T 29v23 - E-Learning - ISO 42001 readiness artificial intelligence management system version 2023
E-Learning (online course) - Implementation, maintenance, certification and improvement of your artificial intelligence management system ISO 42001 version 2023 - You save 50 euros on the documents provided!
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See the online game G 29 IZOGOOD® 42001 Decrypt the ISO 42001 standard while having fun soon See the online course T 49v23 ISO 42001 Internal audit soon See the online training package T 89v23 ISO 42001 readiness and internal audit soon |
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| Result of the training satisfaction survey : | 83.2% | Last update on January 24, 2026 |
Description of the online course for your AI management system ISO 42001: 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
- 1.1 History
- 2 Standards, definitions, books
- 2.1 Standards
- 2.2 Definitions
- 2.3 Books
- 2.1 Standards
- MCT Information security (8 questions)
- 3 Process approach
- 3.1 Process
- 3.2 Process map
- 3.3 Process approach
- 3.1 Process
- MCT Process approach (7 questions)
- 4 Context
- 4.1 Context
- 4.2 Stakeholders
- 4.3 Scope
- 4.4 AIMS
- 4.1 Context
- 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
- 5.1 Leadership and commitment
- 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
- 6.1 Actions to address risks
- 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
- 7.1 Resources
- 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
- 8.1 Operational planning and control
- 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
- 9.1 Inspection, analysis and evaluation
- 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
- 10.1 Continual improvement
- 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)
Read more about the online course ISO 42001
FAQ about ISO 42001
What is ISO 42001?
ISO 42001 (ISO/IEC 42001:2023) is the first international standard for managing Artificial Intelligence Management Systems (AIMS). It defines the requirements for planning, implementing, operating, monitoring, and continually improving AI processes, ensuring the responsible, ethical, transparent, and reliable use of this technology.
Is adopting ISO 42001 mandatory?
No. Certification is not mandatory, but it has become an industry benchmark. Organizations that adopt this ISO demonstrate their commitment to good AI governance practices, thereby mitigating legal and reputational risks and strengthening their brand.
What type of company should apply for ISO 42001?
Any organization that develops or uses AI can benefit from this model, including:
- AI solution providers (platforms, algorithms, machine learning)
- enterprise users (banking, healthcare, utilities, industry)
- regulated or high-risk sectors (finance, healthcare, transportation)
- companies with innovation programs (such as in-house AI labs)
- suppliers in large value chains (automotive, pharmaceutical, government)
- AI startups raising funds
What are the main requirements of the standard?
ISO 42001 follows the high-level structure of ISO standards and focuses on Clauses 4 to 10 and Annex A:
Clause 4: Context of the organization and stakeholders
Clause 5: Leadership and management commitment
Clause 6: Risk approach planning (bias, security, confidentiality)
Clause 7: Support (resources, competence, documentation)
Clause 8: Implementation (planning, risks)
Clause 9: Performance evaluation (monitoring, audits, management review)
Clause 10: Continual improvement (improvement and corrective action)
Annex A: Control objectives and controls
What are the benefits of implementing ISO 42001 for an organization?
- enhanced data security
- early risk management (algorithmic bias, privacy protection)
- stakeholder trust (customers, investors, regulators)
- competitive advantage in tenders and partnerships
- operational efficiency through PDCA cycles
- regulatory alignment and social responsibility
What are the common challenges encountered when adopting ISO 42001?
- cultural resistance to new processes
- technical complexity and specificity of AI metrics
- lack of internal expertise in AI risk and ethics
- initial costs of consulting, technology, and training
- integration with existing systems and workflows
- ongoing maintenance of the management system after certification
How can these challenges be overcome?
- communication and workshops to engage leaders and teams
- partnerships with AI governance experts or consulting firms
- training and skills recognition programs
- development of a business case to demonstrate ROI and risk mitigation
- process mapping and use of governance APIs/platforms
- regular internal audit cycles and KPI monitoring
What is the step-by-step process for implementing ISO 42001?
- gap analysis: Diagnosis of AI maturity level
- policy and objectives: Formalization of AI guidelines and objectives
- governance: Creation of a committee and definition of roles
- processes and controls: Design of data flows, models, and audits
- training: Training, e-learning, and internal awareness
- internal audit: List of questions, identification of nonconformities, and adjustments
- certification: Selection of a certification body and completion of the certification audit
Why is ISO 42001 strategic?
ISO 42001 addresses the challenges of transparency, ethics, security, and risk management related to AI. It fosters stakeholder trust and supports the rapid growth of the AI market.
How to implement ISO 42001?
Implementation relies on clear governance, proactive AI risk management, documented decisions, and the application of the PDCA cycle.
What are the benefits (ROI) of ISO 42001?
Adopting ISO 42001 helps reduce AI-related incidents, improve trust, anticipate regulations, and gain a competitive advantage. 72% of organizations
Certified organizations have improved their brand image.
