Category: AI Search & Retrieval
Definition:
Grounding is the process of connecting an AI-generated response to relevant, reliable information or sources so that the answer is based on supporting evidence rather than generated solely from the model’s internal knowledge.
Why it matters:
Grounding can help AI systems produce answers that are more relevant, accurate, and supported by external information.
For businesses, grounding is particularly relevant because the information an AI system retrieves and relies upon can influence how a brand, product, or topic is represented in an AI-generated answer.
Example:
A user asks an AI search system about the features of a specific software product. The system retrieves information from the company’s documentation and uses that information to generate its response.
The retrieved documentation helps ground the answer.
Grounding vs. Citation:
Grounding refers to using relevant information to support or inform an AI response.
An AI citation is the visible attribution or reference to a source in the resulting response.
A grounded response may or may not display a citation, depending on the system.
Related terms:
RAG · AI Citation · Retrieval · Vector Search · Embeddings · LLM · AI Search · Source Attribution
In simple terms:
Grounding is using relevant information or sources to keep an AI answer connected to supporting evidence.
