AI Governance and Oversight
AI governance is not a policy PDF; it is who can deploy what, with which controls, and under whose accountability. As agentic systems gain access to tools and data, missing ownership becomes a direct operational risk.
Lesson: inventory first, then match oversight to risk and autonomy.Why this matters in practice
Without explicit decision rights, teams duplicate experiments, bypass controls, and escalate incidents too late. Risk-tiered controls let low-risk use cases move quickly while high-risk use cases receive stronger review, monitoring, and human override requirements.
What to check in your organization
1. Is there a single accountable executive owner for AI governance decisions?
2. Do you maintain an inventory of AI systems, models, and external AI services?
3. Are systems classified by risk with proportional approval and monitoring controls?
4. Can operators intervene, override, or stop high-impact systems in production?
Learn more
Explain: NIST AI Risk Management Framework
Apply: NIST AI RMF Playbook
Authority: EU AI Act Article 14 (Human Oversight)
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