AI Governance in Practice: The Operational Skills That Actually Get Results

Course details

Learn the hands-on skills you need to thrive in AI governance roles. Build your understanding of how to apply AI governance through practical exercises such as risk assessments, stakeholder mapping, and crisis response simulations. Discover how to leverage your existing expertise in privacy, compliance, or cybersecurity to implement governance frameworks. Learn to communicate AI risks and governance strategies effectively across technical and policy teams to enable informed decision-making. Address regulatory issues and operational challenges. Find out how to build a governance capacity where responsibilities are shared across the organization. Perfect for privacy analysts, cybersecurity experts, or compliance officers, this course presents strategies to make AI governance operationally effective and sustainable.

Learning objectives
Translate effectively between technical, policy, and business stakeholders to drive AI governance implementation.
Build coalitions across competing organizational interests and navigate the cultural/political dynamics of AI deployment.
Manage the operational realities of AI governance—from risk identification to crisis response—in complex, cross-functional environments.

Concepts

Introduction

AI governance in practice - Operational skills for results

The Reality of AI Governance Work

What AI governance professionals actually do daily
AI systems essentials - What you need to know
Applying your existing skills to AI governance

Stakeholder Mapping and Power Dynamics

Identify your AI governance ecosystem - Internal stakeholders
Identify your AI governance ecosystem - External stakeholders
Reading the room - Organizational culture and AI politics
Negotiating trade-offs among different stakeholders

Technical-Policy Translation Skills

Bilingualism - Technical concepts for policy audiences
Bilingualism - Policy requirements for technical teams

Operational AI Risk Management

Building your AI use case inventory
Conducting practical AI risk assessments
Create actionable risk mitigation plans
Success metrics and measurement to communicate value

Managing AI Governance Crises

When things go wrong - AI incident response fundamentals
Crisis communication across stakeholders

Managing AI Vendors and Third-Party Risk

Evaluating AI vendor claims and capabilities
Essential questions for AI vendor due diligence

Putting It All Together

Running effective AI review meetings
AI governance as a whole-company effort - Your role as educator and evangelist

Conclusion

Succeeding in your AI governance role