The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

A study of 101 enterprises shows that the infrastructure supplying business context to AI agents is being deployed faster than it can be trusted. While retrieval‑augmented generation has become the primary source of context and provider‑native retrieval now outpaces traditional vector databases, many organizations have observed agents delivering confident but incorrect answers due to incomplete or inconsistent context. The article suggests that a governed semantic layer is emerging to address this gap.

Summary written by Kernelia from the original article by VentureBeat AI. The story and its rights belong to its author.