ISO/IEC 22989:2022 (AI Concepts and Terminology)

Why it matters for NETEVO

ISO/IEC 22989:2022 is the terminology bedrock underpinning the entire ISO/IEC AI management-system family. It defines 117 numbered terms across seven groups — AI generally, data, machine learning, neural networks, trustworthiness, natural-language processing, and computer vision — and supplies the canonical AI lifecycle phases in Annex A, mapped to the OECD definition. Without 22989 the conformity argument for ISO/IEC 42001 hangs on an undefined term.

Audit defensibility. ISO/IEC 42001 Clause 2 normatively imports the definition of "AI system" from 22989. Whitepapers and engagement deliverables that use the phrase pick up the 22989 definition by reference, and NETEVO cites the standard at the clause level as the authority for the definition shape. That anchoring is what allows an AI-system claim to survive an audit-grade challenge rather than relying on the loose vernacular sense of the term.

Single-sourced vocabulary across the catalogue. Subsequent NETEVO digests of ISO/IEC 42001, ISO/IEC 42005 and ISO/IEC 23894 cross-reference 22989 definitions rather than inlining them. The result is a single vocabulary spine across the AI governance stack — a structural prerequisite for the integration thesis NETEVO's Law-to-Code Methodology operationalises.

OECD lifecycle mapping. Annex A provides the canonical AI lifecycle phases that NETEVO's Authority Register and Statement of Applicability workflows anchor against. The seven phases align cleanly with the impact-assessment workflow in ISO/IEC 42005 and the risk-management process in ISO/IEC 23894, producing a single lifecycle frame across impact assessment, risk treatment, and management-system conformity.