Grounding
By the Pickgap team · Updated Oct 15, 2026 · 1 min read
Grounding is the process of connecting an AI model's answer to external, current information, such as web search results, maps data or documents, instead of relying only on what the model learned in training. For local recommendations, grounding is what lets AI name businesses based on today's reviews, listings and websites.
Why AI needs grounding
A language model's training data is a snapshot of the past. It doesn't know about a business that opened last year, new hours, or this month's reviews. Grounding fixes that by fetching current information at the moment of the question and giving it to the model to write from.
How the main AI surfaces ground answers
- Google AI Overviews, AI Mode and Gemini: grounded in Google Search and, for places, Google's business data.
- ChatGPT: grounded in web search, through OpenAI's crawler and third-party search providers, when it searches.
- Perplexity: grounded in its own web search for nearly every question, with citations.
What it means for you
Because answers are grounded in what search finds today, you can influence them by changing what search finds: your profile, your listings, your reviews, your website and mentions on other sites. That's the basis of all AI visibility work. It also means an ungrounded answer (no search) relies on training data, which is why small businesses are rarely named when an assistant doesn't search.
Related: retrieval-augmented generation, hallucination.