ISO/IEC 42001 AI Standards Implementation Training Course

Learn to Implement ISO AI Standards for Compliance & Success

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ISO/IEC 42001 AI Standards Implementation Training Course

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Course Overview:

The course provides an implementation and managing ISO/IEC 42001:2023 standards for AI Management Systems (AIMS). Designed for organizations seeking to integrate AI governance and compliance, this course covers AI lifecycle management, offering actionable insights into ISO AI standards implementation, AI risk management frameworks, and AI policy development. Participants will explore key areas such as AI data governance, ethics and accountability, and AI principles for organizations. The course emphasizes the scope of AI Management Systems, detailing governance key concepts, stakeholder analysis, and the importance of aligning with ISO 27001 and other global standards. By attending, participants will gain practical expertise in AI system design best practices, continuous learning in AI, and performance monitoring to ensure a seamless and compliant implementation of AIMS.

Target Audience:

CIOs, CTOs, and IT Managers looking to integrate AI Management Systems (AIMS)
Compliance officers managing AI governance and compliance regulations
Risk managers responsible for AI risk assessment techniques and mitigating AI risks
AI developers and data scientists engaged in AI lifecycle management and AI system design best practices
Project managers working on aligning ISO/IEC 42001 standards with organizational goals

Targeted Organizational Departments:

Information Technology (IT): For implementing AI lifecycle management and AI performance monitoring
Compliance and Risk Management: To ensure adherence to AI governance and compliance requirements
Research and Development (R&D): For AI system design best practices and continuous learning in AI systems
Data Governance Teams: To address data quality and AI data governance

Targeted Industries:

Finance and Banking
Healthcare
Manufacturing
Technology and Software Development
Retail and E-commerce

Course Offerings:

By the end of this course, participants will be able to:

Implement ISO/IEC 42001:2023 standards in their organization
Develop and manage AI governance and compliance policies
Design and monitor robust AI Management Systems (AIMS)
Conduct comprehensive AI risk assessments and mitigate potential risks
Align AI lifecycle management with global standards such as ISO 27001
Address data quality, bias, and ethical challenges in AI data governance

Training Methodology:

This course utilizes a hands-on approach with interactive sessions, real-world AI management case studies, and group discussions. Participants will conduct mock AI impact assessments, analyze system failures, and work on AI compliance exercises. The program focuses on practical application through AI risk management framework development, case studies on ethics, and stakeholder analysis workshops.

Course Toolbox:

Comprehensive course ebook on ISO/IEC 42001:2023 standards
Checklists for AI risk assessment techniques
Templates for AI policy development and AI governance frameworks
Case studies illustrating lessons from AI implementation

Course Agenda:

Day 1: Introduction to ISO AI Standards

Topic 1: Overview of ISO/IEC 42001:2023 – Scope, purpose, and benefits of AI Management Systems (AIMS)
Topic 2: Key terminology and concepts related to AI governance and management
Topic 3: Context of the organization – Identifying internal and external factors influencing AI systems
Topic 4: Stakeholder analysis and their expectations in AI implementation
Topic 5: Alignment with other standards – ISO 27001, ISO 9001, and the EU AI Act
Topic 6: Importance of aligning AI governance with organizational goals
Reflection & Review: Key takeaways from the foundational understanding of ISO/IEC 42001:2023

Day 2: AI Governance and Leadership

Topic 1: Leadership and commitment – Role of leadership in implementing AI Management Systems (AIMS)
Topic 2: Defining AI principles – Ethics, fairness, transparency, and accountability
Topic 3: Policy development – Establishing and communicating AI management policies
Topic 4: Roles and responsibilities – Establishing accountability frameworks for AI governance
Topic 5: Practical approaches to integrating organizational vision into AI strategies
Topic 6: Challenges and solutions in fostering leadership commitment for AI implementation
Reflection & Review: Recap on AI governance strategies and leadership impact

Day 3: Risk and Impact Management in AI

Topic 1: Introduction to AI risk management frameworks – Identifying, analyzing, and mitigating risks
Topic 2: Risk assessment tools and techniques tailored for AI systems
Topic 3: AI impact assessment – Evaluating social, economic, and environmental implications
Topic 4: Case studies on effective AI risk and impact assessments
Topic 5: Compliance and legal requirements – Aligning global AI regulations with AIMS
Topic 6: Developing strategies to address unexpected risks in AI systems
Reflection & Review: Applying risk and impact management insights

Day 4: AI Lifecycle and System Management

Topic 1: AI system design and development – Managing requirements, testing, and validation
Topic 2: Incorporating continuous learning mechanisms in AI systems
Topic 3: Operations and monitoring – Key performance indicators for AI systems
Topic 4: Techniques for identifying and addressing AI system failures
Topic 5: Data governance in AI – Ensuring data quality, security, and privacy
Topic 6: Addressing biases in AI models – Building fairness and transparency into AI governance
Reflection & Review: Lessons learned on lifecycle management and operational improvements

Day 5: Continuous Improvement, Supplier Management, and Practical Implementation

Topic 1: Performance evaluation – Setting measurable objectives for AIMS effectiveness
Topic 2: Nonconformity and corrective actions – Addressing deviations and improving processes
Topic 3: Supplier management and third-party alignment – Ensuring adherence to AI principles
Topic 4: Real-world case studies of AIMS implementation – Success stories and lessons learned
Topic 5: Preparing for certification – Steps to achieve compliance with ISO/IEC 42001:2023
Topic 6: Certification process – Required documentation and strategies for continuous improvement
Reflection & Review: Consolidating certification readiness and key takeaways from the course

How This Course is Different from Other ISO AI Standards Courses:

This course distinguishes itself by focusing on actionable insights and practical applications of ISO/IEC 42001:2023 standards. Unlike other programs, it integrates hands-on exercises such as mock AI impact assessments, comprehensive workshops on AI lifecycle management, and The application of methods for governing and ensuring compliance with artificial intelligence. By leveraging real-world AI management case studies, participants will learn how to overcome industry-specific challenges and implement AI principles for organizations effectively.

credits: 5 credit per day

Course Mode: full-time

Provider: Agile Leaders Training Center

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Amsterdam	Week 45, 2025 Nov 3, 2025 - Nov 7, 2025	5 Days	Onsite	€5,700
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