What is grounding in AI? Definition and examples

Grounding means tying an AI model's answer to specific, verifiable sources, such as your own pages or a search index, so each claim can be checked.

How it works

A language model on its own answers from patterns it learned during training. That knowledge is general, can be out of date and can't point to where a fact came from. Grounding adds a source step. Google Cloud's documentation defines it as "the ability to connect model output to verifiable sources of information," and lists two benefits: it reduces hallucinations and "provides auditability" through links to sources (Google Cloud).

The source can be:

• Your own content, usually through retrieval-augmented generation, where relevant passages are fetched and passed to the model with the question.
• A web search index, which assistants use for current events and broad questions.
• Structured systems, such as a product catalog or order database, queried through a tool.

Grounding is a goal, and RAG is the most common way to reach it. A system can retrieve documents and still ignore them, so a well-grounded assistant also follows rules: answer only from the supplied sources, cite them, and say so when the sources don't cover the question.

Why it matters for your website

Two reasons.

Your own assistant. If an AI agent on your site states a price, a policy or an integration, visitors and your legal team need to know where it came from. Grounded answers with links let a visitor verify the claim in one click, and let you trace a wrong answer back to a wrong or missing page. Ungrounded answers are where hallucinations come from.

Other people's assistants. Your pages can be used to ground other companies' AI products. Google describes grounding in its Gemini apps as "providing content from the Google Search index to the model at prompt time," and lets publishers control that use, along with Gemini training, through the Google-Extended robots.txt token, which Google says does not affect inclusion or ranking in Google Search (Google).

Example

A visitor asks a software company's site assistant: "Do you offer a discount for nonprofits?"

• Ungrounded: "Yes, nonprofits get 30% off all plans." It sounds plausible, and nothing on the site says it.
• Grounded: "I couldn't find a nonprofit discount on our pricing or billing pages. Annual plans are cheaper than monthly ones. Would you like me to pass your question to the team?" Every claim maps to a page, and the gap is admitted.

Related terms

• Retrieval-augmented generation (RAG): the usual way to ground answers in your content.
• Hallucination: what grounding is meant to prevent.
• Knowledge base: the sources a grounded assistant draws from.
• Human handoff: the fallback when sources run out.