What you'll learn

AI adoption creates new opportunities, but it also creates governance challenges when organizations lack clear ownership, consistent decision-making, and practical oversight mechanisms. Without a strong governance framework, teams may build, buy, and deploy AI systems without knowing who approves risk, which standards apply, how exceptions are handled, or how responsible use is demonstrated.

In this course, Designing Responsible AI Governance Frameworks, you’ll gain the ability to design governance structures that help organizations guide responsible AI development and use. First, you’ll explore how to establish accountability, decision-making authority, oversight structures, and communication paths for AI governance. Next, you’ll discover how to translate governance goals into practical policies, standards, and risk-based controls. Finally, you’ll learn how to integrate and evaluate AI governance using enterprise risk practices, business operations, and established guidance such as NIST AI RMF, ISO/IEC 42001, OECD AI Principles, and the EU AI Act.

When you’re finished with this course, you’ll have the skills and knowledge of responsible AI governance needed to design frameworks that clarify accountability, support better organizational decisions, scale controls based on risk, and improve governance effectiveness over time.