数据血统成为新的AI安全边界
企业需要数据血统来管理AI治理、责任和信任，随着代理AI的扩大。
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.