Search Grounding
Søkegrounding
Search grounding is the technique in which an AI model supplements its internal training knowledge with live web retrieval to deliver more current and accurate answers. The model searches the web, fetches relevant texts, and uses them as the ground truth for the answer.
Grounding solves one of the core problems of LLMs: knowledge frozen at the training cutoff. With grounding, a model can answer questions about events that occurred after training. ChatGPT Search, Perplexity, and Google AI Overviews all use grounding.
For marketers, grounding means that live SEO rankings are directly relevant for AI visibility. Pages that rank high on Google are more likely to be retrieved and cited by grounded AI systems.
Frequently asked questions
What's the difference between grounding and RAG?
RAG (Retrieval-Augmented Generation) is the technical architecture. Search grounding is the specific implementation in which an AI model searches the web in real time. RAG can also use internal databases as a knowledge source.
Explore the AI search glossary
AI Search Academy is an independent glossary for AI search and visibility.
See all termsRelated terms
KR
AI Search & Growth Strategist with 25+ years in digital marketing. Read more →