AI systems processing personal data in the EU must satisfy two major regulations
simultaneously: the General Data Protection Regulation (Regulation (EU) 2016/679) and the
EU Artificial Intelligence Act (Regulation (EU) 2024/1689). This assessment maps
obligations side-by-side across 14 overlap areas, identifies coverage
gaps, and gives a prioritized implementation roadmap aligned to COMPEL transformation
stages.
14
Overlap Areas
2
Full Overlaps
2
Potential Conflicts
5
Critical Priority
Overlap Taxonomy
Full Overlap
2 areas
Partial Overlap
6 areas
Complementary
4 areas
Potential Conflict
2 areas
Overlap Areas
Each entry maps a specific GDPR requirement against its EU AI Act counterpart, flags the
overlap type, and specifies COMPEL stages where the obligation is executed.
Data Protection Impact Assessment (DPIA) required where processing, in particular using new technologies, is likely to result in a high risk to the rights and freedoms of natural persons. Must assess necessity, proportionality, risks, and safeguards.
AI Act — Article 9, Article 43, Annex VI, Annex VII
Conformity assessment required for high-risk AI systems before market placement. Must demonstrate compliance with Articles 8-15 covering risk management, data governance, technical documentation, and human oversight.
Conflict Resolution Guidance
Conduct an integrated impact assessment that satisfies both DPIA requirements (focus: data subjects' rights) and AI Act conformity assessment (focus: system compliance). The DPIA can be embedded within the broader conformity assessment, with additional data protection-specific analysis.
Evidence requirements & notes
Evidence Requirements
Integrated impact assessment document covering both DPIA and conformity elements
Risk assessment covering data protection risks and AI system risks
Consultation records with DPO and AI compliance officer
Safeguard and mitigation measures documentation
Notes
Where the AI system processes personal data, the GDPR DPIA is mandatory alongside the AI Act conformity assessment. The European Data Protection Board (EDPB) recommends a combined approach.
DUAL-002 Partial Overlap critical priority
COMPEL: Produce
COMPEL: Learn
Transparency Obligations
GDPR — Article 13, Article 14, Recital 58-62
Controllers must provide data subjects with information about processing including purposes, legal basis, recipients, retention periods, and the existence of automated decision-making with meaningful information about the logic involved.
AI Act — Article 13, Article 52
High-risk AI systems must be designed for transparency. Deployers must provide instructions for use covering capabilities, limitations, accuracy, and human oversight measures. Users must be informed when interacting with AI.
Conflict Resolution Guidance
Create a unified transparency package: GDPR privacy notice enriched with AI Act-specific disclosures (system capabilities, limitations, accuracy metrics). Ensure the "meaningful information about the logic" (GDPR Art 13(2)(f)) is complemented by the AI Act's system capability and limitation disclosures.
Evidence requirements & notes
Evidence Requirements
Unified privacy notice with AI-specific disclosures
AI interaction notification mechanism documentation
System capability and limitation disclosure
Instructions for use provided to deployers
Notes
GDPR transparency focuses on data processing; AI Act transparency focuses on system behavior. Both must be addressed simultaneously for AI systems processing personal data.
DUAL-003 Full Overlap critical priority
COMPEL: Model
COMPEL: Produce
Automated Decision-Making and Human Oversight
GDPR — Article 22, Recital 71
Data subjects have the right not to be subject to decisions based solely on automated processing, including profiling, which produces legal or similarly significant effects. Exceptions require explicit consent, contractual necessity, or legal authorization, with safeguards including the right to human intervention.
AI Act — Article 14
High-risk AI systems must be designed for effective human oversight. Natural persons assigned human oversight must be able to fully understand the system, monitor its operation, override or reverse outputs, and intervene when necessary.
Evidence requirements & notes
Evidence Requirements
Human oversight design specification
Override and intervention mechanism documentation
GDPR Art 22 safeguards implementation evidence
Human reviewer competency verification records
Decision contestation process documentation
Notes
Both regulations require human involvement in automated decisions. The AI Act's human oversight provisions (Art 14) can satisfy GDPR Art 22 safeguard requirements when properly implemented, creating a compliance efficiency.
