pattern: search, select passages, generate an answer from them, and attach citations. The sources a system grounds on decide what it says. If the grounding sources describe your product inaccurately, the answer will too.
What to check on your own site
- Key facts, such as pricing, plans, limits, integrations and supported regions, are stated in text, not only in images or interactive widgets.
- Those facts are consistent across pages, so a retrieved passage does not contradict another.
- Old pages with outdated facts are updated, redirected or clearly dated.
- Important pages are crawlable by the search crawlers that AI products rely on.
Example
A fictional pricing contradiction
Shiftly, a made-up workforce app, changed its free plan limit last year. The pricing page is current, but an old blog post announcing the original limit still ranks. An AI answer grounded on that post states the old limit. The team updates the post with a dated note and the current limit, and links it to the pricing page.
Common mistakes
Assuming grounded means correct
Grounded answers can still be wrong. Check how AI tools describe your key facts.
Putting facts only in images
Pricing tables built as images or behind tabs that need scripts to load may not be read by the systems doing the grounding.
Questions
Grounding is the aim of anchoring answers in sources. RAG is a common technique for doing it.
When citations are shown, yes, at least partly. Some answers are grounded on more pages than are displayed, and some draw on training data without citation.
