數據血統成為新的AI安全邊界
企業需要數據血統來管理AI治理、責任和信任，隨著代理AI的擴大。
as enterprises adopt agentic ai, they face challenges in managing data that is continuously ingested, copied, summarized, transformed, reused, and redistributed. traditional security approaches built around applications, systems, networks, or endpoints are no longer sufficient. data lineage is necessary to understand how data moves and to establish governance, accountability, and trust across human, agentic, and hybrid workflows. this is crucial for securing agentic ai at scale.