Public concern often focuses on an AI system suddenly becoming uncontrollable. More common operational risks are less dramatic: weak inputs, ambiguous instructions, excessive permissions, broken workflows, unsupported claims, drift and superficial approval.
These risks can be addressed through designed boundaries, verification, independent auditing, runtime monitoring and clear human accountability. The future question is not whether capability should stop, but whether control systems are engineered at the same speed.
Revision history
Version 1.0 — 26 July 2026: Initial publication.