As artificial intelligence continues to transform industries across the globe, the demand for robust governance and accountability frameworks has never been greater. The LICQual ISO/IEC 42001:2023 – Artificial Intelligence Management System (AIMS) Lead Auditor course is a globally recognized training program designed to prepare professionals to audit, assess, and certify AI systems in accordance with the ISO/IEC 42001:2023 standard. This specialized course empowers applicants to ensure ethical, transparent, and secure deployment of AI technologies within organizations.
This intensive program equips participants with in-depth knowledge of the Artificial Intelligence Management System standard, focusing on AI-specific risk management, compliance, data governance, and responsible AI practices. It blends international auditing principles with technical guidance for evaluating AI frameworks across various sectors. applicants will gain practical skills to lead audits that align with the latest regulatory and technological expectations.
The LICQual ISO/IEC 42001:2023 Lead Auditor training is ideal for professionals who work in IT governance, cybersecurity, data protection, AI development, compliance, and quality management. Participants will explore key areas such as establishing AI policies, verifying ethical use of algorithms, assessing AI lifecycle stages, and ensuring ongoing conformity to organizational objectives and legal obligations. This course ensures that graduates are fully capable of performing first, second, and third-party audits of Artificial Intelligence Management Systems.
Throughout the course,applicants will delve into audit preparation, audit planning, execution, reporting, and follow-up in the context of AI-driven environments. Real-world case studies and scenario-based exercises enhance understanding of how to apply the ISO/IEC 42001:2023 framework in practical auditing situations. Participants will be trained to lead audit teams, conduct risk-based assessments, and report findings in accordance with ISO 19011 guidelines.
As the global AI ecosystem evolves, organizations must proactively manage AI risks and demonstrate compliance with international standards. The Artificial Intelligence Management System framework introduced by ISO/IEC 42001:2023 provides a structured approach to governing AI responsibly. By earning this lead auditor certification, professionals play a crucial role in safeguarding ethical AI deployment and boosting stakeholder confidence in AI solutions.
Completing the LICQual ISO/IEC 42001:2023 – Artificial Intelligence Management System (AIMS) Lead Auditor course signifies expertise in auditing AI governance frameworks at the highest level. It provides a competitive advantage in the job market and supports career progression into leadership roles in compliance, risk management, and AI oversight. With global recognition, this qualification empowers professionals to help organizations align AI operations with trust, transparency, and accountability.
Course Overview
Qualification Title
LICQual ISO/IEC 42001:2023 – Artificial Intelligence Management System (AIMS) Lead Auditor
Total Units
6
Total Credits
40
GLH
120
Qualification #
LICQ2200427
Qualification Specification
To enroll in the LICQual ISO/IEC 42001:2023 – Artificial Intelligence Management System (AIMS) Lead Auditor applicants must meet the following criteria:
Qualification# |
Unit Title 15526_d603d1-de> |
Credits 15526_37b9f8-c2> |
GLH 15526_2be439-09> |
---|---|---|---|
LICQ2200427-1 15526_9388a5-da> |
Understanding ISO/IEC 42001:2023 and the AIMS Framework 15526_e132b3-cf> |
8 15526_5fb0e9-d2> |
24 15526_eb444d-72> |
LICQ2200427-2 15526_38f1f9-8f> |
AI Risk Management and Ethical Governance 15526_39e68b-e3> |
8 15526_ca03e3-2b> |
24 15526_6e383d-8b> |
LICQ2200427-3 15526_4e5503-27> |
Planning and Preparing for an AIMS Audit 15526_027c69-e3> |
6 15526_bd90ec-49> |
18 15526_acc608-14> |
LICQ2200427-4 15526_dd6a0f-03> |
Conducting AIMS Audits: Techniques and Tools 15526_9b481b-1b> |
6 15526_c97042-f0> |
18 15526_d81ea7-0c> |
LICQ2200427-5 15526_a7e0fe-25> |
Reporting, Nonconformities, and Follow-up Actions 15526_ff567e-7c> |
6 15526_4b20d5-30> |
18 15526_fff33f-b4> |
LICQ2200427-6 15526_d1fb91-2f> |
Global Legal, Regulatory, and Data Protection Considerations in AI 15526_f189c5-19> |
6 15526_4108cf-77> |
18 15526_014c14-f1> |
By the end of this course, learners will be able to:
1. Understanding ISO/IEC 42001:2023 and the AIMS Framework
- Explain the purpose, structure, and scope of ISO/IEC 42001:2023.
