AI agent governance
Governance is the permissions, approval steps, and oversight structure that limit what an agent is allowed to do. It's the primary safety control for agentic systems — more tractable than trying to perfect an agent's judgement.
Moving up the conceptual ladder — from assistant to automation to agent to multi-agent system — increases capability, cost, variance, and risk at the same time. Governance is what keeps that risk bounded as capability increases, rather than treating autonomy as an all-or-nothing setting.
Human-in-the-loop is the dominant governance pattern in production agent systems today: a human approves, reviews, or intervenes at a defined point, rather than an agent acting fully unattended on anything consequential.
Accountability stays human. Legal systems assign responsibility to persons and organisations, not to software — which is exactly why permissions and escalation, not model capability alone, are what a business should be evaluating before deploying an agent.
See how this is applied concretely in Holistic Agent's own security & governance controls, or the underlying discipline in Module 11 of the free course.