Why Grounding is (Still) the Bedrock of Enterprise AI

Grounding connects a Large Language Model's reasoning capabilities to an organization's specific, authoritative data, making it reliable for enterprise use. This process mitigates the risk of hallucinations by instructing the model to base responses exclusively on provided context, often using a technique called Retrieval-Augmented Generation (RAG). A well-grounded AI system builds trust and drives adoption by providing verifiable, auditable answers with source citations. This foundation of trust is essential for de-risking AI investments and achieving a measurable return through increased productivity and reduced liability.