As organizations adopt artificial intelligence (AI) for automation, content creation, decision-making, and other critical functions, they must ensure that their management systems support ethical, secure, and responsible use of AI. To meet this need, the ISO 42001 requirements provide a structured framework for establishing and maintaining effective AI management systems (AIMS).
Understanding the 10 comprehensive clauses of ISO 42001 requirements is essential for businesses that want to align AI practices with internationally recognized standards. This article breaks down each clause and explains how they help organizations balance innovation, compliance, and trust in AI-driven processes.
Understanding the Structure of ISO 42001
The International Organization for Standardization (ISO) publishes some of the most widely used frameworks for secure, sound use of technology across a wide variety of contexts. Many of these are co-developed with the International Electrotechnical Commission (IEC).
One of their recent publications is ISO/IEC 42001:2023, which prescribes practices for developing and maintaining artificial intelligence management systems (AIMS). Industry or client expectations may soon mandate ISO 42001 implementation, so understanding its structure is imperative.
The most critical things to understand about the ISO 42001 Clauses are:
- How Clauses 1–3 provide definitions and context for the rest of the framework
- How Clauses 4–7 help establish sound top-down governance for AI systems
- How Clauses 8–10 build up processes for optimal AI management operations
Ultimately, implementing the framework and maintaining AI management systems effectively is easier and much more efficient when working with a compliance and security advisory partner.
Clauses 1–3: Framework Context
There’s no publicly available ISO 42001 PDF, but ISO has made the first three clauses free to preview via its website. This is because the first three clauses help the public understand its scope (Clause 1), the normative references it depends upon (Clause 2), and definitions for technical terms used throughout (Clause 3). These introductory, informational sections are intended to make everything else about the text easier to understand and use for customers.
Clauses 4–7: Sound AI Governance
Moving into the prescriptive portion of the framework, the next three clauses are dedicated to overarching governance. They describe what sound policy for AIMS looks like in theory, starting from an understanding of the organization and its context. Then, they provide guidance on how to develop and deploy governance in practice through leadership, planning, and support.
Clause 4: Context of the Organization
While clauses 1–3 establish context for the framework, this section explains how and why to take a similar approach to contextualizing your organization before implementing your AIMS.
Clause 4 breaks down into the following areas:
- 4.1: The organization and its context – Baseline thresholds for understanding the organization’s information technology (IT) and risk environments that AI exists within.
- 4.2: Interested parties’ expectations – Metrics for understanding the complex web of needs and expectations that various internal and external stakeholders have of AIMS.
- 4.3: AI management system scope – Standards for determining, adjusting, and managing the scope of AIMS relative to both its current and potential use cases.
- 4.4: AI management systems – Methods for establishing formal AIMS and communicating its scope, needs, risks, and other details to all stakeholders.
Clause 5: Leadership in AI Management
This section builds on the context established above and leverages it to create bespoke leadership strategies for your organization’s specific environment and uses for AIMS.
Clause 5’s points of emphasis break down as follows:
- 5.1: Leadership and commitment – Guidance on what leadership should prioritize and the commitments individual leaders need to make with respect to managing AI systems.
- 5.2: AI policy and governance – Standards for how to develop policy and disseminate it across the organization to ensure all stakeholders understand AIMS’ overarching aims.
- 5.3: Roles and responsibilities – Guidance on developing and communicating specific individual responsibilities to ensure accountability and responsibility across all teams.
Clause 6: Planning for AI Management
In this segment, the framework explains how to build and act upon strategic plans for AIMS and broader AI use, starting with how to understand AI risks and opportunities available to you.
Clause 6’s recommendations and specifications include:
- 6.1: Addressing risk and opportunity – Thresholds for understanding risks and opportunities inherent to AIMS and optimizing for them, including three focal points:
-
-
- 6.1.1: General risk management
- 6.1.2: AI-specific risk assessments
- 6.1.3: AI system impact assessments
-
- 6.2: Planning to meet AI objectives – Guidance on how to establish objectives for AIMS (e.g., fairness, accuracy, and security) and then plan proactively to meet them.
- 6.3: Change management – Standards for planning, approving, implementing, accounting for, and ensuring consistency across changes with minimal disruption.
Clause 7: Support for AI Systems
The last of the governance Clauses explains how and why to provide support to AIMS teams, along with the specific kinds of goals that need to be considered in resource development.
The focus areas of Clause 7 are:
- 7.1: AI support resources – General guidance on what kinds of support AIMS will require and when/how to provide them, including budgeting and policy concerns.
- 7.2: Supporting competence – Specific resources AIMS teams need to target competence goals related to operational efficiency, accuracy, and cybersecurity.
- 7.3: Supporting awareness – Specific resources AIMS teams need to target awareness goals related to team and individual understanding and vigilance.
- 7.4: Supporting communication – Specific resources AIMS teams rely on to communicate effectively, ensuring smooth operations and swift issue resolution.
