ISO 42001 Requirements Explained Clause by Clause

Artificial Intelligence is transforming business at breakneck speed, but with great power comes great responsibility. One flawed algorithm can derail customer trust or even invite regulatory scrutiny. In fact, a 2025 survey found that only 25% of organizations have a fully implemented AI governance program, despite 86% being aware of upcoming AI regulations. This gap highlights why AI governance is not just a buzzword; it is a necessity. Enter ISO/IEC 42001:2023, the world’s first international standard for AI management systems, created to ensure AI is developed and used responsibly. Published in late 2023, ISO 42001 gives organizations a structured blueprint to tame the “Wild West” of AI in a secure, ethical, and transparent way.

What exactly is ISO 42001?

It is a framework for an Artificial Intelligence Management System (AIMS). It is like an AI-specific equivalent of ISO 27001 (information security) or ISO 9001 (quality). It follows the same high-level structure as those standards (Clauses 4 through clause 10 cover the core requirements). That means if you are familiar with other ISO management systems, you will recognize the layout: context, leadership, planning, support, operation, evaluation, and improvement. But ISO 42001 also adds AI-specific twists, for example, expanded planning and operational controls addressing AI’s impact on individuals and society. It also comes with an Annex A (just like ISO 27001) listing recommended AI control measures organizations can adopt to mitigate risks.

ISO 42001:2023 Requirements Clause-by-Clause Explanation

Clause 1:  Scope

ISO/IEC 42001 specifies the requirements for establishing and maintaining an AI Management System within the context of an organization.

This clause defines:

• Applicability to organizations that develop, provide, or use AI systems.
• Coverage of AI lifecycle stages:
• Design
• Development
• Deployment
• Operation
• Monitoring
• Modification
• Decommissioning
• Alignment with organizational objectives, legal obligations, and interested party expectations.

The standard applies regardless of organizational size, sector, or AI maturity level.

Clause 2: Normative References

ISO/IEC 42001 relies on:

• ISO/IEC 22989:2022: Artificial Intelligence Concepts and Terminology

This reference ensures:

• Consistent interpretation of AI-related terms
• Alignment between governance, technical, legal, and operational teams
• Audit-ready documentation using internationally accepted definitions

Clause 3: Terms and Definitions

This clause establishes a common language for AI governance, including key concepts such as:

• AI Management System
• Interested Parties
• AI Risk
• AI System Impact Assessment
• Governing Body
• Data Quality
• Statement of Applicability

Auditors validate not only documentation but also the organization’s understanding and correct use of these terms across policies, procedures, and operational practices.

Clause 4: Context of the Organization

Every journey starts with a map. Clause 4 is all about  (4.1) understanding your organization’s context, the foundation on which your AI governance is built. This clause (4.2) requires you to understand the needs and expectations of interested parties that affect your AIMS, from technological trends and market conditions to legal, ethical, and even environmental considerations. You also must pin down who has a stake in your AI: customers, regulators, employees, suppliers, and what they expect or need. In short, (4.3) defines the scope of your AI management system and the world it operates in. Are you deploying an AI-driven customer service chatbot? An automated medical diagnosis tool? Clause 4 says: document what’s in scope and what’s not, and be crystal clear about the context in which your AI systems run.

Why is this important? If you do not understand your operating environment, you can not effectively manage AI risks or set relevant objectives. Clause 4 ensures AI governance is not happening in a vacuum. By examining business strategy, culture, regulatory landscape, and stakeholder expectations up front, you align your AIMS with your organization’s purpose and risk profile.

Clause 5: Leadership

If Clause 4 sets the stage, Clause 5 brings in the actors, your (5.1) leadership and commitment. Top management’s commitment is the driving force behind effective AI governance. Clause 5 requires senior leaders to actively own and direct the AIMS. This starts with establishing an (5.2) AI policy: a high-level statement of principles and intentions for responsible AI use, aligned with your organization’s values and strategy. Management must approve and communicate this policy, ensuring it is not just a document on paper but a living guide for the company’s AI efforts.

Beyond policy, Clause 5 mandates clear (5.3) roles, responsibilities, and authorities. Who is accountable for AI compliance? Who oversees risk assessments? From the C-suite to technical teams, everyone should know their part.