DUAL-004 Potential Conflict critical priority
COMPEL: Organize
COMPEL: Model
Personal data must be processed lawfully, fairly, and transparently; collected for specified, explicit and legitimate purposes; adequate, relevant and limited to what is necessary (data minimization); accurate; and subject to storage limitation and integrity/confidentiality safeguards.
AI Act — Article 10
Training, validation, and testing data sets must meet quality criteria: relevant, representative, free of errors, complete, and subject to appropriate governance practices including bias examination, annotation procedures, and gap identification.
Conflict Resolution Guidance
Potential tension between GDPR data minimization (Art 5(1)(c)) and AI Act data quality/representativeness (Art 10(3)). Resolution: establish a documented legal basis for processing the data volume needed for AI quality, demonstrate that the data set is the minimum necessary for achieving representativeness, and apply technical safeguards (pseudonymization, access controls).
Evidence requirements & notes
Evidence Requirements
Data governance policy covering both GDPR principles and AI Act requirements
Legal basis documentation for training data processing
Data minimization justification for AI data volumes
Data quality assessment reports
Bias examination results
Notes
The tension between GDPR data minimization and AI Act representativeness is one of the most significant conflicts. Art 10(5) of the AI Act provides a limited derogation for bias detection using special category data.
DUAL-005 Partial Overlap high priority
COMPEL: Organize
COMPEL: Produce
Record-Keeping Obligations
GDPR — Article 30
Controllers and processors must maintain records of processing activities including purposes, categories of data subjects and personal data, recipients, transfers, retention periods, and security measures.
AI Act — Article 12
High-risk AI systems must technically allow automatic recording of events (logs) throughout the system lifetime, ensuring traceability, audit trail completeness, and minimum six-month retention accessible to authorities.
Conflict Resolution Guidance
Implement a unified record-keeping system: GDPR processing activity records (organizational/legal focus) combined with AI Act event logs (technical/operational focus). Ensure log retention policies satisfy both the GDPR storage limitation principle and the AI Act six-month minimum.
Evidence requirements & notes
Evidence Requirements
Records of processing activities (ROPA) covering AI system data processing
AI system event logs meeting Art 12 requirements
Unified log retention policy satisfying both regimes
Authority access procedures for both data protection and AI oversight bodies
Notes
GDPR records focus on data processing activities; AI Act logs focus on system operation events. Both are required and should reference each other for completeness.
DUAL-006 Complementary high priority
COMPEL: Produce
COMPEL: Learn
Data subjects have rights to access, rectification, erasure, restriction, portability, objection, and not to be subject to solely automated decisions. Controllers must respond within one month.
AI Act — Article 14(4), Article 86
Affected persons have the right to an explanation of individual decisions made by high-risk AI systems and the right to contest such decisions. Member States may establish additional rights.
Evidence requirements & notes
Evidence Requirements
Unified rights request handling process
Explanation generation mechanism for AI decisions
Decision contestation workflow and SLAs
Response timeline compliance records
Notes
GDPR rights are broader (access, erasure, portability); AI Act rights are deeper for AI decisions (explanation, contestation). Implement a unified rights management system covering both.
DUAL-007 Complementary high priority
COMPEL: Organize
Designated Compliance Roles
GDPR — Article 37, Article 38, Article 39
Data Protection Officer (DPO) must be designated for public authorities and organizations whose core activities involve large-scale systematic monitoring or processing of special categories of data. DPO must be independent, report to highest management, and have expert knowledge.
AI Act — Article 4(3), Article 26(5)
Deployers of high-risk AI systems must designate a natural person responsible for human oversight. Providers must ensure AI literacy of their staff. While no formal "AI Compliance Officer" role is mandated, the obligations imply a designated AI governance function.
Evidence requirements & notes
Evidence Requirements
DPO appointment documentation
AI governance officer/function designation
Role and responsibility matrix showing DPO and AI governance function interaction
AI literacy training records for relevant staff
Notes
The DPO and AI compliance function should collaborate closely. In smaller organizations, the DPO may take on AI compliance responsibilities. Clear delineation of responsibilities is essential.
DUAL-008 Potential Conflict high priority
COMPEL: Organize
COMPEL: Model
Consent must be freely given, specific, informed, and unambiguous for processing personal data. For special categories, explicit consent is required. Consent must be withdrawable at any time without detriment.
AI Act — Article 10(5), Article 53(1)(d)
AI Act allows exceptional processing of special category personal data for bias detection under strict safeguards. GPAI providers must publish sufficiently detailed summaries of training data content.
