All Episodes

Welcome to the AIGP Course!

Episode 58 — Synthesize Development and Deployment Governance into One Defensible Decision-Making Framework

Episode 57 — Establish External Communication Plans and Deactivation or Localization Controls for AI

Episode 56 — Document Incidents and Post-Market Monitoring While Reducing Secondary Uses and Downstream Harms

Episode 55 — Verify Deployed AI with Audits, Red Teaming, Threat Modeling, and Security Testing

Episode 54 — Conduct Ongoing Monitoring, Maintenance, Updates, and Retraining After Deployment

Episode 53 — Apply Governance Controls to Deployment Through Data, Risk, Issue, and User Training

Episode 52 — Understand the Unique Risks, Opportunities, and Obligations of Deploying Proprietary AI

Episode 51 — Evaluate Vendor Contracts and Licensing Terms Before You Deploy AI

Episode 50 — Assess Selected AI Systems with Focused Impact Reviews Before Deployment

Episode 49 — Choose Deployment Options Across Cloud, On-Premise, Edge, Fine-Tuning, RAG, and Agentic Architectures

Episode 48 — Compare AI Model Types Before Choosing What Your Organization Will Deploy

Episode 47 — Evaluate Deployment Context, Business Goals, Ethics, Data, and Workforce Readiness

Episode 46 — Review AI Development Governance from Impact Assessments to Public Disclosures

Episode 45 — Meet Transparency Duties with Technical Documentation, Instructions, and Monitoring Plans

Episode 44 — Investigate AI Incidents with Cross-Functional Teams Tracing Drift, Data Gaps, and Brittleness

Episode 43 — Assess Production AI After Release with Audits, Red Teaming, Threat Modeling, and Security Testing

Episode 42 — Build Continuous Monitoring, Maintenance, Updates, and Retraining Rhythms for Released AI

Episode 41 — Assess Release Readiness with Model Cards and Conformity Requirements

Episode 40 — Manage Training and Testing Issues While Documenting Results for Compliance

Episode 39 — Improve Interpretability and Reduce Model Risk During AI Testing

Episode 38 — Plan Training and Testing Across Unit, Integration, Validation, Performance, Security, and Bias

Episode 37 — Establish Data Lineage and Provenance You Can Defend Under Scrutiny

Episode 36 — Govern Training Data Rights, Quality, Quantity, Integrity, and Fitness for Purpose

Episode 35 — Document Design and Build Decisions to Prove Compliance and Manage Risk

Episode 34 — Strengthen AI Designs Through Use-Case Evaluation, Benchmarking, Pilots, and Testing

Episode 33 — Identify and Mitigate Design Risks with Harms Matrices, Risk Hierarchies, and Stakeholder Mapping

Episode 32 — Build Human Oversight, Metrics, Thresholds, Feedback, and Controls into Design

Episode 31 — Design AI Systems with Clear Purpose, Requirements, Architecture, and Model Choice

Episode 30 — Perform Impact Assessments Early to Shape Safer AI Design Decisions

Episode 29 — Define Business Context and Use Cases Before Building Any AI System

Episode 28 — Review the Governance Foundations and Legal Duties Most Likely to Matter

Episode 27 — Understand ISO 22989, ISO 42001, and ISO 42005 in AI Governance

Episode 26 — Use the NIST AI RMF and Playbook to Structure Governance

Episode 25 — Apply OECD Trustworthy AI Principles, Frameworks, Policies, and Recommended Practices

Episode 24 — Compare Enforcement, Penalties, and Duties for Providers, Deployers, Importers, and Distributors

Episode 23 — Understand the Distinct Requirements That Apply to General-Purpose AI Models

Episode 22 — Govern Human Oversight, Transparency, Notification, and Quality Management Requirements

Episode 21 — Operationalize AI Law Requirements for Risk Management, Documentation, and Record Keeping

Episode 20 — Map AI Risk Classifications from Prohibited Uses to Minimal Risk

Episode 19 — Interpret Consumer Protection and Product Liability Risks in AI Systems

Episode 18 — Apply Nondiscrimination Law to AI in Employment, Credit, Housing, and Insurance

Episode 17 — Understand How Intellectual Property Law Shapes AI Training and Use

Episode 16 — Protect Sensitive and Special Category Data When AI Uses Biometrics

Episode 15 — Master Controller Obligations for AI Impact Assessments, Rights, Transfers, and Records

Episode 14 — Embed Data Minimization and Privacy by Design into AI Systems

Episode 13 — Navigate Transparency, Choice, Lawful Basis, and Purpose Limits in AI

Episode 12 — Manage Third-Party AI Risk Through Assessments, Contracts, Procurement, and Acceptable Use

Episode 11 — Update Privacy, Security, Data Governance, and IP Policies for AI

Episode 10 — Establish Life Cycle Policies That Drive Oversight and Accountability End to End

Episode 9 — Differentiate Developers, Providers, Deployers, and Users in the AI Governance Model

Episode 8 — Tailor AI Governance to Company Size, Maturity, Industry, and Risk Tolerance

Episode 7 — Create AI Terminology, Strategy, and Governance Training for Every Stakeholder

Episode 6 — Build Cross-Functional AI Governance Collaboration That Actually Works Across the Organization

Episode 5 — Define AI Governance Roles and Clarify Who Owns Which Decisions

Episode 4 — Apply Responsible AI Principles Across Fairness, Safety, Privacy, Transparency, and Accountability

Episode 3 — Understand AI Risks, Harms, and Why Governance Cannot Be Optional

Episode 2 — Grasp AI Definitions, Types, and Core Use Cases That Matter

Episode 1 — Decode the AIGP Exam Blueprint, Question Styles, Policies, and Spoken Study Plan