Zero Trust for Data When Sensitive Is Only a Label
Many enterprises treat sensitive data as a label and assume policy implies protection. Zero Trust for data reframes this as an executive expectation that access must be bounded, continuously verified, and provable. The central failure mode is access sprawl, where entitlements, exceptions, copies, and derivatives expand faster than accountability can keep up. As analytics and AI multiply consumption paths, proof obligations shift from documentation to evidence that controls worked at the point of use. The result is decision friction that surfaces in funding gates, entitlement reviews, and governance escalations rather than in tooling debates.


