ISO/IEC 42001 in the AI Governance Framework Explorer

Establishes the organizational context for the AI management system.

Determine external and internal issues relevant to the AIMS purpose and outcomes.

Identify interested parties and their requirements relevant to the AIMS.

Define boundaries and applicability of the AI management system.

Establish, implement, maintain and continually improve the AIMS.

Leadership commitment and governance of the AI management system.

Top management shall demonstrate leadership and commitment to the AIMS.

Establish an AI policy appropriate to the purpose of the organization.

Assign and communicate roles, responsibilities and authorities for the AIMS.

Planning actions to address risks, opportunities, and objectives.

Plan actions to address risks and opportunities affecting the AIMS.

Consider issues from 4.1, requirements from 4.2, and determine risks and opportunities.

Establish and maintain an AI risk assessment process for identifying, analyzing, and evaluating AI risks.

Define and apply an AI risk treatment process to select and implement controls.

Assess impacts of AI systems on individuals, groups, societies and the environment.

Establish AI objectives at relevant functions, levels, and processes.

When changes to the AIMS are needed, carry them out in a planned manner.

Resources, competence, awareness, communication, and documented information.

Determine and provide resources needed for the AIMS.

Determine necessary competence for persons doing work affecting AI performance.

Ensure persons doing work are aware of the AI policy, their contribution, and implications of non-conformity.

Determine internal and external communications relevant to the AIMS.

Include documented information required by this document and determined necessary for AIMS effectiveness.

Operational planning, control, and execution of AI risk processes.

Plan, implement and control processes needed to meet requirements and implement planned actions.

Perform AI risk assessments at planned intervals or when significant changes occur.

Implement the AI risk treatment plan and retain documented information on results.

Perform AI system impact assessments at planned intervals or when significant changes occur.

Monitoring, measurement, analysis, evaluation, audit, and management review.

Determine what needs to be monitored and measured, methods, and when to analyze results.

Conduct internal audits at planned intervals to verify AIMS conformity and effectiveness.

Plan, establish, implement and maintain an audit programme.

Define audit criteria, scope, frequency, methods, and reporting.

Review the AIMS at planned intervals to ensure its continuing suitability, adequacy and effectiveness.

Top management shall review the AIMS at planned intervals.

Include status of actions, changes, feedback, audit results, and risk assessment results.

Decisions related to continual improvement opportunities and any need for changes.

Nonconformity, corrective action, and continual improvement.

Continually improve the suitability, adequacy and effectiveness of the AIMS.

React to nonconformities, evaluate the need for action, implement changes, and review effectiveness.

Defines terms used throughout the AI management system standard.

Person or group of people with its own functions, responsibilities, authorities, and relationships to achieve its objectives.

Person or organization that can affect, be affected by, or perceive itself to be affected by a decision or activity.

Person or group who directs and controls an organization at the highest level.

Set of interrelated or interacting organizational elements that establish policies, objectives, and processes.

Intentions and direction of an organization as formally expressed by top management.

Result to be achieved; AI objectives are set consistent with AI policy.

Effect of uncertainty, often expressed as a combination of event consequences and associated likelihood.

Set of interrelated or interacting activities that uses or transforms inputs to deliver a result.

Ability to apply knowledge and skills to achieve intended results.

Action taken to eliminate the cause(s) of a nonconformity and prevent its recurrence.

Systematic and independent process for obtaining evidence and evaluating it objectively.

Process to determine a value.

Determining the status of a system, process, or activity through checking, supervising, or critical observation.

Measure that maintains and/or modifies risk, including any process, policy, device, practice, or action.

Person or group accountable for the performance and conformance of the organization.

Formal documented process to identify, evaluate, and address impacts on individuals, groups, and societies from AI systems.

Characteristic that data meet the organization requirements for a specific context.

Documentation of all necessary controls and justification for their inclusion or exclusion.

Controls for establishing and maintaining AI policies.

An AI policy and topic-specific policies shall be defined, approved by management, published, communicated and acknowledged.

The organization shall determine where other organizational policies intersect with or are affected by AI objectives.

