ISO/IEC 42001:2023 AI Management Systems Internal Auditor

About Course

Develop internal audit skills for ai management systems. Includes 36 text lessons with written audit exercises, a 40-question examination and a practical case covering AI risk, impact assessment, data, release and human oversight. Fourteen hours including assessment. AED 499.

LO01: Audit the processes covered by welcome and ai management foundations.
LO02: Audit the processes covered by context, leadership and objectives.
LO03: Audit the processes covered by ai risks, treatment and applicability.
LO04: Audit the processes covered by ai system impact assessment.
LO05: Audit the processes covered by people, resources and information.
LO06: Audit the processes covered by data governance throughout the life cycle.
LO07: Audit the processes covered by responsible design and evaluation.
LO08: Audit the processes covered by deployment, operation and responsible use.
LO09: Audit the processes covered by suppliers, users and incident response.
LO10: Prepare a risk-based programme, audit plan and justified sample.
LO11: Interview, corroborate evidence, calculate measures and write supported findings.
LO12: Report conclusions, evaluate corrective action and verify effectiveness.

Course Content

Welcome and AI management foundations
Audit the processes covered by welcome and ai management foundations.

Internal auditor role and course route
AI systems, models and responsible use
Read the standard: clauses, annexes and PDCA

Context, leadership and objectives
Audit the processes covered by context, leadership and objectives.

AI risks, treatment and applicability
Audit the processes covered by ai risks, treatment and applicability.

AI system impact assessment
Audit the processes covered by ai system impact assessment.

People, resources and information
Audit the processes covered by people, resources and information.

Data governance throughout the life cycle
Audit the processes covered by data governance throughout the life cycle.

Responsible design and evaluation
Audit the processes covered by responsible design and evaluation.

Deployment, operation and responsible use
Audit the processes covered by deployment, operation and responsible use.

Suppliers, users and incident response
Audit the processes covered by suppliers, users and incident response.

Plan the internal audit
Prepare a risk-based programme, audit plan and justified sample.

Conduct the audit and evaluate evidence
Interview, corroborate evidence, calculate measures and write supported findings.

Report findings and verify action
Report conclusions, evaluate corrective action and verify effectiveness.

Assessment

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About Course

What Will You Learn?

Course Content

Welcome and AI management foundations Audit the processes covered by welcome and ai management foundations.

Internal auditor role and course route

AI systems, models and responsible use

Read the standard: clauses, annexes and PDCA

Context, leadership and objectives Audit the processes covered by context, leadership and objectives.

Context, interested parties and the AIMS scope

Leadership, policy, responsibilities and concerns

Objectives, opportunities and planned changes

AI risks, treatment and applicability Audit the processes covered by ai risks, treatment and applicability.

Recognize AI risks and opportunities

Assess AI risks consistently

Treat risks and prepare the Statement of Applicability

AI system impact assessment Audit the processes covered by ai system impact assessment.

Plan an AI system impact assessment

Consider individuals and groups

Consider society and communicate assessment findings

People, resources and information Audit the processes covered by people, resources and information.

Provide and document suitable resources

Build competence and practical awareness

Communicate and control documented information

Data governance throughout the life cycle Audit the processes covered by data governance throughout the life cycle.

Select and acquire suitable data

Evaluate data quality and representativeness

Maintain provenance and control data preparation

Responsible design and evaluation Audit the processes covered by responsible design and evaluation.

Turn responsible design into clear requirements

Distinguish verification and validation

Evaluate limitations, security and difficult cases

Deployment, operation and responsible use Audit the processes covered by deployment, operation and responsible use.

Deploy and change AI systems under control

Monitor operation, documentation and event logs

Use AI responsibly and maintain effective human oversight

Suppliers, users and incident response Audit the processes covered by suppliers, users and incident response.

Manage suppliers, customers and shared responsibilities

Inform users and provide reporting routes

Respond to incidents and retire systems responsibly

Plan the internal audit Prepare a risk-based programme, audit plan and justified sample.

Risk based audit programmes

Objectives scope criteria and planning

Sampling and audit working papers

Conduct the audit and evaluate evidence Interview, corroborate evidence, calculate measures and write supported findings.

Opening interviews and observation

Corroboration and performance measures

Supported findings and audit conclusions

Report findings and verify action Report conclusions, evaluate corrective action and verify effectiveness.

Closing meetings and management review

Correction cause analysis and action plans

Effectiveness follow up and assessment