What does grounding mean?

Microsoft's Bing team puts it in one line: "grounding refers to the source material and web evidence the system uses to support and cite its response" (Bing blog, 16 June 2026, read 1 November 2026).

Google describes it from the other side, as a connection to search: "Grounding with Google Search connects the Gemini model to real-time web content". Google adds that this lets Gemini "provide more accurate answers and cite verifiable sources beyond its knowledge cutoff" (Gemini API docs, last updated 2026-10-28, read 1 November 2026).

Both pages are about web search. In developer use the word is wider: grounding can also mean answering from a company's own files, which is close to retrieval-augmented generation. Writers often use the two words loosely.

Why does grounding matter for B2B SaaS?

A grounded answer about your category is built from the pages the assistant found. If those pages describe you well, the answer can too. If they leave you out or are out of date, the answer can only repeat what they say.

Grounding is also how providers try to cut errors. Google's machine learning course is blunt: "LLMs hallucinate, meaning their predictions often contain mistakes" (Google ML crash course, last updated 2026-01-02). Google lists "Reduce model hallucinations by basing responses on real-world information" as a reason to ground. Grounding reduces hallucination; it does not remove it.

For buyer questions, the sources are often other people's lists. When Prefer checked 188 answers from ChatGPT, Perplexity, Gemini and Claude in July 2026, 40% of the sources cited were independent lists. Vendors' own sites got 34%.

How does grounding work?

Google's docs describe the steps for Gemini with Google Search:

  1. An app sends the user's prompt to the model with the search tool switched on.
  2. The model checks whether a search would improve the answer.
  3. If it would, "the model automatically generates one or multiple search queries and executes them."
  4. The model reads the results and writes its answer from them.
  5. The answer comes back with inline citations and the searches the model ran.

Running several searches for one question is what Google calls query fan-out. Bing calls the searches behind AI answers grounding queries. Its AI Performance report in Bing Webmaster Tools sorts them into types "such as Informational, Commercial, Navigational", so a site owner can see which questions led to their pages being cited.

What does grounding look like? (hypothetical example)

A buyer asks an assistant: "What does Acme Analytics cost?" Acme Analytics is a made-up product. Without grounding, the model answers from its training data, which may be a year old. With grounding, it searches, finds the current pricing page and a recent comparison article, and answers from both with links.

Now say Acme blocks the assistant's search crawler. OpenAI states that "Sites that are opted out of OAI-SearchBot will not be shown in ChatGPT search answers" (OpenAI: overview of crawlers, read 1 November 2026). The comparison article is then the only source left about Acme's price.

  • Retrieval-augmented generation is a method: retrieve text, then generate. Grounding is the aim: an answer that rests on sources. RAG is one common way to ground.
  • An AI citation is the visible result of grounding: the link to a source in the answer.
  • Query fan-out is how Google's AI search runs many grounding searches for one question.
  • Hallucination is what grounding tries to reduce.

For how brands get named in grounded answers, see the LLM SEO guide.