The EU AI Act has moved the compliance bar from promises to evidence. Here’s how to meet it.
If your organisation uses AI anywhere in the EU — or serves EU customers — the EU AI Act applies to you. The good news: you don’t need to rebuild your AI estate. You need to understand it, classify it, and prove you’re controlling it. That’s exactly what governance is for.
Step 1: Build your AI inventory
You can’t comply with a law about AI systems you can’t list. Every model, agent, application and tool that uses AI — including shadow AI — goes into a single inventory with its owner, use case and environment.
Step 2: Classify risk
The Act tiers AI by risk: unacceptable, high, limited and minimal. Most enterprise use falls into limited or minimal, but high-risk systems (hiring, credit, education, critical infrastructure) carry the heaviest obligations. Classify honestly — misclassification is itself a compliance failure.
Step 3: Map obligations to controls
Each risk tier maps to specific obligations: risk management systems, data governance, human oversight, transparency, logging and documentation. For each obligation, identify the control that satisfies it — and who owns it.
Step 4: Build the evidence trail
Regulators and auditors now expect traceable proof: decisions, approvals, exceptions, risk assessments, monitoring logs. If you can’t show it, it didn’t happen. This is where most organisations struggle — policies exist, but evidence doesn’t.
Step 5: Operate continuously
Compliance isn’t a one-time project. Models change, vendors change, usage changes. A continuous loop — define, assess, control, observe, improve — keeps your compliance current instead of stale.