What is AI compliance?
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.