AI Agents

A legally binding EU framework now carries €35 million fines for AI violations.

Most enterprises use AI daily but lack operational controls to govern it.

Enterprises are deploying AI agents faster than they can audit what those agents actually do.

Classical monitoring cannot catch agent anomalies that unfold across sequences of actions.

Agents fail silently, and traditional monitoring cannot see it.

Logging captures breaches after they happen; enforcement policies stop them before they scale.

Most enterprises give AI agents too much access and monitor the wrong identities entirely.

Most organizations document AI governance but fail to enforce it where systems actually run.

Malicious tool components can poison AI agents at machine speed across every system they reach.

When AI agents gain system access, prompt injection attacks move from embarrassing to catastrophic.

Competing terminology across frameworks creates design chaos before deployment even begins.

OAuth and SAML were built for humans, not machines that spawn sub-agents at scale.

Enterprises are deploying AI agents at scales their access controls were never designed to handle.

97% of AI agents inherit excessive permissions they don't need to function.

Agents expose permissions at machine speed, making traditional access control testing obsolete.

Leaked credentials sit active for years while agent deployments outpace security controls.

Agents tolerate variation; RPA scripts break when reality deviates.