Integrated Specialist Program in Artificial Intelligence Management Systems
Description: After completing the course, participants will be able to demonstrate the following competences:
- Define, implement, and improve AI management systems aligned with ISO/IEC 42001.
- Assess, document, and apply AI-specific controls and objectives.
- Conduct and report AI risk assessments based on ISO/IEC 23894.
- Perform AI impact assessments considering ethical, technical, and legal impacts.
- Apply lifecycle thinking in AI system planning, development, and governance.
- Support inclusive and socially acceptable AI solutions.
- Establish AI governance structures and ensure cross-functional coordination.
Previous skills/knowledge: Participants are expected to have the following basic knowledge:
- Familiarity with ISO/IEC 27001 and basic information security principles.
- Understanding of risk management, organizational resilience, and digital infrastructure.
- Basic awareness of management systems (PDCA) and their role in maintaining operations.
Authorized Partners:
Teaching requirements: Trainers should meet the following requirements:
- Subject Matter Expertise: deep and broad knowledge of ISO/IEC 27035-1/2/3/4, ISO 22301, ISO/IEC 27031, and proven experience in implementing ISMS, BCMS, and DR frameworks.
- Certifications: recommended credentials include ISO/IEC 27001, ISO/IEC 27031, and ISO 22301 Lead Implementer or Auditor, and specialized qualifications in incident handling, continuity coordination, and disaster recovery.
- Training & Practical Experience: minimum of 3 years in the field, covering incident response, BIA and risk analysis, business continuity planning, DR testing and coordination of crisis or recovery teams.
Objectives to achieve: This program aims to provide participants with comprehensive skills in AI system management, risk, compliance, ethics, and lifecycle implementation:
- Understand and apply ISO/IEC 42001 and ISO/IEC 23894 principles in AI management.
- Gain skills in designing, implementing, and evaluating AI-specific controls and risk treatments.
- Identify ethical and legal risks in AI, and incorporate mitigation strategies.
- Use AI terminology and lifecycle concepts to support governance, risk, and compliance activities.
- Perform structured AI impact assessments and communicate findings effectively.
- Align AI objectives with organizational goals and regulatory expectations.
- Embed ethics and trustworthiness into AI system design and operation
