governance-team-ai-human-workflow

To define an AI autonomy policy, you classify agent actions into automatic, confirmation, and humans-only categories, then document escalation rules to ensure safe automation and appropriate human oversight.

A human-in-the-loop workflow for AI governance classifies autonomous actions by risk, requiring human confirmation or manual execution for critical tasks while allowing safe automatic actions to proceed without intervention.

You configure new AI agents by applying a formal autonomy policy that specifies which automatic actions require human confirmation, sets escalation criteria, and provides examples to guide agent behavior during onboarding.

You audit autonomous actions by reviewing the generated AI-Human-Policy documentation, checking agent behavior against established escalation criteria, and ensuring all automatic, confirmation, and humans-only actions comply with governance rules.

Yes, this governance workflow supports onboarding new agents in Providers by applying a structured autonomy policy that defines action classifications, escalation rules, and examples to reduce the risk of unauthorized autonomous behavior.

AI autonomy policies reduce risk by enforcing human oversight, but limitations remain if escalation criteria are incomplete or if agents encounter scenarios not covered by the automatic, confirmation, and humans-only action classifications.