AI Risk Management: Guardrails for Real-World AI

1.1 Welcome to the AI Risk Course

1.2 The CIA Triad for AI (What Leaders Need to Know)

1.3 Generative vs. Agentic AI (Deciding How Much Autonomy to Allow)

1.4 Data Security and Access Control (Preventing Leaks and Misconceptions)

1.5 Privacy, PII, PHI, and Data Use in AI (What You May and May Not Do)

1.6 Hallucinations and Prompt Quality (Getting to Reliable Answers)

1.7 Deepfakes, Veracity, and Authenticity (Seeing Is No Longer Believing)

1.8 Bias, Discrimination, and Decision Chains (Who’s Influencing Your Results)

1.9 Trust and Information Integrity vs Data Security (Not the Same Thing)

1.10 AI Dependency and Supply Chain Resilience

1.11 Open Source, Third Party APIs, and Contributing Parties (Know What You’re Shipping)

1.12 Transparency and Design - Know Your Stack (Who Built It? How Does It Work?)

1.13 Shadow AI, Ungoverned Use, and Practical Controls

1.14 Agentic AI Operational Controls (Availability and Safety in Action)