- Interpret key terminology, clauses, and requirements of an Artificial Intelligence Management System.
- Describe how AIMS integrates with organizational strategy, AI lifecycle, and quality systems.
2. AI Risk Management and Ethical Governance
- Identify and assess AI-specific risks including bias, misuse, and unintended outcomes.
- Apply risk mitigation techniques aligned with ethical and responsible AI principles.
- Evaluate governance structures that ensure transparency, accountability, and trust in AI systems.
3. Planning and Preparing for an AIMS Audit
- Develop audit plans in line with ISO 19011 auditing guidelines.
- Define audit scope, criteria, and objectives for Artificial Intelligence Management Systems.
- Prepare necessary documentation and tools for effective audit execution.
4. Conducting AIMS Audits: Techniques and Tools
- Perform systematic audits using interviews, checklists, and document reviews.
- Apply appropriate audit techniques to evaluate compliance and effectiveness of AI controls.
- Assess audit findings against ISO/IEC 42001:2023 and organizational requirements.
5. Reporting, Nonconformities, and Follow-up Actions
- Create clear and professional audit reports identifying strengths, weaknesses, and nonconformities.
- Recommend actionable corrective measures based on audit results.
- Conduct follow-up activities to verify resolution of nonconformities and drive continual improvement.
6. Global Legal, Regulatory, and Data Protection Considerations in AI
- Interpret key global legal and regulatory requirements related to AI systems.
- Assess organizational compliance with data privacy laws such as GDPR and emerging AI legislation.
- Incorporate legal and ethical considerations into audit findings and recommendations.
This diploma is ideal for:
- Professionals responsible for auditing or assessing AI management systems
- Compliance officers working with emerging AI standards and regulations
- IT and data governance managers overseeing responsible AI implementation
- Lead auditors certified in other ISO standards seeking AI specialization
- Risk managers handling AI-related compliance and ethical challenges
- AI developers and system architects aiming to understand audit processes
- Cybersecurity professionals monitoring AI system integrity and threats
- Quality assurance personnel involved in AI lifecycle governance
- Legal and regulatory advisors focused on AI accountability frameworks
- Internal auditors transitioning into AI-specific auditing roles
- Consultants providing AI governance, risk, and compliance services
- Technical managers responsible for enterprise-level AI deployment
- Ethics and trust officers ensuring fairness and transparency in AI
- AI project leads seeking alignment with ISO/IEC 42001:2023 standards
- Professionals preparing organizations for AI certification audits
- Data protection officers concerned with AI and GDPR/AI Act compliance
- Policy makers or analysts working with AI governance frameworks
- Individuals aiming to build careers in AI risk and compliance auditing
- Managers overseeing AI implementation in highly regulated industries
- Trainers and educators seeking to deliver accredited AI audit programs
Assessment and Verification
All units within this qualification are subject to internal assessment by the approved centre and external verification by LICQual. The qualification follows a criterion-referenced assessment approach, ensuring that applicants meet all specified learning outcomes.
To achieve a ‘Pass’ in any unit, applicants must provide valid, sufficient, and authentic evidence demonstrating their attainment of all learning outcomes and compliance with the prescribed assessment criteria. The Assessor is responsible for evaluating the evidence and determining whether the applicants has successfully met the required standards.
Assessors must maintain a clear and comprehensive audit trail, documenting the basis for their assessment decisions to ensure transparency, consistency, and compliance with quality assurance requirements.