EU AI Act vs GDPR: Key Differences Every Business Needs to Know

The Quick Comparison

Before going into detail, here is a side-by-side view of the two regulations. The full text of EU AI Act (Regulation 2024/1689) and GDPR (Regulation 2016/679) are both available on EUR-Lex.

Dimension	GDPR	EU AI Act
What it regulates	Personal data — how it is collected, processed, stored, and used	AI systems — how they are built, documented, governed, and deployed
Enforcement date	25 May 2018	Phased: prohibited AI (Feb 2025), GPAI (Aug 2025), high-risk AI (Aug 2026)
Maximum fine	€20M or 4% of global turnover	€35M or 7% of global turnover (prohibited AI)
Extraterritorial scope	Yes — applies to any company processing EU residents' data	Yes — applies to any company whose AI is placed on the EU market or used by EU residents
Primary compliance obligation	Legal basis for data processing, data subject rights, privacy notices, security measures	Risk classification, technical documentation, risk management, human oversight, conformity declaration
Who enforces	National Data Protection Authorities (DPAs) with one-stop-shop mechanism	National competent authorities; EU AI Office for GPAI
Documentation required	Records of Processing Activities (RoPA), DPIAs, privacy notices	Article 11 technical documentation (7 documents), risk management records, audit logs
Individual rights	Access, rectification, erasure, portability, objection, automated decision-making	Right to explanation of high-risk AI decisions; human review of automated decisions

What's Different: The Core Distinction

GDPR regulates what happens to personal data — the legal basis for collection, how it is used, how long it is kept, who can access it. It is triggered by the processing of personal data and its focus is on protecting privacy rights.

The EU AI Act regulates the AI system itself — not the data it processes, but how the AI is designed, tested, documented, governed, and deployed. It is triggered by the deployment of certain categories of AI system and its focus is on preventing harm from AI errors, biases, and lack of transparency.

An AI system that doesn't process personal data can still be subject to the EU AI Act. A data processing system that doesn't involve AI is still subject to GDPR. The two regulations are not alternatives — they operate independently and both can apply simultaneously.

Where They Overlap

There are several areas where GDPR and the EU AI Act both have requirements that point in the same direction, and where good GDPR practice creates a foundation for AI Act compliance:

Automated Decision-Making (Article 22 GDPR / Article 14 AI Act)

GDPR Article 22 gives individuals the right not to be subject to solely automated decisions that have significant legal or similarly significant effects, and the right to obtain human review of such decisions. The EU AI Act Article 14 independently requires that high-risk AI systems be designed to enable effective human oversight — that humans can intervene, override, or halt the AI. The two requirements converge on the same practical outcome: consequential AI decisions should not be fully automated, and affected individuals should be able to request human review.

Data Quality and Bias (Article 10 AI Act / GDPR accuracy principle)

GDPR's accuracy principle requires that personal data processed is accurate and up-to-date. The EU AI Act Article 10 extends this to training data, requiring that data used to train high-risk AI is examined for biases, meets quality criteria, and is governed by documented processes. If you have good data governance practices from GDPR, Article 10 compliance will be easier — but AI Act requirements are more specific and more technically demanding.

Transparency

GDPR requires privacy notices and transparency about how personal data is used. The EU AI Act requires instructions for use and Explainable AI reports that make AI systems understandable to deployers. Both reflect the same principle — people should know when and how their data or their decisions are being processed — but the specific documentation requirements are different. A privacy notice does not substitute for an XAI report.

Data Protection Impact Assessments (DPIAs) and AI Risk Assessments

GDPR Article 35 requires DPIAs for high-risk personal data processing, including systematic automated decision-making. The EU AI Act Article 9 requires a risk management system for high-risk AI systems. These are not the same document and do not substitute for each other, but a well-structured DPIA will capture some of the same risk categories as an AI Act risk management assessment — creating useful overlap in preparation.

Where They Diverge: What GDPR Doesn't Cover

The most important thing to understand is what GDPR compliance does not give you for AI Act purposes:

• Technical documentation (Article 11) — There is no GDPR equivalent. The requirement to document system architecture, training methodology, performance benchmarks, and conformity is unique to the AI Act. See our Article 11 documentation guide.
• Conformity declaration (Article 47) — GDPR has no conformity declaration mechanism. This is a new obligation with no prior equivalent for software companies.
• EU AI database registration (Article 49) — No GDPR equivalent. High-risk AI systems must be publicly registered in the EU AI database before deployment.
• Accuracy, robustness, and cybersecurity (Article 15) — GDPR requires security measures for personal data, but the AI Act's robustness requirements for AI systems — including adversarial testing, performance monitoring, and model drift detection — go significantly further.
• Risk tier classification — GDPR has risk categories for data processing, but the four-tier AI risk classification (prohibited, high, limited, minimal) and the Annex III category framework are AI Act-specific. See our risk classification guide.

How to Manage Both

For businesses subject to both regulations, here is how to build an efficient joint compliance programme:

1. Map your AI systems first. Identify which AI systems process personal data (subject to both GDPR and AI Act) and which process only non-personal data (AI Act only). This determines your total compliance scope.
2. Leverage your DPIA infrastructure. Extend your DPIA process to capture AI-specific risk factors. Consider updating your DPIA template to include the AI Act risk classification and relevant Annex III categories.
3. Don't conflate your privacy notice and XAI report. They serve different purposes. Your privacy notice explains how personal data is used. Your XAI report explains how the AI system works and makes decisions. They will reference some of the same information but are distinct documents.
4. Integrate AI Act documentation into your data governance programme. The Article 10 data governance requirements fit naturally into an existing data governance framework. Expand your data governance documentation to include AI training data explicitly.
5. Brief your DPO. If you have a Data Protection Officer, they should understand the AI Act's requirements — particularly the overlap areas. In many organisations, the DPO is the natural owner of the AI Act compliance programme alongside technical and product teams.