Responsible governance is increasingly the difference between AI that scales and AI that stalls, and strategy gets approved only when someone communicates it well. In this course, you learn to apply AI governance and ethics frameworks to an initiative so that responsibility is designed in rather than added after an incident. You work with the NIST AI Risk Management Framework, ISO/IEC 42001, the EU AI Act, and IBM's AI governance principles, and learn what question each one answers. You identify and mitigate AI-specific risks, including model, data, regulatory, third-party, and agentic risks, and you test the control most governance plans never examine: whether a person assigned to review AI output can actually catch its errors at the volume they face. Then you develop the communication craft that turns analysis into a decision an executive can act on, including how to deliver an unwelcome finding early and plainly. You finish by rehearsing how to bring the whole advisory story together. No coding or legal background is required.

AI Governance, Risk, and Executive Communication

AI Governance, Risk, and Executive Communication
This course is part of IBM Enterprise AI Transformation and Consulting Professional Certificate

Instructor: LearnQuest Network
Access provided by National Open University of Nigeria
Recommended experience
What you'll learn
Apply AI governance frameworks, such as NIST AI RMF, ISO/IEC 42001, and the EU AI Act, so responsibility is designed in from the start.
Identify and mitigate model, data, regulatory, third-party, and agentic AI risks in a governance and risk plan.
Test whether a human-review control can be performed at the volume a reviewer faces, then redesign or reject it.
Communicate AI strategy to executives, including how to deliver an unwelcome finding early, plainly, and actionably.
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