Glossary · Beginner
What Is Grounding? Definition and Example
Grounding is the practice of connecting an AI model's answer to external, checkable information, such as search results or documents, at the time it answers. Google describes it as "providing content from the Google Search index to the model at prompt time to improve factuality and relevancy" (Google). Grounded answers usually come with citations.
How does grounding work?
The system fetches relevant content, often through a search, and supplies it to the model alongside the question. The model is expected to base its answer on that content. Retrieval-augmented generation is the most common technique for doing this (Lewis et al.).
Grounded vs ungrounded answers
| Ungrounded | Grounded | |
|---|---|---|
| Source of facts | Training data only | Training data plus retrieved content |
| Freshness | Up to the knowledge cutoff | Can be current |
| Citations | Rare | Common |
| Error risk | Higher on recent or niche facts | Lower, but not zero |
Example
Illustrative. A user asks Gemini about a software company's new feature launched last week. An ungrounded model can't know about it. A grounded response searches, finds the company's announcement and a news article, and summarises them with links.
Where does Google-Extended fit in?
Google's Google-Extended robots.txt token lets publishers manage whether their content is used for grounding in Gemini Apps and Grounding with Google Search on Vertex AI, as well as for training. Google says it doesn't affect Google Search, including AI features in Search (Google).
Why it matters for GEO
Grounding is where your published pages enter AI answers. To be used, a page must be reachable by the right crawler, indexed, and clear enough that a passage supports a specific claim. Accurate, well-sourced pages are also what a grounded system needs to correct an outdated belief about your brand.
Common mistakes
- Assuming a grounded answer is automatically correct; check that the cited page supports the claim.
Related
Questions
Is grounding the same as RAG?
They're closely related. RAG is a technique; grounding is the broader goal of tying answers to verifiable sources.
Does Google use the term?
Yes. Google describes grounding as providing content from the Google Search index to the model at prompt time to improve factuality and relevancy.
Does grounding guarantee accuracy?
No. It improves the odds, but models can still misread sources.