AI & Security

ISO/IEC 42001 readiness for AI governance claims

A readiness lens for organizations making AI governance claims.

Published 2026-04-11 • 3 min read

Why this matters

Credible accreditation depends on consistent methods, clear decisions, and evidence that stands up to independent review. This publication translates essential expectations into practical steps so teams can prepare, communicate, and operate with confidence.

Key requirements and expectations

  • Identify sensitive data and apply least-privilege access.
  • Control third-party tools and integrations.
  • Maintain incident response and recovery procedures.
  • Prove security controls with evidence and testing.
  • Define AI system boundaries and responsibilities.
  • Document impact assessments and risk treatments.
  • Maintain transparency about AI use and limitations.

Evidence and records to prepare

  • Security policies, access logs, and monitoring outputs.
  • Risk assessments and vendor due diligence records.
  • Incident response plans and tabletop exercises.
  • Data retention and disposal procedures.
  • AI system inventory and impact assessment records.

Common pitfalls to avoid

  • Unmanaged access to evidence or applicant data.
  • Vendor tools without contractual security controls.
  • Incident response that is untested or outdated.
  • Over-collection of data without a clear purpose.
  • Making AI governance claims without evidence of controls.

Practical checklist

  • Map data flows and classify sensitive records.
  • Review vendor security controls and SLAs.
  • Run incident response drills and update playbooks.
  • Audit access permissions on a fixed cadence.
  • Maintain a documented AI risk assessment workflow.

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