Conflict Resolution Guidance
Where consent is the legal basis: ensure consent mechanisms clearly cover AI training purposes, allow granular choices (training vs. inference), and support withdrawal (though practical model unlearning may be limited). Consider legitimate interests (Art 6(1)(f)) as an alternative legal basis with proper balancing test. For AI Act bias detection derogation (Art 10(5)): document compliance with GDPR safeguards and demonstrate the processing is strictly necessary.
Evidence requirements & notes
Evidence Requirements
Legal basis assessment for training data processing
Consent forms covering AI-specific purposes (if consent is the basis)
Legitimate interest assessment (if LI is the basis)
Data retention and withdrawal mechanism documentation
Art 10(5) strict necessity justification (for special category data)
Notes
Consent withdrawal poses challenges for AI training data already incorporated into models. Organizations should consider legal bases that accommodate the technical realities of AI training while respecting data subject rights.
DUAL-009 Complementary medium priority
COMPEL: Organize
Personal data transfers to third countries require adequacy decisions, appropriate safeguards (SCCs, BCRs), or derogations. The Schrems II ruling requires supplementary measures where surveillance risks exist.
AI Act — Article 53(1), Article 2(7)
AI Act applies to providers placing AI systems on the EU market regardless of establishment. GPAI models trained on data from multiple jurisdictions must comply. The regulation does not override GDPR transfer mechanisms.
Evidence requirements & notes
Evidence Requirements
Data transfer impact assessment for AI training data
Transfer mechanism documentation (SCCs, BCRs, adequacy decisions)
Supplementary measures assessment for high-risk transfers
AI model training data geographic provenance documentation
Notes
Cloud-based AI training and inference often involve cross-border transfers. Organizations must ensure GDPR transfer mechanisms cover AI-specific data flows, including model weights that may encode personal data.
DUAL-010 Full Overlap high priority
COMPEL: Produce
COMPEL: Learn
Data subjects have the right to meaningful information about the logic involved in automated decision-making, the significance, and envisaged consequences. Recital 71 references the right to obtain an explanation of the decision reached.
AI Act — Article 13, Article 86
High-risk AI systems must be designed for transparency enabling deployers to interpret outputs. Article 86 establishes the right to explanation of individual AI-assisted decisions.
Explanation delivery mechanism for affected individuals
Notes
GDPR's "meaningful information about the logic" and the AI Act's right to explanation are mutually reinforcing. The AI Act provides more operational specificity about what transparency means in practice.
DUAL-011 Complementary medium priority
COMPEL: Model
COMPEL: Produce
Privacy by Design and AI System Requirements
GDPR — Article 25
Controllers shall implement appropriate technical and organisational measures designed to implement data-protection principles (data protection by design and by default). This includes pseudonymization, data minimization, and privacy-enhancing technologies.
AI Act — Article 15
High-risk AI systems shall achieve appropriate levels of accuracy, robustness, and cybersecurity throughout their lifecycle. Redundancy, fail-safe mechanisms, and resilience against adversarial attacks are required.
Integrated design review records covering both privacy and AI quality
Notes
Privacy by design (GDPR) and accuracy/robustness (AI Act) are complementary: both require proactive engineering of safeguards. Privacy-enhancing technologies (differential privacy, federated learning) can satisfy both simultaneously.
Controllers must notify supervisory authorities within 72 hours of becoming aware of a personal data breach. Data subjects must be notified without undue delay if the breach is likely to result in a high risk to their rights and freedoms.
AI Act — Article 62, Article 73
Providers and deployers must report serious incidents to market surveillance authorities. Serious incidents include those causing death, serious damage to health, property, environment, or fundamental rights.
Conflict Resolution Guidance
Implement a unified incident management process with dual notification paths: GDPR notification to supervisory authority (72 hours) and AI Act notification to market surveillance authority. An incident may trigger both obligations simultaneously (e.g., AI system malfunction causing data breach). Coordinate timelines and reporting content to ensure consistency.
Evidence requirements & notes
Evidence Requirements
Unified incident response plan covering both GDPR and AI Act obligations
Incident classification criteria distinguishing data breaches and AI serious incidents
Dual notification templates for supervisory and market surveillance authorities
Incident log with timeline compliance records
Notes
A single AI system incident can trigger both GDPR breach notification (if personal data is affected) and AI Act serious incident reporting. Organizations need a single incident management process with dual reporting tracks.