Clause 6: Planning

Now we dive into the nitty-gritty of risk management and objective setting for AI. Clause 6 is one of the heftiest sections, and for good reason, AI introduces unique risks (think bias, security vulnerabilities, unintended misuse) and unique opportunities. This clause requires organizations to (6.1) proactively identify AI-related risks and opportunities, then plan how to address them. It is all about being ahead of the curve rather than reacting to problems later. Key tasks under Clause 6 include conducting thorough (6.1.2) AI risk assessments and impact analyses. You need a consistent process to evaluate how likely and severe potential AI failures or threats are, from a data breach in an AI model to an algorithm inadvertently discriminating.

Clause 6 also says (6.2) set AI objectives and plan for changes. Based on your risks and business goals, define concrete targets, maybe to reduce model bias by X%, or to achieve a certain accuracy with explainability, and outline the steps, owners, and timelines to achieve them.

ISO 42001 requires a link between your risk treatments and a set of recommended controls in Annex A. Specifically, you must determine which controls (from a list of 38 AI controls) are needed for your risks and compare them against Annex A to ensure you did not miss anything essential.

Clause 7: Support

You have got a plan, now you need the muscle to execute it. Clause 7 covers the supporting resources and processes required to keep your AI management system effective. It is like an infrastructure for AI governance. First, (7.1) Resources: Do you have the right people, skills, tools, and budget for managing AI responsibly? The standard says you must ensure adequate resources are in place. That could mean hiring AI Ethics Specialists, investing in model monitoring software, or simply allocating time for teams to document and review AI processes.

​​Next, (7.2) Competence and  (7.3) Awareness: ISO 42001 emphasizes training and awareness so that everyone involved in AI (from Developers to business users) knows their role in maintaining ethical AI. Do your Data Scientists understand bias mitigation techniques? Are your Project Managers aware of the AI Policy and the consequences of not following it? Clause 7 asks you to document competencies and ensure ongoing training, building a knowledgeable workforce around AI governance.

(7.4) Communication is another piece, establishing how you will internally and externally communicate information about your AI management system. For example, you might set protocols for reporting AI incidents up the chain, or decide what you will publicly disclose about your AI systems to customers. Good communication ensures transparency and keeps stakeholders in the loop, which in turn builds trust.

Finally, Documented (7.5) Information: this is the crucial part. You need to create and control documentation for your AIMS: policies, procedures, risk assessments, technical documentation of AI models, decision logs, etc. And you must manage these documents properly (version control, approvals, access control, retention).

Clause 8: Operation

Clause 8 is where the rubber meets the road; it is about executing your AI processes under controlled conditions across the AI system lifecycle. In other words, implement all the policies, plans, and resources from earlier clauses to manage real AI systems. This clause covers (8.1) operational planning and control: you need to plan how AI-related activities will be carried out and ensure they are done in line with your governance requirements. From designing or procuring an AI system to testing, deployment, and ongoing maintenance, there should be a controlled process at each step. If you use third-party AI services or data, those also need to be under control (no more “rogue AI projects” popping up without oversight).

A critical aspect of Clause 8 is continuing the (8.2) AI risk management loop. ISO 42001 expects you to regularly assess AI risks during operation, not just once during planning. For example, if you make a major change to an AI model or its data, you should reassess risks (Could new biases be introduced? Did the change affect model performance?). Similarly, you must carry out and update your (8.3) AI risk treatment plans as new risks emerge or old ones persist.

Additionally, Clause 8 extends the idea of (8.4) AI risk impact assessments into the operational phase. Earlier in Clause 6, you likely did an initial impact assessment; Clause 8 says to perform these regularly, especially after significant changes, and keep records.

Clause 8 also touches on incident response: be prepared to handle AI incidents or deviations. If something goes wrong, say your AI-powered credit scoring system starts showing discriminatory patterns or a critical AI service goes down, you need predefined procedures to respond and correct the course.

