Technical paper

Governing the High-Risk Actions of AI Agents

Match human approval to the consequences of the action.

AI agents need clear authority to operate independently. Organizations need to define when that authority requires verified human approval.

This iProov technical paper explores how to govern consequential AI agent actions while preserving the productivity of routine automation.

When should AI agents require verified human approval?

This paper identifies three interactions that call for the strongest evidence of human approval:

• Setting or changing permissions: Bind an accountable human to the authority an agent can exercise.
• Approving high-risk actions: Require approval of the specific action when it exceeds standing permissions or policy requires human review.
• Establishing human accountability: Connect an agent’s identity to the person or people responsible for its actions and permitted to instruct it.

What you’ll learn

Explore how to set permission boundaries, escalate consequential actions for human approval, and assign ownership of risk decisions. Understand where stronger verification adds value and how proportionate controls can help limit approval fatigue.

For security, risk, and AI leaders putting accountable AI autonomy into practice.