DUAL-013 Partial Overlap medium priority
COMPEL: Organize
AI Supply Chain Governance and Joint Controllership
GDPR — Article 26, Article 28
Where two or more controllers jointly determine purposes and means of processing, they are joint controllers and must arrange their respective responsibilities by agreement. Processors must be bound by data processing agreements.
AI Act — Article 25, Article 28
Obligations apply along the AI value chain: providers, deployers, importers, distributors, and authorized representatives each have defined obligations. Downstream integrators may become providers under certain conditions.
Conflict Resolution Guidance
Map the AI Act value chain roles (provider, deployer, importer) to GDPR processing roles (controller, joint controller, processor). Ensure contractual arrangements (Art 26/28 GDPR) cover AI-specific obligations alongside data protection clauses. A single contract should address both regimes.
Evidence requirements & notes
Evidence Requirements
AI supply chain mapping with role designation under both regulations
Joint controllership agreement (where applicable) covering AI and data protection
Data processing agreements incorporating AI Act obligations
Supply chain due diligence records
Notes
AI supply chains often involve complex multi-party arrangements. An AI provider (AI Act) may be a processor (GDPR) or joint controller depending on the arrangement. Clear contractual allocation is essential.
DUAL-014 Partial Overlap high priority
COMPEL: Organize
COMPEL: Learn
Penalties and Enforcement Coordination
GDPR — Article 58, Article 83, Article 84
GDPR supervisory authorities can impose administrative fines up to EUR 20M or 4% of total worldwide annual turnover (whichever is higher) for the most serious infringements. Each Member State supervisory authority has investigative, corrective, and advisory powers.
AI Act penalties: up to EUR 35M or 7% of annual worldwide turnover for prohibited AI practices; up to EUR 15M or 3% for other obligations. The AI Office coordinates enforcement for GPAI. National market surveillance authorities enforce for high-risk AI.
Conflict Resolution Guidance
The AI Act explicitly states (Recital 10) that it complements GDPR and does not affect its application. Penalties under both regulations can theoretically be imposed for the same conduct (ne bis in idem questions may arise). Organizations should implement unified compliance programs to mitigate risk under both regimes simultaneously.
Evidence requirements & notes
Evidence Requirements
Compliance program documentation covering both GDPR and AI Act
Enforcement authority mapping (supervisory authority vs. market surveillance)
Risk assessment for dual-enforcement scenarios
Legal analysis of ne bis in idem implications
Notes
AI Act penalties (7% turnover for prohibited practices) exceed GDPR maximums (4% turnover). The interaction between GDPR supervisory authorities and AI Act market surveillance authorities requires careful organizational mapping.
Gap Analysis
Obligations that one regulation mandates but the other does not — organizations must
bridge both sides to achieve defensible dual compliance.
GAP-001 GDPR Gap Ref: AI Act Art 9
AI Risk Management System
GDPR does not mandate a dedicated risk management system for AI. The AI Act requires a documented risk management system throughout the AI lifecycle for high-risk systems.
Action: Establish an AI risk management framework that integrates with your DPIA process. Use the AI Act risk management requirements as a blueprint and extend your GDPR compliance program.
GAP-002 GDPR Gap Ref: AI Act Art 10
Training Data Quality Standards
GDPR focuses on lawful processing and data minimization but does not prescribe data quality standards for AI training data (representativeness, completeness, bias testing).
Action: Supplement GDPR data governance with AI-specific data quality requirements: bias examination, representativeness testing, and annotation quality controls as required by Art 10.
GAP-003 AI Act Gap Ref: GDPR Art 17
Right to Erasure for AI Models
The AI Act does not address how the GDPR right to erasure applies to personal data embedded in trained AI models. Model unlearning remains technically challenging.
Action: Document your approach to erasure requests involving AI training data. Consider techniques such as model retraining, machine unlearning, or data isolation with access controls.
GAP-004 AI Act Gap Ref: GDPR Art 20
Data Portability for AI Contexts
The AI Act does not address data portability in AI contexts. GDPR portability rights may be difficult to implement where data has been transformed through AI processing.
