Harmonised Standards Mapper

AI Management System

Requirements for an AI management system — governance, risk management, and responsible AI practices.

AI System Impact Assessment

Guidance on conducting AI system impact assessments, including risk identification and mitigation.

Requirements for AI Auditing Bodies

Competence requirements for bodies auditing AI management systems and AI systems.

Quality Model for AI Systems

Quality characteristics for AI systems: functional correctness, robustness, transparency, fairness, and explainability.

Overview of Trustworthiness in AI

Overview of approaches to achieve trustworthiness in AI systems and failure modes.

AI Risk Management

Guidance on how organisations that develop, produce, deploy, or use AI can manage risk.

Overview of Ethical and Societal Concerns

Identifies ethical and societal issues associated with AI and guidance on addressing them.

AI System Life Cycle Processes

Framework for AI system life cycle processes — requirements, design, data management, testing, deployment, and monitoring.

Functional Safety and AI Systems

Guidance on the application of AI in functional safety applications — safety integrity, safe failure, and validation.

Framework for AI Use Cases

Framework for describing AI use cases and their characteristics for standardisation purposes.

Cybersecurity for Consumer IoT

Security baseline for internet-connected consumer devices.

Industrial Cybersecurity

Security standards for industrial automation and control systems.

Information Security Management System (ISMS)

Requirements for establishing, implementing, maintaining, and continually improving an information security management system.

Privacy Information Management (PIMS)

Extension to ISO 27001/27002 for privacy management — mapping to GDPR requirements for personal data processing.

Risk Management — Guidelines

Principles and guidelines for risk management applicable to any organisation or activity.

Model Process for Addressing Ethical Concerns in System Design

IEEE standard for a model process to address ethical concerns during the conceptualisation and development of systems.

Transparency of Autonomous Systems

Measurable and testable levels of transparency in autonomous systems so they can be understood by various stakeholders.

NIST AI Risk Management Framework

Voluntary framework from the US NIST providing a structured approach to AI risk: Map, Measure, Manage, Govern.

Assessment of the Robustness of Neural Networks

Methods to assess the robustness of neural networks including formal methods and statistical approaches to testing.

Artificial Intelligence (EU Standardisation Mandate)

EU mandate M/570 tasked CEN-CENELEC JTC 21 with developing harmonised European Standards for the EU AI Act — covering risk management, data governance, transparency, and conformity assessment.