What are some concrete use cases?
One manufacturer reduced production downtime by 30% by securing its automated lines thanks to the standard; another company detected an algorithmic bias in its credit system.
Which standards are related?
ISO 42001 complements frameworks such as the GDPR, the European AI Act, ISO 27001, and ISO 9001, facilitating risk management and international compliance.
What tools/methods are recommended?
The standard relies on the PDCA (Plan-Do-Check-Act) cycle for continuous improvement and recommends the establishment of governance committees and the use of auditing techniques.
How to manage governance/risks?
ISO 42001 mandates the designation of responsibilities, the documentation of decisions, traceability, and the proactive management of technical, legal, and ethical risks.
Goal of the module:
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
- improved image of the company
- a step ahead of the competition
- enhanced customer satisfaction
- better economic results
- increased daily efficiency
- staff is aware, consulted, motivated and proud
- high level of risk control
- reduced insurrance costs
- profitable engagement for all
- best practices valorized
- formalization of knowledge
- process control
- legal obligations updated
Notions of ISO 42001
Any person involved in the preparation and implementation of an ISO 42001 artificial intelligence management system:
- pilot of ISO 42001 certification project
- director
- AI manager
- information security manager
- computer technician
- AI technician
- quality director
- quality manager
- metrology manager
- safety manager
- maintenance manager
- project leader
- quality correspondent
- quality technician
- quality assistant
- quality operator
- quality mission personnel
- internal auditor
- student
21 hours online on average (according to knowledge and aptitudes, this duration can vary individually). One hour of online training is equivalent to at least 2 hours of training on the spot.
At the end of the module, you will be able to:
- interpret the requirements of the ISO 42001 standard
- take part in the development of the AI policy and objectives
- take part in the implementation of the document system
- understand and implement the 7 quality management principles
- evaluate the ISO 42001 certification project
- be familair with the steps and tools for implementation of your AIMS
Methods and tools
- dedicated Internet site
- specific online training module
- Open and Distance Learning (ODL) teaching
- your training history:
- the time you have passed on each clause and subclause of the module
- the record of the score of all your trials of the MCTs (multiple-choice tests)
- level test at beginning of the training
- 19 tests (MCTs) with comments, notes on a 20 point scale and recommendations
- videos
- true stories
- good practices
- bad practices
- case studies
- jokes
- games
- online tutorial :
- a follow up of acquired material and the progress of each trainee
- online or by e-mail within 24 hours
- personalized answers to questions
- advice and recommendations about documents, books and useful links
- delivered certificate of attendance and mastery at the end of the training (example)
Access to the course is 60 days from the date of validation of your order. This period will be renewed for free upon a simple request within 6 months
ISO 42001 requirements version 2023
Test your knowledge of the requirements of ISO 42001 version 2023 in relation to the clauses and sub-clauses of the standard by answering the questions of the:
Overview of ISO 42001 Clauses 4-10 2' 53"
Annex 2: Crafting AI Policies in ISO 42001 2' 23"
Annex 3: Structuring AI Roles in ISO 42001 2' 15"
Annex 4: Managing AI Resources in ISO 42001 3' 50"
Annex 5: Assessing Impacts of ISO 42001 AI Systems 4' 2"
Annex 6: AI Systems Lifecycle of ISO 42001 8' 50"
Annex 7: Data for AI Systems in ISO 42001 4' 18"
Annex 8: Information for Interested Parties of ISO 42001 3' 38"
Annex 9: Use of AI Systems in ISO 42001 3' 57"
Annex 10: Third-party and Customer Relationships in ISO 42001 3' 52"
How to Implement AI Management Systems (AIMS) | 7 Step Guide to ISO 42001 15' 44"
ISO 42001 Structure & AIMS Scope Explained 17' 36"
ISO 42001 Explained: The New AI Governance Standard & What It Means for Your Business 18' 55"
ISO 42001 Lead Auditor: Master AI Governance & Risk Management 24' 49"
ISO 42001 - AI Management Systems Masterclass 28' 54"
ISO/IEC 42001 AI Governance and Implementation Bootcamp 1h 51' 28"
Unlocking the Power of AI Management Systems - A Workshop on ISO/IEC 42001 2h 52' 01"
Here is a MCT (Multiple-choice test) to evaluate, before beginning, the level of your knowledge for this course. (One or more correct answers are possible). You can start again as many times you wish.
1. The ISO 42001standard defines for an information security management system:
2. The statement of applicability (SoA) allows you to:
3. Assessing the risks allows us to:
4. Staff are made aware of, among other things:
5. Examples of processes that can be outsourced:
6. The internal audit:
7. Examples of nonconformity treatment activity:
8. The AI policy:
9. What is the main objective of Annex A.4?
10. Examples of data sources:
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