AIIA: Auditing AI: Hands-On for Internal Auditors (v2.0)

Overview

Course Overview
Understand and evaluate the foundational concepts, mechanisms, risks, and governance implications of Artificial Intelligence (AI) and Generative AI systems, with a specific focus on how these technologies impact audit scope, risk assessment, and control requirements. Internal and external auditors will assess whether AI initiatives are governed effectively from planning through deployment using recognized frameworks and documented controls. Design and apply AI governance policies and procedures for GenAI applications by aligning organizational controls with trust principles, regulatory requirements, and AI lifecycle oversight. Will be able to apply the full AI audit lifecycle to a real-world case, assess governance maturity, and produce closure documentation appropriate for either internal or external auditor roles in accordance with ISO/IEC 42001 and the NIST AI Risk Management Framework.

Course Outline
Understanding and Auditing AI Applications

Learning Path 1: Understanding AI Systems and Establishing Audit Scope

Module 1: Exploring AI and Generative AI Services
Module 1 – Lab: Exploring LLM Behavior and Drafting AI Compliance Assessments
Compliance Assessments
Summary and Takeaways

Module 2: How to Audit the Intricate Components of AI Applications

Module 2 – Lab Part A: Evaluating and Tracking Compliance Measures with Microsoft Purview Compliance Manager
Module 2 – Lab Part B: Fairness and Bias Review Using Aequitas

Module 3: Investigating Internal AI Usage – Governance
Module 3 – Lab1: Governance Audit of AI-driven Traffic Sign Recognition
Module 3 – Lab 2: Reviewing AI Prompt Trails with Microsoft Purview

Module 4: Redefining Audit Engagement Across the AI Lifecycle
Module 4 – Lab: Conducting a Prompt-Based AI Audit

Module 5: Execute AI Project Management Efficiently
Module 5 – Lab: Reviewing AI Project Governance Templates

Module 6: Monitoring AI Systems and Governance in Action
Module 6 Lab: Documenting AI Risk Using the Risk Register tool

Module 7: Designing Governance in New AI and GenAI Applications
Module 7 Lab: Assessing Your Organizations AI Governance Maturity

Module 8: Auditing AI Improvement Cycles and Profile-Driven Risk Tailoring
Module 8 – Lab: Auditing Evidence of AI Governance Improvement

Module 9: Administering Trust and Accountability in Emerging AI Platforms
Module 9 – Lab: Privacy Trust Assessment

Module 10: Finalizing the AI Audit – Synthesis, Reporting, and Strategic Readiness