Recent incidents with internal assistants and open-source agents are not isolated glitches. They expose structural weaknesses in how enterprises approach autonomy, trust, and security for AI systems.

As generative and agentic systems move from experiments to execution, the question is no longer whether models are powerful enough. It is whether the data environments they rely on are stable enough to be trusted with real authority.