Zero Trust Reality Check for Defensible Data and AI
This diagnostic helps senior leaders stress-test zero trust claims about data and AI without turning the discussion into architecture or tooling. It focuses on the authority fracture: when policy language exists but enforceable control and proof do not. The questions force clarity on runtime evidence, proof velocity, and exception handling under release pressure. It also surfaces where accountability defaults when proof cannot be produced in the moment it matters. The intent is to make narrative substitution visible in steering committees and decision forums.
