ISO/IEC 42001:2023 Artificial Intelligence Management Systems Foundation Level Training and Certification Program

Programme Summary

Build an understanding of AI management using ISO/IEC 42001:2023. Participants connect AI governance, lifecycle risks and impact assessment evidence with responsibilities and performance measures. Exercises based on an enterprise AI service deployment case develop requirement interpretation, evidence selection and gap recognition. The programme establishes a foundation for responsible development, procurement and use of AI systems and further implementation or auditor development.

Training Objectives

1 Explain AI management requirements; 2 Connect requirements with operational responsibilities; 3 Recognise unassessed AI impacts; 4 Select relevant implementation evidence; 5 Prepare for further practical development.

Learning Outcomes

1 Define AI roles and system scope; 2 Distinguish AI risk and impact assessments; 3 Justify control applicability decisions; 4 Evaluate lifecycle and monitoring evidence; 5 Identify accountable human oversight arrangements.

Target Audience

AI Governance Managers; AI Product Managers; Technology Risk Managers; Data Governance Managers; Management System Coordinators.

Target Industries

Enterprise Software; Financial Services; Healthcare Technology; Government Digital Services; Industrial Automation.

Course Contents

• Module 1 Standard Purpose and Practical Application: Management system purpose and intended outcomes; Requirement guidance and evidence distinctions; Course case scope and learning responsibilities.
• Module 2 AI Roles Context and System Scope: AI provider developer and user roles; System inventory and intended use context; Interested parties and organisational boundaries.
• Module 3 AI Leadership and Governance Planning: AI policy and accountable responsibilities; Objectives risks and management resources; Competence communication and documented information.
• Module 4 AI Risk Assessment and Treatment: Risk criteria and lifecycle risk scenarios; Risk analysis evaluation and treatment ownership; Control selection and applicability justification.
• Module 5 AI System Impact Assessment: Affected people groups and societal contexts; Intended use foreseeable misuse and consequences; Impact assessment evidence and review triggers.
• Module 6 AI Lifecycle Controls and Accountability: Design development and deployment responsibilities; Verification validation and operational acceptance; Human oversight and controlled lifecycle changes.
• Module 7 Data and Information Governance: Data provenance suitability and quality; Data preparation access and lifecycle controls; Documentation transparency and stakeholder information.
• Module 8 AI Suppliers Use and Monitoring: Supplier responsibilities and acquisition interfaces; Responsible use and deployment safeguards; Performance monitoring incident reporting and escalation.
• Module 9 AI Assurance and Improvement: Management system and control effectiveness measures; Internal audit and management review; Corrective action and changing AI risks.
• Module 10 Interpreting Requirements in Context: Mandatory requirements and proportionate application; Interfaces with applicable legal obligations; Supported judgements and unresolved interpretation issues.
• Module 11 Selecting Relevant Management System Evidence: AI risk and impact assessments; AI control applicability records; AI lifecycle and monitoring records.
• Module 12 Foundation Application Workshop: Map responsibilities within the supplied case; Match controls to relevant requirements; Explain gaps and practical next steps.

Assessment

• 60 single best answer questions, including applied scenarios; one mark per question.
• 90 minute invigilated digital examination with identity verification. Approved accessibility adjustments preserve the assessed competence.
• Clean standard text and supplied case documents permitted; internet, messaging and external AI tools prohibited.
• Individual applied assessment (45 minutes): Using a supplied enterprise AI service deployment case, produce an AI system inventory and responsibility map, link three controls to relevant requirements and explain one unresolved weakness.
• Assessment criteria: Accurate interpretation of AI management requirements; Relevant use of AI risk and impact assessments; Clear connection between controls responsibilities and identified gaps.
• Pass each component separately: 45/60 written marks (75%) and at least 70% on the applied task.
• All mandatory criteria must pass: Do not fabricate evidence or knowingly present unsupported conformity conclusions.
• Individual results and feedback are provided. One reassessment may follow coaching under the published enrolment terms.

Certification

• Successful learners receive a TQCSI Arabia digital Certificate of Successful Completion.
• The certificate records the learner name, exact programme title, teaching hours, completion date and unique verification reference.
• Verified identity, full attendance and separate written and applied passes are required; all mandatory critical criteria must be met.
• Proposed issue target: within 30 calendar days of approved results and settlement of applicable fees.
• Records assessed foundation knowledge of AI management; it does not establish professional auditor status, independent personnel certification or organisational certification.
• Attendance confirmation may record completed hours for unsuccessful learners; it does not certify successful completion.

Programme Profile

Number of daysNumber of daysNumber of days

333

Total teaching hoursTotal teaching hoursTotal teaching hours

18 hours; breaks, pre course work and formal final assessments excluded.18 hours; breaks, pre course work and formal final assessments excluded.18 hours; breaks, pre course work and formal final assessments excluded.

Delegates allowedDelegates allowedDelegates allowed

Maximum 20 delegates.Maximum 20 delegates.Maximum 20 delegates.

Training prerequisitesTraining prerequisitesTraining prerequisites

No formal qualification required. Familiarity with AI management activities and everyday business processes is recommended.No formal qualification required. Familiarity with AI management activities and everyday business processes is recommended.No formal qualification required. Familiarity with AI management activities and everyday business processes is recommended.

Pre course assignment and assessmentPre course assignment and assessmentPre course assignment and assessment

Complete a 20-minute diagnostic and identify how AI risk and impact assessments support a supplied operational case.Complete a 20-minute diagnostic and identify how AI risk and impact assessments support a supplied operational case.Complete a 20-minute diagnostic and identify how AI risk and impact assessments support a supplied operational case.

End of course assessmentEnd of course assessmentEnd of course assessment

60 question written exam (90 minutes) and individual applied task (45 minutes).60 question written exam (90 minutes) and individual applied task (45 minutes).60 question written exam (90 minutes) and individual applied task (45 minutes).

Passing criteriaPassing criteriaPassing criteria

75% written and 70% applied, passed separately; full attendance. All mandatory criteria must pass.75% written and 70% applied, passed separately; full attendance. All mandatory criteria must pass.75% written and 70% applied, passed separately; full attendance. All mandatory criteria must pass.