Monday, March 16 2026

T 89v23- E-learning - ISO 42001 training package - Readiness and audit of your artificial intelligence management system AIMS version 2023

To implement, manage, and develop an artificial intelligence management system (AIMS), ISO 42001 online training offers a flexible and immediately applicable solution. This e-learning package (reference T 89v23) is designed to support organizations that want to structure their AI practices, achieve ISO 42001 certification, and ensure the performance of their system through a controlled internal audit. By choosing this comprehensive package, you benefit from two complementary training courses (readiness + audit) and their associated materials, while saving €75 on the second course and €82 on the included documents.
225
€
Ex. VAT
T 89v23- E-learning - ISO 42001 training package - Readiness and audit of your artificial intelligence management system AIMS version 2023
 

Description

Objectives of the trainings:

 

Readiness for implementation, certification, maintenance and improvement of your artificial intelligence management system (ISO 42001) in order to:

  • ensure ethical, transparent, reliable, and secure use of artificial intelligence (AI)
  • comply with applicable regulations
  • promote a culture of responsible development and deployment of AI systems

 

To conduct an audit according to ISO 19011 in order to:

  • identify improvement opportunities
  • increase the satisfaction of stakeholders
  • evaluate the performance of the ISO 42001 artificial intelligence management system

 

See the set of documents ISO 42001 artificial intelligence package readiness and internal audit version 2023

 

online TRAINING ISO 42001 READINESS version 2023

Discover the ISO 42001 standard version 2023 and

  • its content
  • its principles
  • its requirements
  • the stakes

 

Get used to

  • artificial intelligence (AI) approach
  • AI management system (AIMS)
  • process approach
  • AI readiness documents
  • AI internal audit documents
  • risk approach
  • AI terminology
  • continual improvement

 

The important and fundamental elements of an AI system

  • AI approach (history, quality management principles, PDCA cycle)
  • process approach (definitions, process types, mapping)
  • context of the company (customer requirements)
  • leadership of top management (commitments, responsibilities)
  • planning of the AIMS (risks, actions, objectives, changes)
  • product realization and service provision (operational control, AI risk assessment and treatment, AI system impact assessment)
  • performance evaluation (monitoring, measure, analysis, internal audits, management review)
  • improvement (nonconformities, corrective actions, continual improvement)
  • controls (Annex A)

 

The menu of the course

  • Presentation
  • MCT Beginning (10 questions)
  • 1 Artificial intelligence
    • 1.1 History
    • 1.2 Application areas
    • 1.3 Principles and steps
  • 2 Standards, definitions, books
    • 2.1 Standards
    • 2.2 Definitions
    • 2.3 Books
  • MCT Information security (8 questions)
  • 3 Process approach
    • 3.1 Process
    • 3.2 Process map
    • 3.3 Process approach
  • MCT Process approach (7 questions)
  • 4 Context
    • 4.1 Context
    • 4.2 Stakeholders
    • 4.3 Scope
    • 4.4 AIMS
  • Case Interested parties
  • Case Customer and need
  • Case Priority tasks
  • Summary of clause 4
  • MCT Context (8 questions)
  • 5 Leadership
    • 5.1 Leadership and commitment
    • 5.2 AI policy
    • 5.3 Roles, responsibilities and authorities
  • Case AI policy
  • Case New line
  • Summary of clause 5
  • MCT Leadership (8 questions)
  • 6 Planning
    • 6.1 Actions to address risks
    • 6.2 Objectives
    • 6.3 Changes
  • Case New risk
  • Case Risk treatment
  • Case Risk register
  • Case Change
  • Summary of clause 6
  • MCT Planning (10 questions)
  • 7 Support
    • 7.1 Resources
    • 7.2 Competence
    • 7.3 Awareness
    • 7.4 Communication
    • 7.5 Documentation
  • Case Importance of work
  • Case Communication
  • Summary of clause 7
  • MCT Support (9 questions)
  • 8 Operation
    • 8.1 Operational planning and control
    • 8.2 AI risk assessment
    • 8.3 AI risk treatment
    • 8.4 AI system impact assessment
  • Case Design review
  • Case Process stability
  • Summary of clause 8
  • MCT Operation (9 questions)
  • 9 Performance
    • 9.1 Inspection, analysis and evaluation
    • 9.2 Internal audit
    • 9.3 Management review
  • Case Audit readiness
  • Case Auditor question
  • Case Management review
  • Summary of clause 9
  • MCT Performance (9 questions)
  • 10 Improvement
    • 10.1 Continual improvement 
    • 10.2 Nonconformity and corrective action
  • Case Nonconformities
  • Case Kaizen and problem
  • Summary of clause 10
  • MCT Improvement (10 questions)
  • Annex A
  • A.2 Policies related to AI
  • Summary of annex A.2
  • MCT Annex A.2 (6 questions)
  • A.3 Internal organization
  • Case Responsibilities
  • Summary of annex A.3
  • MCT Annex 3 (7 questions)
  • A.4 Resources for AI systems
  • Case Resources
  • Summary of annex A.4
  • MCT Annex 4 (8 questions)
  • A.5 Assessing impacts of AI systems
  • Case AI system impacts
  • Summary of annex 5
  • MCT Annex 5 (7 questions)
  • A.6 AI system life cycle
  • Case Life cycle
  • Summary of annex A.6
  • MCT Annex A.6 (8 questions)
  • A.7 Data for AI systems
  • Case Data
  • Summary of annex A.7
  • MCT Annex 7 (6 questions)
  • A.8 Information for interested parties of AI systems
  • Case Response to an incident
  • Case Incident log
  • Summary of annex A.8
  • MCT Annex 8 (6 questions)
  • A.9 Use of AI systems
  • Case Use of AI systems
  • Summary of annex 9
  • MCT Annex 9 (6 questions)
  • A.10 Third-party and customer relationships
  • Case Selecting suppliers
  • Summary of annex 10
  • MCT Annex 10 (6 questions)
  • MCT End (20 questions)

