A Practical Guide to Building an Artificial Intelligence Management System from Foundation to Certification
Introduction: Why Your Organization Needs an AI Management System
- What You Will Know After Reading This Book
- Who This Book Is For
- How This Book Is Organized
- How to Use This Book
Chapter 1: The Imperative for AI Governance
- Why AI Governance Matters Now
- From Ad Hoc Controls to Systematic Management
- The Cost of Unmanaged AI Risk
- What an AIMS Delivers
Chapter 2: Understanding Responsible AI and Management Systems
- Responsible AI Principles in Practice
- Management System Fundamentals
- The Plan-Do-Check-Act Cycle for AI
- How ISO/IEC 42001 Bridges Governance and Operations
Chapter 3: ISO/IEC 42001 in Context
- The ISO/IEC 42001 Development Story
- Relationship to ISO/IEC 23894 and Other AI Standards
- Alignment with NIST AI RMF and OECD Principles
- Regulatory Landscape: EU AI Act, Sectoral Laws and Global Trends
- Integration with ISO 9001, ISO/IEC 27001 and Other Management Systems
Chapter 4: Structure, Scope and Terminology of ISO/IEC 42001
- High-Level Structure and Clause Organization
- What Is In Scope and What Is Not
- Key Terms and Definitions You Must Know
- Roles: Developer, Provider, Deployer, User
- How to Read the Standard Correctly
Chapter 5: Context of the Organization (Clause 4)
- Understanding Internal and External Issues
- Identifying Interested Parties and Their Requirements
- Defining the AIMS Scope with Precision
- The AI Management System as an Integrated Component
Chapter 6: Leadership (Clause 5)
- Top Management Commitment Beyond Symbolism
- Developing an Effective AI Policy
- Assigning Roles, Responsibilities and Authorities
- Embedding AIMS into Organizational Governance
Chapter 7: Planning (Clause 6)
- Addressing Risks and Opportunities Systematically
- AI Risk Assessment Methods and Approaches
- Setting Measurable AI Objectives
- Planning Changes to the AIMS
Chapter 8: Support (Clause 7)
- Resources and Infrastructure for AI Governance
- Building Competence in Responsible AI
- Awareness Programs That Work
- Internal and External Communication on AI
- Managing Documented Information Effectively
Chapter 9: Operation (Clause 8)
- Operational Planning and Control Design
- AI Lifecycle Governance from Concept to Decommissioning
- AI Risk Assessment and Impact Evaluation in Practice
- AI Risk Treatment and Control Selection
- Third-Party and Supply Chain AI Management
Chapter 10: Performance Evaluation (Clause 9)
- Monitoring, Measurement, Analysis and Evaluation
- Internal Audit Program Design for AIMS
- Management Review Input, Process and Output
Chapter 11: Improvement (Clause 10)
- Nonconformity and Incident Response for AI Systems
- Root Cause Analysis and Corrective Action
- Building a Continual Improvement Culture
Chapter 12: Annexes and Specific Requirements
- Understanding Normative vs Informative Annexes
- AI Risk Assessment Framework (Annex A)
- AI Impact Assessment Methodology (Annex B)
- Applying the Annexes to Real Scenarios
Chapter 13: Getting Started - Project Initiation and Gap Assessment
- Securing Leadership Buy-In and Resources
- Establishing the Implementation Team
- Conducting a Comprehensive Gap Assessment
- Building Your Implementation Roadmap
Chapter 14: Designing Your AIMS
- Governance Structures and Decision Rights
- Policy Architecture and Document Hierarchy
- Process Design for AI Lifecycle Management
- Control Framework Selection and Customization
Chapter 15: Implementing Controls and Processes
- Phased Rollout Strategies
- Operationalizing Risk Assessment and Treatment
- Building Data Governance for AI Systems
- Model Governance and Technical Controls
- Training, Awareness and Cultural Change
Chapter 16: Operating and Maintaining Your AIMS
- Documentation Discipline and Record Keeping
- Ongoing Monitoring and Performance Tracking
- AI Incident Management Procedures
- Managing Changes to AI Systems and the AIMS
Chapter 17: Preparing for Certification Audit
- Certification Readiness Assessment
- Selecting the Right Certification Body
- Stage 1 Documentation Review Preparation
- Stage 2 On-Site Audit Execution
Chapter 18: Maintaining Certification and Advancing Maturity
- Surveillance Audits and Recertification
- Handling Nonconformities and Findings
- Sustaining AIMS Effectiveness Over Time
- Advanced Optimization and Maturity Models
Chapter 19: Integration Strategies for Existing Management Systems
- Integrated Management System Design Principles
- Mapping ISO/IEC 42001 to ISO/IEC 27001 Controls
- Leveraging ISO 9001 Quality Processes for AI
- Integrating with ISO 31000 Risk Management
- Practical Integration Patterns and Pitfalls