This course aims to enable participants to master the knowledge and skills required to evaluate and report the consistency and effective implementation of an Artificial Intelligence Management System (AIMS), helping organizations carry out ethical artificial intelligence practices in the AI era, ensure responsible development and use of AI systems, improve the quality, safety, traceability, transparency and reliability of AI systems, and actively and effectively respond to risks and impacts related to the AI system lifecycle. The purpose of ISO/IEC 42001:2023 Internal Auditor Training is to equip learners with the necessary techniques to conduct internal audits of an enterprise's Artificial Intelligence Management System (AIMS) and help it continuously improve. This training can help learners identify the risks and negative impacts organizations face when AI governance measures fail, and efficiently take means to control risks.

• Master the knowledge and skills to evaluate and report the consistency and effective implementation of an Artificial Intelligence Management System (AIMS)
• Help organizations carry out ethical artificial intelligence practices in the AI era
• Ensure responsible development and use of AI systems
• Improve the quality, safety, traceability, transparency and reliability of AI systems
• Actively and effectively respond to risks and impacts related to the AI system lifecycle
• Identify the risks and negative impacts organizations face when AI governance measures fail, and efficiently take means to control risks

• Personnel engaged in AI system management and AI governance, including personnel related to AI quality, safety and data governance, middle and senior management personnel engaged in enterprise management, internal auditors and other related personnel

• Background and trends of artificial intelligence development
• AI compliance requirements and supervision in various countries and regions
• ISO 42001: AI management system framework
• Basic elements and characteristics of AI management system
• Clauses of ISO 42001:2023 standard
• Objectives of AI governance
• Detailed explanation of AI risks
• Overview and basic concepts of risk management
• AI risk assessment and AI system impact assessment
• Risk identification, risk analysis
• Risk evaluation, risk treatment
• AI system impact assessment and treatment
• Cases and practice of AI risk assessment and AI system impact assessment
• Establishment of AI management system
• Operation of AI management system
• Performance evaluation of AI management system
• Continuous improvement of AI management system
• Cases of AI management system establishment
• Introduction to AI controls
• AI control domains, control objectives and control measures
• Practical cases of AI control measures
• Planning and implementation of internal audits
• Introduction to GB/T 19011
• Basic audit knowledge
• Cases and practice