5 Steps to Prepare for EU AI Act Compliance

Most SME teams do not fail on intent — they fail on sequencing. The EU AI Act can feel overwhelming when treated as a legal checklist disconnected from day-to-day operations. A better approach is phased implementation: visibility first, then classification, then controls, then evidence, then continuous monitoring.

Below is a practical five-step method designed for real teams with limited bandwidth.

Step 1: Build an AI inventory you can trust

Create one register for all AI-enabled workflows across the company. For each system capture:
- name and owner,
- purpose and business process,
- affected user groups,
- input data categories,
- output usage (advisory vs decision-influencing),
- vendor/provider details,
- current controls and open gaps.

Do not stop at "tools list." Record use context. Same tool, different team, different risk.

Output of Step 1: a living inventory with accountable owners.

Step 2: Classify risk by use context

Use Annex III and Article 5 screening logic to classify each entry:
- prohibited-risk candidate,
- high-risk candidate,
- limited-risk transparency candidate,
- minimal/low operational risk.

Document rationale in plain language with legal references. If uncertainty is high, flag for legal/compliance review. Classification should be evidence-backed and revisitable.

Output of Step 2: risk map with documented rationale.

Step 3: Implement minimum viable controls

For each high-impact use case, implement core controls:
- human oversight checkpoints and override pathways,
- logging and traceability for key decision events,
- incident escalation ownership and thresholds,
- transparency notices where required,
- data quality/bias checks proportionate to use case.

Avoid waiting for "perfect framework". Start with controls that reduce harm probability and improve explainability.

Output of Step 3: control set per use case with owners and deadlines.

Step 4: Build your evidence package

Compliance without evidence is fragile. Create a practical documentation bundle:
- inventory snapshot,
- role mapping (provider/deployer/etc.),
- risk classification notes,
- oversight procedures,
- incident process,
- template-based technical/risk documentation where applicable,
- review logs and approval records.

This package should answer a procurement auditor's first questions within minutes.

Output of Step 4: audit-ready evidence bundle.

Step 5: Run compliance as an operating system

Set recurring governance cadence:
- monthly risk register updates,
- quarterly control reviews,
- event-driven reassessment after major model/process changes,
- annual policy and training refresh.

Track KPIs such as override rates, incident volume, unresolved control gaps, and documentation freshness.

Output of Step 5: continuous compliance loop, not one-off project.

Practical 10-item implementation checklist

1. Inventory exists and has owners.
   
2. Each entry has role and use-context notes.
   
3. Article 5 screening completed for sensitive systems.
   
4. Annex III high-risk candidates identified.
   
5. Oversight/override steps documented.
   
6. Logs exist for decision-relevant events.
   
7. Incident escalation workflow tested.
   
8. Transparency messaging deployed where needed.
   
9. Evidence pack centrally stored and versioned.
   
10. Governance cadence is scheduled and active.

Common failure modes

• Treating this as legal-only work.
• Ignoring operational ownership.
• Documenting after incidents, not before.
• No trigger-based reassessment when systems change.
• No linkage between risk score and mitigation priority.

Final takeaway

Compliance readiness by 2026 is achievable for SMEs if work is staged and operationalized. Start with what you can control this week: inventory, ownership, and risk classification. Build from there. The companies that treat compliance as product quality will move faster and safer than those that treat it as late-stage paperwork.