The EU AI Act and GDPR both apply to AI systems that process personal data — which is most of them. They are complementary frameworks, not alternatives. GDPR governs how personal data is used; the AI Act governs how AI systems are built, deployed, and monitored. For most SaaS companies, both apply simultaneously.
Understanding where they overlap — and where they diverge — is essential for building a compliance programme that doesn't do the same work twice.
The Core Difference
| GDPR | EU AI Act | |
|---|---|---|
| What it regulates | Processing of personal data | AI systems and their deployment |
| Primary concern | Data subject rights and privacy | Safety, accuracy, bias, transparency, and fundamental rights |
| Trigger | Processing personal data of EU residents | Placing AI on the EU market or deploying it in EU |
| Who is regulated | Controllers and processors | Providers, deployers, importers, distributors |
| Enforcement | Data Protection Authorities (DPAs) | National market surveillance authorities + European AI Office |
| Max fine | €20m or 4% global turnover | €35m or 7% global turnover (prohibited AI) |
Both regulations apply independently. Complying with one does not satisfy the other.
Where They Overlap
1. Automated Decision-Making
GDPR Article 22 gives data subjects the right not to be subject to decisions based solely on automated processing — including profiling — that produce legal or similarly significant effects. Data subjects have the right to:
- Obtain human review of the automated decision
- Express their point of view
- Contest the decision
AI Act Annex III classifies AI systems making decisions in employment, credit, insurance, and other high-stakes areas as high-risk, and requires human oversight mechanisms.
The overlap: Both require that AI systems in consequential domains allow for human review. In practice, you satisfy both requirements with a single human oversight mechanism — but you need to document it under both frameworks separately.
The difference: GDPR Article 22 applies wherever an automated decision has legal/significant effects on an individual, regardless of AI Act risk tier. The AI Act applies only to AI systems in the specific Annex III use cases.
2. Transparency and Disclosure
GDPR Articles 13 and 14 require you to inform data subjects, at the point of data collection, that their data is being processed, for what purpose, and whether it will be used in automated profiling or decision-making.
AI Act Article 50 requires disclosure when users interact with AI chatbots, encounter AI-generated content, or have their emotions assessed by AI.
The overlap: Both require informing users about AI. A single notification can be designed to satisfy both, but it must address each framework's specific elements.
The difference: GDPR requires disclosure at data collection; AI Act requires disclosure at the point of AI interaction. For a chatbot collecting personal data while it chats, both apply at the same time. For an AI system that analyses existing data without new collection, GDPR Article 14 (indirect collection) may still apply even if no new interaction occurs.
3. Training Data and Special Categories
GDPR restricts processing of special category data (health, biometric, ethnic origin, political opinions, sexual orientation, religious beliefs, trade union membership) — requiring explicit consent or another Article 9 basis.
AI Act Article 10 requires training data to be free from errors and biases that could lead to discrimination — explicitly referencing the GDPR special category characteristics as areas requiring particular attention.
The overlap: If you train AI on special category data, GDPR and AI Act requirements reinforce each other. Both demand governance and documentation of why and how special category data is used.
The difference: GDPR focuses on lawful basis and data subject rights. The AI Act focuses on bias evaluation and technical data quality — GDPR compliance with special category data does not automatically satisfy AI Act Article 10 data governance requirements.
4. Data Protection Impact Assessments and Fundamental Rights Impact Assessments
GDPR Article 35 requires a Data Protection Impact Assessment (DPIA) for high-risk processing — including systematic profiling, large-scale special category processing, and systematic monitoring.
AI Act Article 27 requires deployers of high-risk AI (in the public sector, or private sector covering high-risk categories) to conduct a Fundamental Rights Impact Assessment (FRIA) before deployment.
The overlap: Both assessments evaluate the impact of an AI system on individuals before deployment. They cover overlapping ground, and a well-designed DPIA can be structured to satisfy FRIA requirements simultaneously.
The difference: A DPIA focuses on data protection risks and mitigations. A FRIA is broader — it covers impact on all fundamental rights (equality, non-discrimination, dignity, access to justice) not just privacy. You need both for many high-risk AI deployments.
Where They Diverge
AI Act obligations that have no GDPR equivalent
- Risk management system — ongoing documented process throughout the AI system lifecycle
- Technical documentation (Article 11) — detailed file on model architecture, training, and performance
- Conformity assessment — self-assessment or third-party certification before market placement
- EU AI database registration — public registry of high-risk AI systems
- CE marking — required on high-risk AI documentation
- Post-market monitoring — ongoing collection of system performance data after deployment
- Incident reporting — serious incidents and AI malfunctions must be reported to authorities
None of these exist in GDPR. They are purely AI Act obligations.
GDPR obligations that have no AI Act equivalent
- Data subject access rights — right to access, rectification, erasure, portability
- Lawful basis — you must identify and document a legal basis for every processing activity
- Data minimisation — process only the data you need
- Retention limits — do not keep data longer than necessary
- Data Processing Agreements — required with every processor
- International transfer mechanisms — SCCs, adequacy decisions, BCRs
These are GDPR-only. The AI Act does not replace or reduce any of them.
Practical Compliance Approach
Running two separate compliance programmes for GDPR and the AI Act is inefficient. The most effective approach is an integrated compliance file that addresses both frameworks for each AI system.
For each AI system, build a single file that contains:
- GDPR: Lawful basis, data subject rights, DPIA (if required), DPA with processors
- AI Act: Risk classification, Article 11 technical documentation, conformity assessment, registration
- Shared elements: Transparency disclosures (covering both GDPR Articles 13/14 and AI Act Article 50), human oversight mechanism, training data governance (satisfying both GDPR lawful basis and AI Act Article 10)
This approach produces a defensible compliance record for both frameworks without duplicating work.