Overview
SIST EN ISO/IEC 22989:2026, titled Information technology - Artificial intelligence - Artificial intelligence concepts and terminology (ISO/IEC 22989:2022, Corrected version 2025-12), is a European and international standard developed by CEN and ISO/IEC JTC 1 SC 42. This standard establishes a harmonized set of concepts and terminology for the field of artificial intelligence (AI). It serves as a foundational reference for the development of other AI-related standards and supports clear communication between a broad range of stakeholders including commercial enterprises, government agencies, not-for-profit organizations, and the academic community.
Global interest and advancements in AI-including machine learning, data science, and cognitive computing-highlight the critical need for consistent terminology. This document covers key terms, high-level AI concepts, system lifecycle considerations, and the main fields and application domains for AI solutions.
Key Topics
SIST EN ISO/IEC 22989:2026 includes:
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Terminology for Artificial Intelligence:
- Standard definitions for AI, AI system, agent, autonomy, automation, and related concepts.
- Clear distinction between narrow AI (specialized tasks) and general AI (broad, human-like capabilities).
- Concepts from data science, machine learning (e.g., supervised, unsupervised, reinforcement learning), and cognitive computing.
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AI System Lifecycle:
- Standardized life cycle stages including inception, development, validation, deployment, operation, continuous validation, and retirement.
- Concepts of continuous learning and system re-evaluation to address AI’s evolving nature.
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Trustworthiness and Stakeholder Roles:
- Definitions and attributes such as robustness, reliability, explainability, transparency, fairness, and bias mitigation.
- Identification of major roles within the AI ecosystem (e.g., AI provider, producer, customer, partner, subject, authorities).
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Main AI Fields:
- Computer vision, natural language processing, data mining, planning and decision-making.
- Techniques such as neural networks, decision trees, expert systems, and support vector machines.
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Integration with Related Technologies:
- Links to big data, cloud and edge computing, Internet of Things (IoT), and cyber-physical systems.
Applications
Standardized AI terminology under SIST EN ISO/IEC 22989:2026 delivers practical value to various industries and sectors:
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Supporting Standards Development:
- Acts as a reference for other technical committees designing AI standards, ensuring consistency across documents and sectors.
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Facilitating Communication:
- Promotes effective dialogue among developers, regulators, procurement professionals, and technology users by reducing ambiguity.
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Enabling AI System Assessment and Comparison:
- Provides a common baseline for comparing features such as trustworthiness, explainability, robustness, and performance among AI solutions.
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Guiding AI Integration and Compliance:
- Assists organizations incorporating AI into business processes or products, supporting compliance with regulatory and ethical requirements.
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Enhancing Training and Education:
- Offers a reliable foundation for AI curriculum development and professional training programs.
Related Standards
Organizations engaged in AI development or implementation may also benefit from referencing related standards, including:
- ISO/IEC 2382 - Information technology vocabulary
- ISO/IEC 38507 - Governance implications of using AI by organizations
- ISO/IEC TR 24028 - Overview of trustworthiness in AI
- ISO/IEC 24029 - Assessment frameworks for AI system robustness
- ISO/IEC 20546 - Big data overview and vocabulary
Conclusion
Adopting SIST EN ISO/IEC 22989:2026 is crucial for any organization or stakeholder involved in artificial intelligence. It ensures clarity in documentation, procurement, compliance, and policy, paving the way for responsible AI adoption and advancing international harmonization in this rapidly evolving field.