 

online course internal audit of your artificial intelligence management system ISO 42001 version 2023

 

Discover the internal audit in an ISO 42001 version 2023 certified company and

  • locate the audit in the artificial intelligence approach
  • identify the stakes
  • understand the requirements
  • control the tools

 

Get used to

 

The important and fundamental elements of an internal audit

  • scope
  • normative references
  • principles
  • audit program (responsibilities, records)
  • audit conducting (objectives, evidence, conclusions)
  • auditor competence (knowledge, training)

 

The menu of the course

  • Presentation
  • MCT (multiple-choice test) Beginning (10 questions)
  • 1 Scope
  • 2 Normative references
  • 3 Definitions
  • 4 Principles
    • 4.1 Management principles
    • 4.2 Audit principles
    • 4.3 AIMS performance
  • MCT Internal audit (7 questions)
  • 5 Audit program
    • 5.1 General
    • 5.2 Objectives
    • 5.3 Risks
    • 5.4 Establishing
    • 5.5 Implementing
    • 5.6 Monitoring
    • 5.7 Reviewing and improving
  • Case New risk
  • Case Audit program
  • MCT Audit program (11 questions)
  • 6a Audit preparation
    • 6.1 General
    • 6.2 Initiating
      • 6.2.1 First contact
      • 6.2.2 Situations and feasibility
    • 6.3 Preparing the audit
      • 6.3.1 Document review
      • 6.3.2 Audit plan
  • Case Nonconformities
  • Case Audit readiness
  • MCT Audit preparation (8 questions)
  • 6b Conduct an audit
    • 6.4 Audit activities
      • 6.4.1 Opening meeting
      • 6.4.2 Audit evidence
      • 6.4.3 Audit conclusions
    • 6.5 Audit report
    • 6.6 Completing the audit
    • 6.7 Audit follow-up
  • Case Audit finding
  • Case External audit nonconformity
  • Case Audit report
  • Case Management review
  • MCT Conduct an audit (8 questions)
  • 7 Competence and evaluation of auditors
    • 7.1 General
    • 7.2 Auditor competence
    • 7.3 Evaluation criteria
    • 7.4 Evaluation methods
    • 7.5 Auditor evaluation
    • 7.6 Improving competence
  • Case Auditor question
  • Case Auditor independence
  • MCT Auditor competence (7 questions)
  • MCT End (20 questions)