Discussions of ISO/IEC 42001 often start with certification. For an organization developing its AI capabilities, a more fundamental starting question is how AI use is managed consistently. Who sets objectives, how are risks reviewed, and what happens when practice does not follow policy? A management system connects these questions with organizational responsibilities and processes. Management discipline should be developed before formal recognition is pursued. Certification, where relevant and chosen, becomes a separate decision once the scope, readiness, and organizational needs are understood.
Understand the standard’s purpose and boundaries
ISO describes ISO/IEC 42001:2023 as a requirements standard for establishing, implementing, maintaining, and improving an AI management system [1]. The first edition was published in 2023. Its focus is how an organization manages AI, rather than automatic approval of every application or output. Our editorial recommendation is to begin with the purpose of adoption: consistent oversight, clear accountability, or a particular assessment need. Avoid treating a certificate as a substitute for system testing, impact assessment, and legal review. Detailed requirements work needs access to the official standard; this article provides a management orientation, not a complete clause checklist or certification audit guide.
Define a manageable scope
The organization needs to understand which AI uses fall within the intended scope, which units are involved, and how providers relate to the work. An overly broad scope can obscure ownership and implementation evidence. An overly narrow one may overlook important dependencies such as data, user decisions, or third-party services. Map how AI policy relates to existing risk management, information security, procurement, and operations. Use internal mechanisms that remain relevant before creating new forums. Leadership needs visibility of the resources and working-practice changes required, so implementation does not stop at documentation that people find difficult to use.
Look for evidence that policy is practiced
A policy design needs to become traceable activities. For example, a new use proposal has a need owner, risk assessment, approval, and decision rationale. A system change has a change record and control review. An error has handling, follow-up, and learning. These are editorial examples of practice evidence, rather than a complete list of standard requirements. Empty documents or unused templates do not show that management is operating. Interview users and process owners to understand whether responsibilities are known and obstacles can be raised. Identified gaps need an improvement owner and a review date.
Connect technical risks with management decisions
Model quality, data use, provider changes, and operational dependence require discussion across functions. NIST AI RMF offers a risk management perspective through govern, map, measure, and manage [2]. The two references serve different purposes and should be selected according to need; mentioning both does not establish that a system satisfies all requirements. Make risk information usable for leadership: explain impacts, evidence, owners, mitigation choices, and residual risk. Technical teams still need to examine systems in context. Where personal data is processed, the legal function reviews relevant obligations. A management system clarifies accountability routes but does not replace those assessment skills.
Separate readiness from the certification decision
Ask why the organization is considering certification, what scope it wants, and what resources will maintain practices after assessment. These needs differ from drafting an initial policy. If chosen, certification involves a certification body and its process; advisory work does not guarantee the result or legal compliance. A practical starting point is to inventory uses, check ownership, and gather examples of existing implementation evidence. AI Governance & Risk Management helps design roles, policies, controls, risk registers, and oversight mechanisms, with ISO/IEC 42001 as one relevant reference. Implementing and maintaining the management system remains an organizational responsibility.