EU AI Act vs GDPR: Key Differences, Overlaps & Compliance

The cleanest way to keep them apart is to ask what each law regulates:

• The GDPR regulates the processing of personal data — collection, storage, use and sharing of information about identifiable individuals. It is a data-protection and privacy law.
• The EU AI Act regulates AI systems according to a risk-based framework: prohibited practices (Article 5), high-risk systems (Annex III), limited-risk systems with transparency duties (Article 50), and minimal-risk systems.

An AI system that processes no personal data at all — say, a model predicting machine failure from sensor data — still falls under the AI Act but largely outside the GDPR. Conversely, a simple spreadsheet of customer records engages the GDPR but not the AI Act.

Note the fine ceilings differ: see our EU AI Act penalties guide for the full tier breakdown.

The two regimes intersect wherever an AI system processes personal data — which is common. The main touch-points:

• Automated decision-making. GDPR Article 22 gives individuals rights around solely automated decisions with legal or similarly significant effects. Many such decisions are made by AI systems the Act classifies as high-risk, so both regimes apply to the same use case.
• Transparency. The GDPR requires informing data subjects about processing; the AI Act (Article 50) requires informing people when they interact with AI, when content is AI-generated, or when systems like emotion recognition are used.
• Risk and impact assessments. The GDPR's Data Protection Impact Assessment (DPIA) and the AI Act's risk management — plus the fundamental-rights impact assessment required of certain high-risk deployers — cover related but distinct ground.
• Lawful basis and data governance. High-risk AI training data obligations under the Act sit alongside the GDPR's requirements for a lawful basis and data minimisation.

These are easy to conflate but serve different purposes:

• A DPIA (GDPR) assesses risks to the rights and freedoms of data subjects arising from a specific processing operation. It is triggered by high-risk processing of personal data.
• The AI Act's risk management system is an ongoing, lifecycle obligation for high-risk AI systems, focused on the safety and performance of the system itself.
• Certain deployers of high-risk systems must also carry out a fundamental-rights impact assessment (FRIA) before deployment.

Where both apply, the assessments can be aligned and evidence reused — but one does not satisfy the other. You cannot file a DPIA and consider your AI Act risk-management duty discharged.

Because most business AI touches personal data, the two regimes stack rather than substitute. A hiring tool that screens CVs, for example:

• Processes personal data → GDPR applies (lawful basis, transparency, Article 22 safeguards, likely a DPIA).
• Is an AI system used for recruitment → AI Act classifies it as high-risk (Annex III), triggering risk management, documentation, human oversight and more.

Missing either exposes the organisation to separate penalty regimes. The two sets of fines are independent — a single system could, in principle, attract enforcement under both laws for different failings.

Treating the two regimes as one joined-up programme is far more efficient than running them in silos:

• Map once, use twice. An inventory of AI systems and the personal data they process feeds both your GDPR records and your AI Act risk classification.
• Align assessments. Design your DPIA and AI Act risk/FRIA processes to share inputs and evidence.
• Coordinate governance. Your DPO and AI governance owner should work from the same system inventory and risk register.
• Mind the deadlines. The AI Act phases in separately from the GDPR — prohibited practices and AI literacy applied from 2 February 2025, with high-risk obligations following on 2 December 2027.

Start by classifying your systems with our complete guide, then run the free risk checker to see which regimes each system engages.