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What is an AI audit?

4 min read

Two things get called 'AI audits.' Don't confuse them. An internal AI audit is a self-assessment your team runs to find gaps. An external AI audit is performed by a third party against a defined standard, usually for certification, regulatory filing or enterprise procurement.

What an AI audit examines

Scope varies by framework, but the recurring areas are consistent.

  • Governance — policies, named owners, escalation paths
  • Inventory — every AI system, vendor and dependency
  • Data — sources, consent, retention, residency
  • Model — testing, evaluation, bias, robustness
  • Vendor — third-party risk and contractual terms
  • Oversight — where humans review or override
  • Monitoring — production behaviour and incident response
  • Evidence — exportable records mapped to framework requirements

Who performs the audit

Three options, in order of cost and authority:

  • Internal team — quick, cheap, useful for finding gaps before anyone else does
  • Specialist consultancy — expensive but pragmatic; good before a real external audit
  • Accredited certification body — required for ISO 42001 certification or formal EU AI Act conformity assessment

Timeline and cost for best results

An internal audit on a small AI stack: 1–2 weeks of work for one person. A consultancy-led readiness audit: 4–8 weeks, $20k–$60k. A full external ISO 42001 audit: 6–12 weeks of audit activity, $25k–$50k in audit fees plus internal effort.

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