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What is AI compliance?

4 min read

AI compliance is the umbrella term for everything an organisation does to prove its AI use is legal, safe and well-governed. It's a superset of data privacy, security and traditional governance — extended to cover the specific risks that AI introduces.

What AI compliance covers in practice

A real AI compliance program touches every stage of the AI lifecycle, not just the model. The substantive areas:

  • Inventory — every AI system you build, buy or embed
  • Risk classification — what could go wrong, how bad, how likely
  • Data governance — what data trains and runs the models, with what consent
  • Vendor due diligence — every third-party AI provider in your stack
  • Human oversight — where humans must review, approve or override
  • Monitoring and incident response — detection and reaction in production
  • Evidence and audit trail — proof, exportable on demand

Frameworks that drive AI compliance

Most programs converge on the same four reference points. Each answers a different question.

  • EU AI Act — the law for AI in the European market
  • NIST AI RMF — the US framework for managing AI risk
  • ISO/IEC 42001 — the certifiable international management-system standard
  • SOC 2 — the assurance standard most enterprise buyers ask for

Who needs AI compliance for best results

If your organisation builds AI, embeds AI in a product, or sells into enterprises or regulated markets — you need a compliance program. The threshold is much lower than most teams assume; even agencies using ChatGPT in client deliverables are increasingly being asked for written AI policies and vendor risk assessments.

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