AI Governance & Risk

AI Governance & Risk

Duration: 2 Days

Description

As organizations adopt generative AI, leaders need a clear framework for governing its use responsibly. This course gives managers, executives, and risk owners a practical foundation in AI governance: the policies, oversight structures, and risk-management practices needed to deploy AI safely and in line with emerging regulation. Participants examine the real risks generative AI and increasingly autonomous AI agents introduce, learn how to build governance appropriate to their organization’s size and risk appetite, and leave with a roadmap for establishing accountable, well-managed AI use.
Class time is divided between discussion and case studies (70 percent) and applied planning exercises (30 percent).

Audience

Managers, executives, compliance and risk professionals, legal and privacy stakeholders, and anyone responsible for overseeing how AI is adopted and used within an organization. No technical background is required.

Objectives

  • Explain what AI governance is and why it matters for organizations
  • Identify the primary risks generative AI introduces across legal, ethical, and operational dimensions
  • Describe major regulatory and standards developments shaping AI oversight
  • Outline the components of an effective AI governance program
  • Establish roles, policies, and review processes for accountable AI use
  • Develop a practical roadmap for governing AI in your own organization

Prerequisites

There are no technical prerequisites. A general awareness of how generative AI is used in business will help participants get the most from the course.

  • Familiarity with your organization’s current AI or technology use
  • A general understanding of generative AI concepts

Related AI Courses

See the full AI training roadmap and course directory for how this fits into a broader learning path.

Pair this course with AI Security and AI Ethics and Bias for a complete view of responsible AI oversight.

Course Outline

  • Module 1 – Course Introduction
    • Welcome and objectives
    • Why AI governance matters now
    • Governance, risk, and compliance in context
  • Module 2 – Understanding AI Risk
    • Categories of AI risk: legal, ethical, operational, reputational
    • Data privacy, confidentiality, and intellectual property
    • Accuracy, bias, and fairness concerns
    • Security and misuse risks
  • Module 3 – The Regulatory Landscape
    • Emerging AI regulation and why it is evolving
    • Key frameworks and standards
    • Industry-specific and regional considerations
    • Keeping pace with a changing environment
  • Module 4 – Components of an AI Governance Program
    • Principles and acceptable-use policies
    • Oversight structures and accountability
    • Risk assessment and approval workflows
    • Documentation, transparency, and auditability
  • Module 5 – Operationalizing Governance
    • Roles and responsibilities across the organization
    • Vendor and third-party AI risk
    • Monitoring, incident response, and escalation
    • Training and culture
  • Module 6 – Building Your Governance Roadmap
    • Assessing current state and risk appetite
    • Prioritizing policies and controls
    • Phased rollout and quick wins
    • Hands-on exercise: draft a governance roadmap
  • Module 7 – Course Wrap-Up
    • Key takeaways
    • Resources for continued learning
    • Next steps