Ungrounded AI operates from memory, generating based on training patterns. Grounded AI operates from evidence, connecting outputs to actual data. The distinction determines reliability.

How Grounding Works

Grounding systems retrieve relevant information before or during generation. This might be documents from your knowledge base, real-time data from APIs, or search results from the web. The AI then generates responses that reference this grounded information.

Grounding vs RAG

RAG is one grounding technique focused on document retrieval. Grounding is broader: it includes RAG but also real-time data access, database queries, API calls, and web search. Grounding is the concept; RAG is a specific implementation.

Why Grounding Matters for Marketing

Marketing content needs accuracy. Grounded AI can cite real statistics, reference actual product details, use current pricing, and align with verified brand messaging. Ungrounded AI guesses at these, creating risk and rework.