AI Operating Model and Decision Rights
AI delivery fails when ownership is ambiguous. Clear operating models define who decides, who approves, who executes, and who is accountable when outcomes go wrong.
Lesson: establish accountable ownership and decision paths before scaling AI programs.Why this matters in practice
Without a defined operating model, councils multiply, accountability diffuses, and high-impact decisions stall or bypass controls. A practical RACI for AI decisions helps teams move quickly while preserving governance.
What to check in your organization
1. Is there a named accountable owner for AI strategy and risk decisions?
2. Are decision rights documented across business, technology, risk, and legal teams?
3. Is there a standard escalation route for high-impact AI issues?
4. Are governance forums decision-making bodies, not update meetings?
Learn more
Explain: NIST AI Risk Management Framework
Apply: NIST AI RMF Playbook
Authority: ISO/IEC 42001 AI Management Systems
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