ISO 42001 for Self-Hosted AI: What Auditors Actually Ask For (and What Your Infrastructure Has to Prove)

ISO/IEC 42001:2023 certifies an organization’s AI management system rather than any individual model, requiring documented governance, roles, risk and impact assessments, lifecycle controls, internal audits, management reviews, and continual improvement within a clearly defined scope. For self-hosted AI, auditors focus heavily on infrastructure evidence demonstrating where models and data run, who has access, how each deployment is approved and linked to source commits, what is logged and retained, and whether production configurations match approved records. Organizations must address all 38 Annex A controls in a Statement of Applicability, with particular attention to AI-specific risk assessments and impact assessments covering effects on individuals, groups, and society. Certification is conducted by an accredited body through Stage 1 and Stage 2 audits, followed by annual surveillance over a three-year certificate period, making continuously generated records more reliable than manually collected screenshots. Existing ISO 27001 processes can reduce preparation effort, while managed AI providers can be treated as suppliers, though self-hosting gives organizations more direct control over data residency, logs, and operational evidence. The article presents Qovery as a platform that can support the infrastructure side of this evidence by deploying AI workloads in an organization’s own cloud account with access controls and commit-linked deployment records, while emphasizing that it does not provide certification or replace required governance documentation.

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