ISO 42001
Evidence collection
Model cards & system cards as audit evidence

Model cards & system cards as audit evidence

Model cards and system cards can act as central, reusable evidence objects that tie ISO 42001 requirements to specific AI models and end‑to‑end systems. When designed well, they provide auditors with a single, structured view of the purpose, data, risks, testing, and limits for each AI asset. Model cards are structured documents that describe the purpose, data sources, training/testing, performance, and limitations of one AI model, functioning like a technical data sheet with a risk note.​ System cards extend this idea to the full AI system, covering model composition, integrations, security, human oversight, and context-of-use so developers and auditors can see how the model operates in production.
For audits, model and system cards can evidence that controls are defined, implemented, and monitored at the asset level. Typical content that maps cleanly to ISO 42001:​
  • Governance & accountability: Owners, approvers, decision rights, and links to risk registers and policies.​
  • Data lineage & provenance: Data sources, collection methods, quality checks, and limitations, aligned with documentation requirements for AI system inputs.​
  • Testing, performance & fairness: Evaluation datasets, metrics, environment, and known failure modes, which auditors use to verify robustness and bias management practices.​
  • Operational boundaries: Intended use, prohibited use, user groups, and integration points, showing that deployment context and constraints have been considered.
During internal and external audits, use model and system cards as entry points: auditors start with the card, then sample down into underlying logs, tickets, and assessments referenced in it. Maintain a catalogue of cards for all in-scope models/systems and link it to your AI inventory and AI risk register so you can prove complete and current coverage across the AIMS scope.

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