The AI policy shall be reviewed at planned intervals or if significant changes occur to ensure continuing suitability, adequacy and effectiveness.

Controls for internal organizational structure supporting AI governance.

AI roles and responsibilities shall be defined and allocated.

A mechanism for reporting AI concerns and potential non-compliance shall be established.

Controls for managing resources related to AI systems.

Relevant resources required for AI system lifecycle activities shall be identified and documented.

Information about data resources utilized for the AI system shall be documented.

Information about the tooling resources utilized for the AI system shall be documented.

Information about the system and computing resources utilized for the AI system shall be documented.

Information about human resources and their competencies used for AI system lifecycle activities shall be documented.

Controls for assessing the impacts of AI systems on individuals, groups, and societies.

A process shall be established to assess the potential consequences of AI systems for individuals, groups, and societies.

The results of the AI system impact assessment shall be documented.

The potential impacts of AI systems to individuals or groups of individuals throughout the system lifecycle shall be assessed and documented.

The potential societal impacts of AI systems throughout their lifecycle shall be assessed and documented.

Controls across the AI system lifecycle.

Controls covering the AI system lifecycle: impact assessment, development and acquisition, verification and validation, deployment, operations, monitoring, and retirement.

Objectives to guide responsible development of the AI system shall be identified, documented, and integrated into the development lifecycle.

Specific processes for responsible design and development of AI systems shall be defined and documented.

Requirements for new AI systems or material enhancements shall be specified and documented.

AI system design and development shall be documented based on organizational objectives.

Verification and validation measures and criteria for the AI system shall be defined and documented.

A deployment plan shall be documented and requirements verified before deployment of the AI system.

Necessary elements for ongoing operation shall be defined and documented, including system and performance monitoring, repairs, updates, and support.

Technical documentation needed for each category of interested parties shall be determined and provided.

The lifecycle phases at which event log recording should be enabled shall be determined and documented.

Controls for managing data used in AI systems.

Data management processes related to AI system development shall be defined, documented and implemented.

Processes for acquiring data for AI systems shall be established.

Data quality criteria for AI systems shall be defined, measured and maintained.

The provenance of data used in AI systems shall be documented and traceable.

Data preparation processes for AI shall be documented and controlled.

Controls for providing information about AI systems to interested parties.

Documentation and information about AI systems shall be provided to users and relevant interested parties.

Capabilities shall be provided for interested parties to report adverse impacts related to AI systems.

A plan for communicating AI system incidents to users shall be determined and documented.

Obligations for reporting information about the AI system to interested parties shall be determined and documented.

Controls for responsible use of AI systems.

Processes for responsible use of AI systems shall be defined and documented.

Objectives to guide responsible use of AI systems shall be identified and documented.

The AI system shall be used according to its intended uses and accompanying documentation.

Controls for managing relationships with third parties, suppliers, and customers regarding AI systems.

Responsibilities within the AI system lifecycle shall be allocated between the organization, partners, suppliers, customers and third parties.

A process shall be established to ensure supplier products and services align with the organization’s responsible AI approach.

The organization’s responsible AI approach shall consider customer expectations and needs.

Normative annex providing implementation guidance for all controls listed in Table A.1, organized in sections B.2 through B.12 corresponding to Annex A control families.

Informative annex outlining potential organizational objectives (accountability, AI expertise, data quality, environmental impact, fairness, privacy, reliability, safety, security, transparency) and risk sources for AI systems.

109 entries, each with a plain-English explanation, implementation guidance at three organization sizes, evidence checklists, and risk context. 88 entries carry source-grounded risk profiles.

The Framework Explorer documents 95 audited cross-framework mappings touching ISO/IEC 42001, connecting it to NIST AI RMF, EU AI Act, ISO/IEC 27001, OWASP LLM Top 10, OWASP Agentic AI Top 10, MITRE ATLAS. Every mapping was verified against the source documents.

No. Entry titles identify each requirement, and all explanations are original plain-English summaries written by Tech Jacks Solutions. For official text, consult the publishing body directly.