Artificial Intelligence Management System (AIMS)
The LICQual ISO/IEC 42001:2023 – Artificial Intelligence Management System (AIMS) Internal Auditor course equips learners with the knowledge and skills to audit AI management systems effectively. As AI continues to transform industries, learners gain the expertise to ensure compliance, enhance performance, and drive continuous improvement within AI operations.
Learners explore the ISO/IEC 42001:2023 standard, focusing on AI governance, risk management, and ethical considerations. The course provides insight into AI-specific auditing principles, techniques, and best practices, enabling learners to evaluate processes for compliance, effectiveness, and reliability.
Through a combination of theoretical instruction and practical exercises, learners develop the ability to plan, conduct, report, and follow up on internal audits tailored to AI systems. Key areas include data integrity, algorithm transparency, risk mitigation, and bias detection.
By completing the course, learners are prepared to strengthen AI quality assurance, support regulatory adherence, and contribute to the ethical and efficient operation of AI systems. This training positions learners as essential contributors to trustworthy and accountable AI governance.
Course Overview
Qualification Title
LICQual ISO/IEC 42001:2023 – Artificial Intelligence Management System (AIMS) Internal Auditor
Total Units
6
Total Credits
40
GLH
120
Qualification #
LICQ2200429
Qualification Specification
To enroll in the LICQual ISO/IEC 42001:2023 – Artificial Intelligence Management System (AIMS) Internal Auditor applicants must meet the following criteria:
|
Qualification# |
Unit Title |
Credits |
GLH |
|---|---|---|---|
|
LICQ2200429-1 |
Introduction to ISO/IEC 42001:2023 and Artificial Intelligence Management Systems |
8 |
24 |
|
LICQ2200429-2 |
Principles and Practices of Internal Auditing in AI Management Systems |
8 |
24 |
|
LICQ2200429-3 |
Conducting Internal Audits for AI Management Systems |
6 |
18 |
|
LICQ2200429-4 |
Reporting and Follow-up on AI Management System Audits |
6 |
18 |
|
LICQ2200429-5 |
Legal, Ethical, and Regulatory Considerations in AI Auditing |
6 |
18 |
|
LICQ2200429-6 |
Preparing for Certification and Enhancing Auditor Competency |
6 |
18 |
By the end of this course, learners will be able to:
Study Unit 1: Introduction to ISO/IEC 42001:2023 and Artificial Intelligence Management Systems
- Explain the structure and key requirements of the ISO/IEC 42001:2023 standard.
- Describe the fundamentals of Artificial Intelligence Management Systems (AIMS).
- Identify the roles and responsibilities of internal auditors within AI governance and risk management frameworks.
Study Unit 2: Principles and Practices of Internal Auditing in AI Management Systems
- Illustrate the purpose and types of internal audits specific to AI management systems.
- Develop effective audit plans and prepare for auditing activities in AI environments.
- Recognize audit criteria and methods for collecting valid audit evidence in AI systems.
Study Unit 3: Conducting Internal Audits for AI Management Systems
- Execute internal audit activities, including interviews, observations, and documentation review.
- Assess AI system controls related to data integrity, security, and compliance.
- Identify and document audit findings and nonconformities linked to AI management risks.
Study Unit 4: Reporting and Follow-up on AI Management System Audits
- Prepare comprehensive and clear audit reports for various stakeholders.
- Communicate audit findings effectively to management and relevant parties.
- Develop and monitor corrective action plans to ensure continual improvement.
Study Unit 5: Legal, Ethical, and Regulatory Considerations in AI Auditing
- Explain global legal and regulatory frameworks relevant to AI auditing.
- Address ethical considerations including AI bias, transparency, and data privacy during audits.
- Maintain auditor confidentiality and professional ethics throughout audit processes.
Study Unit 6: Preparing for Certification and Enhancing Auditor Competency
- Outline steps to facilitate ISO/IEC 42001:2023 certification readiness via internal audits.
- Apply best practices and audit tools to enhance audit effectiveness.
- Plan for continuous professional development to stay current with AI auditing trends.
This diploma is ideal for:
- Professionals involved in AI governance, compliance, and internal control functions
- Internal auditors aiming to specialize in artificial intelligence management systems
- IT auditors seeking to enhance their skills in AI systems assessment and risk evaluation
- AI project managers responsible for system compliance and quality assurance
- Quality managers and coordinators working with ISO or other management system standards
- Compliance officers overseeing the ethical and legal aspects of AI deployment
- Risk managers evaluating AI technologies for operational and strategic impact
- Technical leads and engineers interested in ISO/IEC 42001:2023 compliance frameworks
- Data protection officers and privacy professionals involved in AI-related systems
- Business analysts assessing AI system performance and reliability
- Consultants advising organizations on ISO/IEC 42001 implementation and internal audits
- Professionals preparing organizations for AI management system certification
- Information security specialists responsible for auditing AI system vulnerabilities
- Policy advisors or legal experts working at the intersection of AI and regulatory compliance
- Individuals seeking to future-proof their careers by gaining expertise in AI audit methodologies
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.