From the course: Generative AI for Business Leaders
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AI governance structures, who owns AI decisions?
From the course: Generative AI for Business Leaders
AI governance structures, who owns AI decisions?
AI governance needs clear ownership. Without it, AI spreads through disconnected tools, informal experiments, and teams making decisions in isolation. That creates risks. It also makes it harder to see what is working, what should be scaled, and what should be stopped. In many organizations, AI governance means creating a steering group that brings together business, technology, data, legal, risk, HR, cybersecurity, and compliance. That's a good starting point, but governance cannot sit in a committee alone. Each AI use case also needs a clear owner. Who owns the business outcome? Who owns the data? Who approves the risk level? Who monitors performance? And who's accountable if something goes wrong? This becomes even more important with AI agents. When AI can access systems, update records, or trigger workflows, governance needs to cover permissions, escalation rules, audit trails, and human approval points. The goal is to make accountability visible. People should know which tools…
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