AI grounding
AI grounding: tying answers to sources.
What AI grounding means, how grounding AI works in Google and in assistants, and why it decides which pages get cited.
Short answer
What is grounding in AI answers?
AI grounding ties a model's answer to retrieved sources instead of memory alone. Google describes grounding AI as pulling relevant, up-to-date pages from its Search index, then linking to pages that support the response.
In brief
Four things to know first.
Retrieved, not remembered
A grounded answer draws on pages fetched at the moment of the question, not only on what a model learned.
Retrieval picks the sources
Google says its AI features retrieve pages through its core Search ranking systems. A page that is not retrieved cannot support an answer.
Links show the support
Google shows clickable links to pages that support the response. These are the citations you can win.
Sources are not guaranteed
Google's Gemini help page says not every response includes sources. Some answers carry no links at all.
Definition
What grounding AI means, in plain words.
Grounding connects a model's answer to real, retrievable sources. Google calls the technique retrieval-augmented generation, or grounding. It uses core Search ranking systems to fetch relevant, up-to-date pages.
Google says its generative AI models use publicly accessible, crawlable content to provide grounded responses. A page that crawlers cannot reach has nothing to offer a grounded answer.
| Ungrounded answer | Grounded answer | |
|---|---|---|
| Source of facts | What the model learned in training | Pages retrieved when the question is asked |
| Freshness | Fixed at training time | Up-to-date pages from the index |
| Links shown | None to check | Links to supporting pages |
How it works
How a grounded answer gets built.
Google's guide describes query fan-out: the model generates related queries to fetch more results. Its example turns "how to fix a lawn that's full of weeks" into searches like "best herbicides for lawns."
The retrieved pages feed the written answer. Google then shows links to pages that support it.
Question
A person asks the assistant something.Retrieval
The engine pulls relevant, up-to-date pages, using related queries to fetch more results.Answer
The model writes one answer using what it retrieved.Links
The engine shows links to pages that support the response.
Want to see which pages ground the answers?
We map the buyer prompts your audience uses in ChatGPT, Claude, Perplexity and Gemini, and show who is cited and from which sources.
Why it matters
Grounding decides who gets cited.
To appear in Google's AI features, a page must be indexed and eligible to show in Search with a snippet. Google adds that there are no additional technical requirements.
Google's Gemini help page says not every response includes sources. If the Sources button is missing, Gemini gave no links for that response.
Retrievable pages win
Google says its AI features are rooted in core Search ranking and quality systems.
Useful pages stand out
Google says unique, compelling, useful content will likely matter most for presence in AI search over the long run.
Quoted text gets a link
Gemini lists a link when it directly quotes a large amount of text from a page.
What to do
Make your pages easy to ground on.
Most of the work is basic and shared with SEO. Check results against your own buyers' questions, since sources shift by platform and prompt.
Keep key pages indexable
Make sure each page is crawlable, indexed and eligible to show in Search with a snippet.Publish non-commodity content
Offer expert or first-hand takes, not common knowledge that could come from anyone.Put answers first
State the direct answer and the specific facts at the top, so each claim stands alone.Skip the hacks
Google says it does not use llms.txt, and that page variants made to manipulate AI responses may breach spam policy.Track what gets cited
Run your buyers' questions across assistants and record which pages are cited, against a baseline.
FAQ
AI grounding: common questions.
What does grounding mean in AI?
Grounding in AI means anchoring a model's answer to retrieved sources. Google describes it as retrieval-augmented generation, which uses core Search ranking systems to pull relevant, up-to-date pages and shows clickable links to pages that support the response.
Is grounding the same as retrieval-augmented generation?
Grounding and retrieval-augmented generation describe the same technique in Google's wording, which calls it retrieval-augmented generation, or grounding. The model retrieves relevant pages first, then writes the answer from them and links to pages that support it.
Does a grounded AI answer show sources every time?
A grounded AI answer does not show sources every time. Google's Gemini help page says not all responses include related links or sources, and that a missing Sources button means no links were provided for that response.
How does a page become a source for grounding?
A page can become a grounding source if it is indexed and eligible to show in Google Search with a snippet. Google says there are no additional technical requirements.
Do I need llms.txt or special markup for grounded answers?
Google says you do not need llms.txt files or other special machine-readable files, markup or Markdown to appear in its generative AI features, because Google Search does not use them. Structured data is also not required, though it remains useful for rich results.
How is grounding different from query fan-out?
Grounding is the whole step of retrieving web pages to support an answer. Query fan-out is one part of it: Google describes it as concurrent, related queries the model generates to fetch additional search results. For 'how to fix a lawn that's full of weeds', one fan-out query is 'best herbicides for lawns'.
See which sources ground your category's AI answers.
We run your buyers' questions through ChatGPT, Claude, Perplexity and Gemini and show you the gap.