- 7.5: Documenting information – Guidance on how and why to document AIMS information for general reporting and analytical reasons, including:
-
- 7.5.1: General AI support documentation
- 7.5.2: Creating and updating documentation
- 7.5.3: Controlling AI support documentation
Clauses 8–10: Optimal AI Operations
The last three clauses of the framework are focused on operational practices and protocols to ensure efficiency and sustainability. These begin with general system operation (clause 8) and move into performance evaluation (clause 9) and continuous improvement (clause 10). These processes build on governance with practical actions to take for optimal AIMS performance.
Clause 8: AI System Operation
The first of these operational Clauses bridges between governance and practical controls with guidance on planning and assessment activities to ensure efficient, secure AIMS deployment.
Clause 8 breaks down into the following subjects:
- 8.1: Operational planning – Guidance on how to plan for smooth AIMS operations and what kinds of factors to consider with respect to risks, resources, and responsibilities.
- 8.2: Operational AI risk assessments – Practical advice on assessing AI-specific risks relative to operational goals, understanding findings, and mobilizing them as insights.
- 8.3: Operational AI risk treatments – Standards for treating issues identified across AIMS risk assessments, including prioritization, escalation, and follow-up assessments.
- 8.4: Operational system impact assessment – Methods for understanding potential impacts of AI and other risks on AIMS operation and AIMS’ impact on other systems.
Clause 9: AI Performance Evaluation
This section provides insights into the specific ways organizations should evaluate AIMS performance, including metrics to use and practical advice on how to audit and review.
The guidance and primary considerations of Clause 9 are:
- 9.1: Monitoring, measuring, analyzing, and evaluating – Thresholds and metrics for effectively understanding AIMS inputs and outputs relative to all organizational systems.
- 9.2: Conducting internal audits – Guidance on how and why to audit internal use cases and performance of AIMS to ensure staff-wide consistency, with two focal points:
-
-
- 9.2.1: General internal audit practices
- 9.2.2: Creating an internal audit program
-
- 9.3: Conducting management reviews – Tips on reviewing management practices in particular to determine gaps in AIMS efficacy or efficiency, including three main areas:
-
- 9.3.1: General management review practices
- 9.3.2: Processing management review inputs
- 9.3.3: Utilizing management review results
Clause 10: AI System Improvement
The final Clause is focused on how to take steps in the present to ensure improvements into the future—and how to prevent emerging issues from persisting with effective, proactive corrections.
Clause 10 wraps up the framework’s guidance with notes on:
- 10.1: Continual improvement – Standards for ensuring AIMS performance improves over time, consistently, with tips for breaking plateaus and ramping up innovation.
- 10.2: Corrective actions – Practical advice on dealing with issues of nonconformity, noncompliance, and other AIMS issues at the level of system and staff performance.
Other ISO 42001 Considerations
The 10 Clauses of ISO 42001 are comprehensive with respect to understanding and deploying effective AIMS. However, they’re not the only things organizations need to consider if their aim is ISO 42001 certification. There are also Annexes, which provide further guidance.
Annex A provides an accessible reference for all controls required to meet specific AIMS objectives. It’s especially useful for tailoring implementation to development and use risks.
Annex B, then, provides much more robust and granular guidance for implementation:
- B.1: General implementation guidance
- B.2: Policies related to AI and AIMS
- B.3: Internal organizational guidance
- B.4: Resources for AI and AIMS
- B.5: Assessing AIMS impact
- B.6: Understanding AIMS life cycles
- B.7: Implementing data in AIMS
- B.8: Information and communication within AIMS
- B.9: Guidance on using AIMS
- B.10: Third-party relationships
Annex C provides further context for the objectives targeted in Annex A. Beyond general definitions (C.1), it highlights 11 specific objectives for AIMS across specification C.2:
- C.2.1: Accountability
- C.2.2: AI expertise
- C.2.3: Test data quality
- C.2.4: Environmental impact
- C.2.5: Fairness
- C.2.6: Ease of maintenance
- C.2.7: Privacy
- C.2.8: Robustness
- C.2.9: Safety
- C.2.10: Security
- C.2.11: Transparency
C.3 then details sources of risks to these objectives and how to manage them.
Finally, Annex D provides advice for using and implementing AIMS across different industrial contexts, including how to integrate AIMS with other technological systems and standards.
Streamline Your ISO 42001 Certification
AI provides immense value in speeding up repetitive processes and powering more robust and flexible computational tasks than prior technological innovations. But it also comes with unique risks, and it takes sound governance to reap the benefits of AI while minimizing its pitfalls. The ISO 42001 AI framework helps organizations do this through its 10 comprehensive clauses.
RSI Security has helped organizations govern their AI systems effectively, implementing ISO 42001 and other guides to meet their industry and client needs. We believe discipline upfront unlocks freedom later, and we’ll help you rethink your AI management to grow with confidence.
To learn more about our ISO 42001 certification services, contact RSI Security today!
Download Our ISO 42001 Checklist