Clause 9: Performance Evaluation

By this point, you have set up and are operating an AI management system. Clause 9 asks, “How do you know it is working?” This clause is all about (9.1) monitoring, measurement, analysis, and evaluation of the performance of both your AI systems and the governance processes around them. In practice, that means defining metrics and indicators to track. For example, you might monitor the accuracy of an AI model, the number of AI incidents or near-misses, training completion rates on AI ethics, or compliance metrics against ISO 42001 requirements. Organizations need to regularly analyze this data to gauge if objectives are being met and where improvements are needed.

Clause 9 also introduces the need for (9.2) internal audits of the AIMS. This is a familiar concept from other ISO standards: periodically (say, annually) have an internal team or independent function audit your AI management system against ISO 42001 requirements. Are we following our processes? Are documents in order? Did we treat that identified risk properly? The audit should be objective and thorough, and the results must be documented. Any findings (nonconformities) will feed into Clause 10 (improvement).

Another piece is (9.3) management review, top management should routinely review the AIMS performance. In these reviews, leadership looks at metrics, audit results, issues encountered, and opportunities. The idea is to evaluate if the AIMS remains effective and suitable for the organization’s needs. Maybe new regulations have come in, or business objectives shifted. Is the AI governance still aligned? Management review is where strategic adjustments can be made, and resources reallocated if necessary.

Clause 10: Improvement

No management system would be complete without a focus on (10.1) continual improvement. Clause 10 is the final clause, and it reinforces the idea that AI governance is not a one-time setup; it is an evolving program. Organizations are required to have processes to (10.2)identify nonconformities (problems) and take corrective actions. If something in your AIMS is not working, say an audit finds a gap, or an AI incident exposes a flaw in your process, Clause 10 compels you to investigate the root cause, fix it, and make sure it does not happen again. This is classic ISO: find the issue, correct it, and prevent recurrence.

Moreover, Clause 10 asks for proactive improvement beyond just fixing problems. It is about the continual improvement of the AIMS’s effectiveness. This could involve updating policies as new best practices emerge, setting new, higher standards for AI model performance, or integrating new tools to automate parts of your governance. Given how quickly AI technology and regulations change, this clause future-proofs your AI management.

In essence, Clause 10 creates a culture of learning and adaptability. Every incident, audit finding, or piece of feedback is an opportunity to refine your AI governance. Over time, this makes your management system more resilient and mature. It is like a kaizen (continuous improvement) but applied to AI processes and policies.

Annex A: AI Controls (and Their Role)

After Clause 10, ISO 42001 includes Annexes A through D. The most critical is Annex A, which provides a comprehensive list of 38 reference controls for AI governance. Annex A is like a toolbox of security and ethics controls, covering things like data management, bias mitigation, transparency, human oversight, third-party management, etc. For example, there are controls on having an AI ethics policy, roles and responsibilities, data quality checks, AI impact assessments, incident response procedures, and more. These are not one-size-fits-all; organizations are expected to choose the controls relevant to their identified risks and context. Annex B then provides implementation guidance for each control, while Annexes C and D give additional information on potential AI objectives, risk sources, and how to integrate AIMS with other management systems.

Under ISO 42001, Annex A controls are not automatically mandatory, but there is a twist: Clause 6.1.3 (in Planning) requires you to compare your risk treatment controls against Annex A’s list. This means if you decide not to implement a certain Annex A control, you should be conscious of that choice and document why it is not applicable or how you address that risk in another way. Conversely, if you need a control that is not in Annex A, you are free to add it, just document it. During certification, Auditors will check that you have rationalized your control set against Annex A, ensuring no glaring gaps.

How Does ISO 42001 Translate into Career & Business Impact with InfosecTrain?

ISO 42001 is more than a compliance checklist; it is a framework for turning responsible AI governance into a business advantage. By following Clauses 4–10, an organization lays down a solid foundation: understanding context, demonstrating strong leadership, proactively managing risks, supporting the effort with resources, operationalizing controls, continuously evaluating performance, and improving over time. This holistic, clause-by-clause approach ensures that AI systems are not only innovative but also safe, fair, and accountable.

That’s exactly where InfosecTrain’s ISO 42001:2023 Lead Auditor Certification Training bridges the gap between theory and execution.

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