Data lineage becomes critical security layer for AI agents in enterprises

Enterprise AI agents are increasingly making decisions by pulling data from multiple internal sources—pricing systems, communications, archives—without human review between handoffs. This creates governance and security risks when agents pass outputs to other agents or systems. Data lineage, the practice of tracking where data originates and how it flows through systems, is emerging as a core security control for agentic AI deployments. The approach aims to provide visibility, accountability and trust in AI systems without slowing their adoption.