Grounding means an AI output is supported by the context, data, or sources available to the system. A grounded answer can be traced back to evidence. An ungrounded answer may be plausible, but it is not supported.
For developers, grounding is an eval target and a design constraint. RAG systems should capture retrieved context in traces, preserve source metadata, and evaluate whether claims in the answer are backed by the provided evidence.