Description
This course provides participants with a foundational understanding of ISO/IEC 42001:2023, the international standard for Artificial Intelligence Management Systems (AIMS). The training introduces key concepts, principles, and requirements for managing AI systems responsibly, including ethical considerations, governance, risk management, transparency, and accountability. Participants will learn how organizations can implement controls to ensure the safe, secure, and trustworthy use of AI technologies. The course is ideal for organizations adopting AI or seeking to align with international best practices for AI governance and compliance
Course Objectives
By the end of this course, participants will be able to:
- Understand the purpose and structure of ISO/IEC 42001:2023
- Recognize key principles of responsible and ethical AI
- Identify risks associated with AI systems
- Understand governance and management requirements for AI
- Interpret the main clauses of the standard
- Appreciate the importance of transparency, accountability, and fairness in AI
- Support the implementation of an AI Management System (AIMS)
- Prepare for AI governance and compliance initiatives
The benefits
Participants and organizations will benefit by:
- Increase awareness of AI governance and risk management
- Improved understanding of ethical and responsible AI practices
- Enhanced organizational readiness for AI adoption and regulation
- Reduced risks related to AI misuse, bias, and non-compliance
- Strengthened stakeholder trust and confidence in AI systems
- Alignment with international best practices for AI management
- Foundation for implementing ISO/IEC 42001 within the organization
Modules
Module 1: Introduction to ISO/IEC 42001:2023
- Overview of
AI Management Systems (AIMS)
- Purpose and
scope of the standard
- Key
terminology and concepts
Module 2: AI Governance and Principles
- Responsible
AI principles (fairness, transparency, accountability)
- Ethical
considerations in AI
- AI lifecycle
overview
Module 3: Context of the Organization
- Understanding
organizational context
- Stakeholder
identification and expectations
- Defining the
scope of AIMS
Module 4: Leadership and Planning
- Leadership
roles and responsibilities
- AI policy
and objectives
- Risk and
opportunity management
Module 5: AI Risk Management
- Identifying
AI-related risks (bias, privacy, security, safety)
- Risk
assessment methodologies
- Mitigation
and control strategies
Module 6: Support and Operational Controls
- Resources,
competence, and awareness
- Data
management and governance
- Operational
controls for AI systems
Module 7: Performance Evaluation
- Monitoring
and measurement of AI systems
- Internal
audits and reviews
- Performance
indicators and reporting
Module 8: Improvement and Accountability
- Incident
management and corrective actions
- Continuous
improvement of AI systems
- Accountability and documentation
Module 9: Practical Exercises and Case Studies
- Basic AI governance framework development
- AI risk identification exercise
-
Ethical decision-making scenarios
Certification
Delegates will receive a Certificate of:
- Attendance, or
- Competency
Assessment
There will be an assessment at the end of the course.
- Delegates have to complete the assessment with a minimum score of 60% to receive a Certificate of Competence.
- Delegates who score between 50% and 59% will get a second attempt at the assessment.
- If you fail the second attempt, will need to repurchase the course
- Delegates will receive a Certificate of Attendance regardless of a pass or fail.