Action: Implement data export capabilities for personal data used in AI systems. Document which data can be ported and any technical limitations on portability of AI-processed data.
GAP-005 GDPR Gap Ref: AI Act Art 15
Cybersecurity and Adversarial Robustness
GDPR requires integrity and confidentiality safeguards but does not address AI-specific threats such as adversarial attacks, model poisoning, or prompt injection.
Action: Extend your security program to cover AI-specific attack vectors. Implement adversarial robustness testing, model integrity verification, and input validation against prompt injection.
GAP-006 AI Act Gap Ref: GDPR Art 9
Special Category Data in AI Training
The AI Act provides a narrow derogation (Art 10(5)) for processing special category data for bias detection, but does not fully harmonize with GDPR Art 9 conditions.
Action: When using special category data for bias detection, document both the AI Act derogation and the applicable GDPR Art 9 condition. Implement strict safeguards including pseudonymization and access controls.
Conflict Resolution
Areas where the GDPR and EU AI Act create tension that organizations must actively
resolve through program design.
CR-001
Data Governance and Processing Principles
GDPR Position
Personal data must be processed lawfully, fairly, and transparently; collected for specified, explicit and legitimate purposes; adequate, relevant and limited to what is necessary (data minimization); accurate; and subject to storage limitation and integrity/confidentiality safeguards.
AI Act Position
Training, validation, and testing data sets must meet quality criteria: relevant, representative, free of errors, complete, and subject to appropriate governance practices including bias examination, annotation procedures, and gap identification.
Resolution
Potential tension between GDPR data minimization (Art 5(1)(c)) and AI Act data quality/representativeness (Art 10(3)). Resolution: establish a documented legal basis for processing the data volume needed for AI quality, demonstrate that the data set is the minimum necessary for achieving representativeness, and apply technical safeguards (pseudonymization, access controls).
GDPR Article 5, Article 6, Article 9, Article 25 read together with AI Act Article 10. See also AI Act Recital 10 (GDPR compatibility clause).
CR-002
Consent Mechanisms for AI Training Data
GDPR Position
Consent must be freely given, specific, informed, and unambiguous for processing personal data. For special categories, explicit consent is required. Consent must be withdrawable at any time without detriment.
AI Act Position
AI Act allows exceptional processing of special category personal data for bias detection under strict safeguards. GPAI providers must publish sufficiently detailed summaries of training data content.
Resolution
Where consent is the legal basis: ensure consent mechanisms clearly cover AI training purposes, allow granular choices (training vs. inference), and support withdrawal (though practical model unlearning may be limited). Consider legitimate interests (Art 6(1)(f)) as an alternative legal basis with proper balancing test. For AI Act bias detection derogation (Art 10(5)): document compliance with GDPR safeguards and demonstrate the processing is strictly necessary.
GDPR Article 6, Article 7, Article 9, Recital 42-43 read together with AI Act Article 10(5), Article 53(1)(d). See also AI Act Recital 10 (GDPR compatibility clause).
Implementation Priority Matrix
Sequencing guidance based on regulatory priority, implementation effort, and
recommended deadlines.
ID
Area
Priority
Effort
Category
Deadline
PM-001
Impact Assessment Obligations
critical
very high
partial overlap
Q2 2026
PM-002
Transparency Obligations
critical
very high
partial overlap
Q2 2026
PM-003
Automated Decision-Making and Human Oversight
critical
very high
full overlap
Q2 2026
PM-004
Data Governance and Processing Principles
critical
very high
potential conflict
Q2 2026
PM-005
Record-Keeping Obligations
high
high
partial overlap
Q3 2026
PM-006
Individual Rights and Redress
high
high
complementary
Q3 2026
PM-007
Designated Compliance Roles
high
high
complementary
Q3 2026
PM-008
Consent Mechanisms for AI Training Data
high
high
potential conflict
Q3 2026
PM-009
Cross-Border Data Transfer for AI Models
medium
medium
complementary
Q4 2026
PM-010
Right to Explanation of AI Decisions
high
high
full overlap
Q3 2026
PM-011
Privacy by Design and AI System Requirements
medium
medium
complementary
Q4 2026
PM-012
Incident Notification and Reporting
critical
very high
partial overlap
Q2 2026
PM-013
AI Supply Chain Governance and Joint Controllership