Audit AI Governance Systems Step by Step | ISO/IEC 42001 | Risk | Ethics | Bias | Templates | Real Case Studies

What you'll learn

Conduct ISO/IEC 42001 audits from planning to reporting

Identify AI-specific risks and nonconformities in audits

Evaluate AI ethics, bias mitigation, and governance controls

Use real-world templates to complete AI audit exercises

Requirements

Knowledge of ISO 42001

Description

Are you ready to lead AI audits with confidence and align your organization with ISO/IEC 42001?This course will guide you step by step through the entire ISO 42001 AI governance audit process, using practical examples, hands-on exercises, and professional templates. Whether you're an AI compliance officer, internal auditor, governance specialist, or simply interested in AI risk management, this course is designed to give you the tools and knowledge to become a certified and confident ISO 42001 Lead Auditor.What you will learn:How to conduct ISO/IEC 42001 audits from preparation to follow-upIdentify and address AI-specific risks, nonconformities, and compliance gapsEvaluate AI bias, fairness, ethics, and security governance controlsApply audit techniques using real-world templates, checklists, and reporting toolsWhy this course?With the rise of AI in critical systems—from healthcare to transportation—organizations must ensure that their AI solutions are safe, fair, explainable, and compliant with emerging international standards. ISO 42001 is the world's first AI Management System standard, and this course is tailored to help professionals audit it effectively.We use a model company throughout the course to demonstrate each audit step in context—no dry theory. Each concept is made practical, with exercises that help you build real auditing experience. Assignments include scenarios based on a second model company, so you can apply your skills to new challenges.You will also receive downloadable templates, including audit checklists, stakeholder interview guides, risk assessment forms, and reporting formats.Who is this course for?AI governance and compliance professionalsInternal and lead auditors transitioning into AI auditingRisk managers and ethics officers working with AI systemsAI developers and data scientists involved in AI lifecycle complianceWhether you're preparing for a professional certification, a regulatory audit, or simply want to take the lead in AI governance, this course will give you the structure and skills to succeed.

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Our Use Case - NeuroVista Technologies

Section 2: Introduction to the Artificial Intelligence Management System & ISO/IEC 42001

Lecture 3 Introduction to the AIMS & ISO-IEC 42001

Section 3: Overview of ISO 42001

Lecture 4 ISO 42001 Structure

Lecture 5 Clause 4 - Context of the Organization

Lecture 6 Clause 5 - Leadership

Lecture 7 Clause 6 - Planning

Lecture 8 Clause 7 - Support

Lecture 9 Clause 8 - Operation

Lecture 10 Clause 9 - Performance Evaluation

Lecture 11 Clause 10 - Improvement

Section 4: Step 2: Audit Preparation & Planning

Lecture 12 Core Principles Of Auditing (Integrity, Objectivity, Confidentiality

Lecture 13 Understanding The Risk-Based Approach In AI Auditing

Lecture 14 Ethical Considerations & Bias Detection In AI Audits

Lecture 15 AI Auditing Techniques & Evidence Gathering Strategies

Section 5: Step 3: Initiation of an AI Audit

Lecture 16 Step 2 - Audit Preparation & Planning

Lecture 17 Establishing Audit Objectives & Scope

Lecture 18 Our Use Case for Assignments - AutoVision AI

Lecture 19 Identifying Relevant AI Governance Controls

Lecture 20 Preparing Audit Checklists & Questionnaires

Lecture 21 Allocating Resources & Scheduling AI Audits

Section 6: Step 3: Initiating the Audit

Lecture 22 Step 3 - Initiation of an AI Audit

Lecture 23 Conducting The Opening Meeting

Lecture 24 Reviewing AI Policies, Risk Assessments & Documentation

Lecture 25 Evaluating AI Model Lifecycle Compliance

Lecture 26 Interviewing Key Stakeholders

Section 7: Step 4: On-Site Audit Activities

Lecture 27 Step4: On-Site Audit Activities

Lecture 28 Assessing AI System Governance & Security Controls

Lecture 29 Reviewing AI Model Transparency & Explainability Standards

Lecture 30 Evaluating Bias, Fairness, And Ethical AI Practices

Section 8: Step 5: Identifying Nonconformities & Audit Reporting

Lecture 31 Step 5 - Identifying Nonconformities & Audit Reporting

Lecture 32 Categorizing Major & Minor Nonconformities

Lecture 33 Writing Clear & Actionable Audit Findings

Lecture 34 Recommending Corrective Actions & Improvements

Lecture 35 Preparing The Audit Report & Communicating Results

Section 9: Step 6: Closing The Audit & Follow-Up Actions

Lecture 36 Step 6 - Closing The Audit & Follow-Up Actions

Lecture 37 Conducting The Audit Closing Meeting

Lecture 38 Addressing Audit Findings & Corrective Action Implementation

Lecture 39 Monitoring Continuous Improvement In AI Governance

Section 10: Conclusion

Lecture 40 Conclusion

AI compliance officers, internal auditors, risk managers, and professionals involved in AI governance and responsible AI practices