ISO/IEC 42001:2023

Information technology — Artificial intelligence — Management system

apartmentPublishing Organization:International Organization for Standardization (ISO)

Global Technology Services Finance & Banking Healthcare Manufacturing Automotive Retail

Standard Introduction

ISO/IEC 42001:2023 is an active standard published by International Organization for Standardization (ISO). It is commonly used across Technology, Services, Finance & Banking, Healthcare, Manufacturing, Automotive, Retail and applies in Global.

Use this page to review the official documentation, current status, and the certification or assessment bodies most commonly associated with ISO/IEC 42001:2023.

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AI-Specific Management System

The world's first international standard providing a certifiable framework for responsible AI development, deployment, and use — covering the entire AI system lifecycle.

assessment

AI Risk and Impact Assessment

Requires systematic identification of AI-specific risks and assessment of impacts on individuals, groups, and society — including ethical, fairness, transparency, and safety considerations.

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Data Governance

Mandates robust data management practices covering data quality, bias detection, provenance tracking, and lifecycle management for AI training and operational data.

list_alt AIMS Framework

AI policy and organizational commitment
AI risk assessment and treatment process
AI impact assessment for affected stakeholders
Data management and data quality controls
AI system lifecycle management (design through retirement)
Transparency and explainability requirements
Third-party and supply chain AI governance
Monitoring, measurement, and continual improvement

Who Needs to Comply?

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Organizations that develop, provide, or use AI systems — including technology companies, financial institutions, healthcare organizations, government agencies, and any entity deploying AI in decision-making processes.

Key Requirements

AI Risk Assessment

Implement a systematic process to identify, analyze, and evaluate risks specific to AI systems — including risks of bias, unfairness, lack of transparency, safety failures, and privacy violations throughout the AI lifecycle.

AI Impact Assessment

Assess the potential consequences of AI systems on individuals, groups, and society. Consider ethical, social, environmental, and human rights impacts. Document assessment results and implement mitigation measures.

Data Management

Establish controls for data acquisition, quality, labeling, bias assessment, and lifecycle management. Ensure training data is representative, appropriately documented, and compliant with applicable privacy and intellectual property requirements.

AI System Lifecycle Controls

Implement controls across the AI system lifecycle — from requirements definition and design through development, testing, deployment, monitoring, and retirement. Maintain documentation and traceability throughout.

Transparency and Accountability

Ensure AI systems and their outputs are explainable to relevant stakeholders. Maintain clear accountability structures for AI-related decisions. Provide mechanisms for affected parties to seek recourse.

Penalties & Enforcement

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No direct legal penalties — ISO/IEC 42001 is voluntary. However, it provides a structured path to demonstrate compliance with the EU AI Act and other emerging AI regulations. Certification increasingly expected by enterprise customers and regulators.