Glossary

What is grounding in AI?

Also known as AI grounding, search grounding, grounded generation

Definition

Grounding is when an AI model bases its answer on information it looks up at the time, such as search results or documents, rather than only on what it learned in training. Grounded answers usually cite sources.

Key points

A grounded answer is based on information the model looks up at the time of the question.
Grounded answers usually cite sources, while answers from training alone do not.
Your brand needs to do well in both, since different engines work in different ways.

What does it mean in practice?

Ask a model with no web access about a cafe that opened last month, and it may know nothing or guess. Ask a grounded model, and it searches first, reads what it finds and writes an answer with links.

Google describes grounding with Google Search as connecting Gemini to real-time web content. It says this reduces made-up answers and lets the model show its sources. ChatGPT search, Perplexity and Google AI Overviews all ground their answers in web results, which is why they can cite pages.

Why does it matter for AI search?

Grounding decides which route your content takes into an answer. For grounded answers, your pages need to be crawlable, indexed and easy to quote. Your brand also needs to appear on the sites that get retrieved. For ungrounded answers, what matters is what the model learned in training, which reflects your reputation across the web over time.

It helps to check both. In Axiom GEO, ChatGPT and Perplexity are tracked with web search, so answers include cited pages. Gemini and Claude are asked through their APIs without web search, which shows how the model itself sees a brand. Perplexity, Gemini and Claude tracking explains the difference. Our guide on how AI engines choose sources goes further.

These terms connect to grounding.

Retrieval-augmented generation, the method behind most grounded answers.
Hallucination, the kind of error grounding aims to reduce.
Citation, the links grounded answers show.
Query fan-out, one way engines search more widely.

Common questions

Why do some AI answers have sources and others do not?

Answers with sources are usually grounded, meaning the engine searched the web or a set of documents before writing. Answers without sources usually come from what the model learned in training. Some engines ground most answers, others only when the question needs fresh information.

Does grounding stop AI from making mistakes?

It reduces mistakes but does not remove them. A grounded answer is only as good as the pages it finds. If those pages are out of date or wrong, the answer can be wrong too. The model can also misread a source or blend details from two pages.

Reviewed 26 September 2026

All terms A to Z