EU AI Act vs GDPR: What Your Privacy Team Already Covers (and What's New)

If your company is already GDPR-compliant, you are better positioned for the EU AI Act than most. You have a privacy team, data processing records, DPIAs, and consent mechanisms. That infrastructure matters.

But it is not enough. The EU AI Act regulates something different from GDPR, and assuming your privacy compliance covers AI compliance is the most common mistake we see.

Different regulations, different targets

GDPR regulates personal data processing. It cares about what data you collect, how you store it, who you share it with, and whether people can access or delete it.

The EU AI Act regulates AI systems themselves. It cares about how the system was designed, what decisions it makes, whether it is documented, how it is tested, and whether users know they are interacting with AI.

Both can apply to the same product simultaneously. An AI-powered HR screening tool processes personal data (GDPR) and is a high-risk AI system (AI Act). You need to comply with both, and compliance with one does not satisfy the other.

What already overlaps

The good news: several GDPR requirements give you a running start on AI Act compliance.

Data governance

GDPR's data minimisation, purpose limitation, and storage limitation principles align closely with Article 10 of the AI Act (data governance for high-risk systems). If you already document your data sources, retention policies, and processing purposes, you have the foundation for AI Act data governance documentation.

Data Protection Impact Assessments (DPIAs)

If you have conducted DPIAs for your AI systems under GDPR Article 35, some of that analysis feeds into the AI Act's risk assessment requirements. The AI Act requires a broader risk management system (Article 9), but your DPIAs cover the data-related risks.

Transparency

GDPR Articles 13 and 14 already require you to inform people about automated decision-making. The AI Act's Article 50 transparency obligations extend this — but if you already disclose automated processing in your privacy notices, you have the communication infrastructure in place.

Rights and human oversight

GDPR Article 22 gives individuals the right not to be subject to purely automated decisions with legal or significant effects. The AI Act's human oversight requirements (Article 14) are more specific about how that oversight must work in practice, but the principle is the same: humans must be able to intervene.

What's genuinely new

These are the obligations that have no GDPR equivalent. This is where most companies have gaps.

Risk classification

GDPR does not classify systems by risk tier. The AI Act does — every AI system falls into prohibited, high, limited, or minimal risk, and the classification determines your entire obligation set. There is no GDPR shortcut here; you need to classify each system independently.

Technical documentation (Annex IV)

This is the biggest gap. High-risk AI systems must have comprehensive technical documentation covering system architecture, training data, validation methodology, performance metrics, and risk analysis across 9 mandated sections. GDPR records of processing activities cover data flows; Annex IV covers the system itself. These are fundamentally different documents.

Conformity assessment

High-risk AI providers must conduct a formal conformity assessment before placing the system on the market. This is a structured self-assessment (or third-party assessment for certain biometric systems) verifying compliance with all applicable requirements. GDPR has no equivalent process.

Quality management system

Article 17 requires high-risk AI providers to implement a quality management system covering development, testing, validation, and post-market monitoring. This goes well beyond GDPR's data quality principles — it is a full process framework for the AI lifecycle.

Content labeling

If your AI generates synthetic content (text, images, audio, video), Article 50 requires machine-readable labeling. GDPR has no content labeling requirement. This is entirely new technical work.

Where they can conflict

In some cases, the two regulations create tension.

Data retention.GDPR requires data minimisation and storage limitation — keep only what you need, delete it when you're done. The AI Act requires maintaining training data documentation and logs for the lifetime of the system, plus 10 years after it is withdrawn from the market. Your legal team will need to reconcile these timelines.

Bias testing. Article 10(5) of the AI Act allows processing of special category data (race, ethnicity, health) for bias detection and correction in high-risk systems. Under GDPR, processing special category data requires a specific legal basis. The AI Act provides one — but you need to document the justification carefully and ensure the data is handled with appropriate safeguards.

Explainability.GDPR's right to explanation (Article 22) and the AI Act's transparency requirements both push toward explainable AI, but they frame it differently. GDPR focuses on individual rights to understand a specific decision. The AI Act focuses on systemic transparency — how the system works in general, not just for one person. You may need both individual and systemic explanations.

The practical approach

If you already have GDPR infrastructure, here is how to build on it for AI Act compliance:

• Audit your AI systems. Your GDPR data processing register lists what data you process. Now list what AI systems you operate. These are different inventories with different purposes.
• Classify each system. Use the free classifier at getactready.com/classify to determine risk tiers. Your DPIAs may have flagged some of these systems already, but the AI Act classification criteria are different from GDPR risk assessments.
• Map the gaps. For each system, compare what your GDPR documentation covers against what the AI Act requires. The gaps are almost always: technical documentation, conformity assessment, quality management, and content labeling.
• Assign ownership. GDPR compliance typically sits with your DPO or legal team. AI Act compliance often requires engineering involvement for technical documentation and content labeling. Decide who owns what now, not when the deadline hits.

The transparency deadline is 74 days away. The high-risk deadline is 561 days. Your GDPR foundation gives you a real advantage — but only if you start building on it now.