What it means
Agentic AI systems are designed to take sequences of actions to achieve goals. The failure occurs when autonomous systems are deployed in contexts requiring human judgement, ethical reasoning, or contextual sensitivity. Unlike generative AI misapplication (wrong output), agentic misapplication results in wrong actions with immediate real-world consequences.
Why it matters
An agentic system deployed beyond its appropriate scope does not produce an incorrect output; it takes an incorrect action. The governance failure is deploying autonomous capability where human oversight is required.
Board governance implications
Before deploying any agentic system, the board must define the specific tasks and contexts within which autonomous action is authorised, and confirm that those boundaries are technically enforced, not merely stated in policy.
Governance failure timeline
Pre-deployment
Failure to define and technically enforce the scope boundaries of autonomous action before approving deployment.
Absence of a confirmed limit on what the system is authorised to do in contexts requiring human judgement.
Deployment
Autonomous actions are being taken in contexts that require human judgement.
Unlike a generative AI producing an incorrect output, an agentic system produces an incorrect action, with immediate real-world consequences at point of occurrence, not point of discovery.
Post-deployment
Unsanctioned actions continue to accumulate contractual liability and reputational exposure.
Regulatory scrutiny focuses on what boundaries the organisation defined and whether those boundaries were technically enforced or merely stated in policy.