What is grounding?
Grounding is the process of tying an AI model's answer to specific, verifiable sources, such as search results, documents or a product database, so the answer rests on real information instead of only on what the model remembers. A grounded answer can usually show where each claim came from.
Without grounding, a language model answers from patterns learned during training, which may be outdated or incomplete. With grounding, the system first collects relevant material and instructs the model to stay close to it. The most common method is retrieval-augmented generation, where web pages or documents are retrieved at the moment of the question.
AI companies use the term widely. Google, for example, offers developers grounding with Google Search for Gemini, and its Google-Extended robots.txt token lets sites decide whether their content may be used to train and ground Gemini models. That token does not affect Google Search, and AI Overviews are part of Search.
Why grounding matters for AI visibility
Grounding is how your website gets a say in AI answers. When an assistant grounds its response in live sources, the pages it selects shape what it says about your category, which brands it names and which sites it cites. A page chosen as grounding material can become an AI citation with a link back to you.
Grounding also limits the damage of an AI hallucination. If the sources about your brand are accurate, current and consistent, grounded answers tend to repeat those facts. If the best available source is an outdated review, that is what the model repeats instead.
How to become a grounding source
Make sure your key pages are indexed and readable without JavaScript. Google says a page needs to be indexed and eligible to appear with a snippet in Search before it can show up as a supporting link in AI Overviews or AI Mode.
Answer specific questions directly, with facts a model can lift: numbers, names, dates and conditions.
Show that your information is current with visible update dates, and remove or redirect outdated pages.
Add structured data so machines can read your company, products and prices without guessing.
Earn coverage on independent sources. For brand comparisons, assistants often ground their answers in reviews and comparison articles rather than vendor pages.
Our guide on how to get cited by AI goes deeper. Trackbase tracks both mentions and citations across 11 AI models, so you can see when your pages are used as a source.
Examples of grounding
Asked "what does a heat pump installation cost", Google AI Overviews builds its summary from several web pages and links to them.
Perplexity answers a question about a B2B payroll software vendor by reading the vendor's pricing page and two review sites, then cites all three.
A Dutch bicycle webshop grounds its customer chatbot in its own product catalog, so the bot only recommends bikes that are actually in stock.
A developer builds a travel assistant on Gemini with grounding with Google Search, so answers about opening hours reflect current search results.
Frequently asked questions
What is the difference between grounding and RAG?
Grounding is the goal: an answer that is anchored in verifiable sources. Retrieval-augmented generation (RAG) is the most common way to reach it, by retrieving relevant pages or documents and giving them to the model before it writes. Grounding can also use other inputs, such as a product database or files that a user uploads.
Does grounding mean the AI answer is always correct?
No. Grounding makes answers more accurate and easier to check, but the model can still misread a source, pick an outdated page or combine facts from sources that disagree. A grounded answer is only as good as the sources it finds, which is why accurate, current and consistent information about your brand matters so much.
Can I stop Google from using my content to ground Gemini?
Yes. The Google-Extended token in robots.txt controls whether your content may be used to train and ground Gemini models. It does not affect how your pages rank or appear in Google Search, and AI Overviews are part of Search. Weigh the choice carefully: if you block it, Gemini models cannot use your content for training or grounding, which also removes you as a potential source in those answers.