AI Governance in Practice: Build responsible, audit-ready programs with ISO/IEC 42001, NIST AI RMF, and lifecycle controls

Build an audit-ready AI governance program with practical assessments, lifecycle controls, and guidance aligned with ISO/IEC 42001, NIST AI RMF, OECD AI Principles, and the EU AI Act

Key Features

• Apply ISO/IEC 42001, NIST AI RMF, OECD AI Principles, and the EU AI Act in practice
• Conduct AI impact and risk assessments using structured methods and practical templates
• Build audit-ready lifecycle controls, documentation, monitoring, and accountability
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description

Turn AI governance principles, standards, and regulatory requirements into a practical program that operates across the AI lifecycle.

This book shows you how to build responsible AI governance around ISO/IEC 42001, the NIST AI RMF, OECD AI Principles, the EU AI Act, and other frameworks. You’ll conduct AI risk and impact assessments, define governance roles and decision rights, establish policies and lifecycle controls, and create documentation for transparency, accountability, and AI compliance.

You’ll apply governance through development, deployment, monitoring, and retirement; address AI security and safety; prepare for AI incidents; and use AI audits and monitoring findings to strengthen controls. Practical scenarios, templates, checklists, and step-by-step guidance turn frameworks into repeatable organizational practices.

Written by Hemang Doshi, who has more than 20 years of experience in system audit, IT risk and compliance, internal audit, risk management, information security audit, third-party risk management, and operational risk management, this book connects governance frameworks with practical implementation. By the end, you’ll be able to build an accountable, audit-ready AI governance program and integrate AI risk management with existing compliance, security, privacy, and risk processes.

What you will learn

• Explain responsible AI principles and governance lifecycle risks
• Compare ISO/IEC 42001, NIST AI RMF, OECD, and the EU AI Act
• Conduct structured AI impact and risk assessments
• Define accountable governance roles and decision rights
• Create policies and lifecycle controls for responsible AI
• Document AI systems for transparency and auditability
• Prepare for AI incidents with structured response processes
• Perform AI audits and improve governance from findings

Who this book is for

AI governance, compliance, and risk management professionals responsible for overseeing AI systems, evaluating AI risks, or implementing responsible AI practices, along with data scientists, ML engineers, internal auditors, privacy leaders, and technology executives. A foundational understanding of AI concepts, basic IT risk principles, and organizational policies or governance frameworks is recommended. This book also provides a strong foundation for AI GRC certifications such as AIGP, AAIA, AAIR, AAISM, AIMS, and others.

Table of Contents

1. Understanding Artificial Intelligence
2. Introduction to AI Governance
3. Principles of Responsible AI
4. Overview of Global AI Governance Frameworks – ISO/IEC 42001 and EU AI Act
5. AI Governance Framework – ISO/IEC 42001
6. AI Governance Framework – NIST AI RMF
7. AI Governance Framework – OECD AI Principles
8. European Union AI Act
9. AI Impact Assessment
10. AI Risk Assessment
11. Comparative Analysis of AI Frameworks – ISO/IEC 42001 and EU AI Act
12. AI Governance Structure
13. AI Governance Documents
14. AI Lifecycle Governance
15. Security of AI Systems
16. AI Incident Management
17. AI System Audits