Organizations are racing to secure and govern AI agents as lifecycle risks, insider-like threats, and hidden agent sprawl expand.
27 stories from 6 sources · since Oct 16
AI agents are moving from pilots to embedded enterprise workflows, and the coverage says that shift is creating major identity, ownership, and runtime governance gaps. CIOs are being warned that model-level controls, build-time checks, and sandboxes are not enough once agents can access data, tools, and business processes at machine speed. The common message is that AI governance is now an operating-model issue, not just a security or model-training issue.