As artificial intelligence transforms business operations across Europe, organisations face a complex compliance landscape. While the GDPR has governed data protection since 2018, the EU AI Act introduces an entirely new regulatory framework specifically for AI systems.
Understanding how these regulations intersect and where gaps emerge is critical for any organisation deploying AI technology.
The Compliance Challenge: Two Frameworks, One AI System
The GDPR and the AI Act serve different purposes but both apply to AI deployments. GDPR focuses on protecting personal data throughout its lifecycle, while the AI Act targets the safety and fundamental rights implications of AI systems themselves.
This creates a compliance burden where organisations must satisfy both frameworks simultaneously, yet neither provides a complete roadmap for the other.
Meeting GDPR requirements doesn’t automatically ensure AI Act compliance, and vice versa. There’s a missing layer between these two regulatory frameworks that organisations struggle to navigate.
How can integrated compliance frameworks give businesses a competitive advantage in AI deployment?
By streamlining compliance, reducing costs, accelerating deployment, and demonstrating responsible AI practices, businesses can move faster than competitors, build stakeholder trust, and future-proof their operations.
Why is bridging the GDPR-AI Act compliance gap now more critical than ever?
With phased implementation and higher penalties for non-compliance under the AI Act, organizations must avoid siloed efforts, inconsistent assessments, and documentation gaps to mitigate risks, liabilities, and reputational damage.
What role does the eyreACT solution play in addressing compliance gaps between GDPR and the AI Act?
eyreACT provides a unified risk assessment framework, integrated documentation, dual-framework monitoring, automated compliance mapping, and governance coordination, bridging the gaps between GDPR and the AI Act for more efficient compliance.
How do GDPR and the EU AI Act overlap and differ in their compliance requirements?
Both frameworks require transparency, risk assessment, documentation, and respect for individual rights, but they differ in methodologies, documentation specifics, and governance structures, creating gaps in compliance when implementing both regulations.
What are the main differences between GDPR and the EU AI Act?
GDPR primarily focuses on the protection of personal data and applies to any processing of personal data, whereas the EU AI Act concentrates on safety and fundamental rights concerns related to AI systems, with a risk-based approach and technical requirements.
GDPR vs AI Act: Key Differences
| Aspect | GDPR | EU AI Act |
|---|---|---|
| Primary Focus | Protection of personal data | Safety and fundamental rights in AI systems |
| Scope | Any processing of personal data | AI systems based on risk classification |
| Risk Approach | Rights-based with impact assessments | Risk-based with four categories (unacceptable, high, limited, minimal) |
| Key Requirements | Lawful basis, data minimization, transparency, rights of data subjects | Conformity assessments, technical documentation, human oversight, transparency obligations |
| Enforcement | National data protection authorities | National market surveillance authorities + EU AI Office |
| Penalties | Up to €20M or 4% of global turnover | Up to €35M or 7% of global turnover (for prohibited practices) |
| Effective Date | May 2018 | Phased implementation from February 2025 to August 2027 |
Where the Frameworks Overlap and Diverge
Areas of Overlap
Both regulations address:
- Transparency and explainability requirements
- Risk assessment obligations
- Documentation and record-keeping
- Rights of individuals affected by automated systems
- Data quality and accuracy standards
Critical Gaps
The compliance gap emerges in several areas:
- Different risk assessment methodologies: GDPR’s Data Protection Impact Assessments (DPIAs) evaluate data processing risks, while the AI Act requires conformity assessments focused on AI system capabilities and deployment contexts.
- Distinct documentation requirements: GDPR mandates records of processing activities, while the AI Act requires technical documentation packages that detail AI system design, development, and performance.
- Separate governance structures: GDPR appoints Data Protection Officers for oversight, while the AI Act may require dedicated quality management systems and post-market monitoring.
AI Act and GDPR Compliance Requirements Comparison
| Requirement Type | GDPR Implementation | AI Act Implementation | eyreACT Solution |
|---|---|---|---|
| Risk Assessment | Data Protection Impact Assessment (DPIA) | AI Risk Classification + Conformity Assessment | Unified risk framework mapping DPIA to AI Act risk tiers |
| Documentation | Records of Processing Activities (ROPA) | Technical Documentation Package | Integrated documentation repository linking data flows to AI system specs |
| Transparency | Privacy notices, right to information | Transparency obligations for high-risk AI, user instructions | Centralized transparency hub with layered disclosure |
| Human Oversight | Human intervention in automated decisions | Human oversight requirements for high-risk AI | Coordinated governance controls across both frameworks |
| Monitoring | Ongoing compliance monitoring | Post-market monitoring for high-risk AI | Real-time compliance dashboard with dual-framework tracking |
The eyreACT Compliance Bridge
eyreACT addresses the missing compliance layer by providing:
1. Unified Risk Assessment Framework
Instead of conducting separate DPIAs and AI risk assessments, eyreACT enables organisations to perform integrated evaluations that satisfy both regulatory requirements simultaneously.
2. Converged Documentation System
A single source of truth that maintains GDPR-compliant records while automatically generating AI Act technical documentation, eliminating redundancy and ensuring consistency.
3. Dual-Framework Monitoring
Real-time compliance tracking that monitors both GDPR and AI Act obligations, alerting teams to violations under either framework before they escalate.
4. Automated Compliance Mapping
Intelligent mapping between GDPR data processing activities and AI system operations, ensuring that changes in one area trigger appropriate compliance reviews in the other.
5. Governance Coordination
Tools that coordinate Data Protection Officers, AI system owners, and compliance teams under a unified governance structure that addresses both frameworks holistically.
Implementation Roadmap
| Phase | GDPR Activities | AI Act Activities | eyreACT Integration |
|---|---|---|---|
| Phase 1: Assessment | Audit personal data processing | Classify AI systems by risk level | Map data flows to AI risk categories |
| Phase 2: Documentation | Update/create ROPA and DPIAs | Develop technical documentation packages | Generate unified compliance repository |
| Phase 3: Controls | Implement data protection measures | Deploy AI governance controls | Configure integrated control framework |
| Phase 4: Monitoring | Establish ongoing GDPR monitoring | Set up post-market surveillance | Activate dual-framework dashboard |
| Phase 5: Optimization | Continuous improvement of data practices | Iterative AI system refinement | Automated compliance optimization |
Why the Gap Matters Now
With the EU AI Act’s phased implementation underway, organisations can no longer afford a siloed approach to compliance. The penalties for non-compliance with the AI Act exceed even GDPR’s substantial fines, and the reputational damage from violations under either framework can be severe.
Organizations that fail to bridge the GDPR-AI Act compliance gap face:
- Duplicated compliance efforts and wasted resources
- Inconsistent risk assessments leading to blind spots
- Documentation gaps that fail audits under either framework
- Delayed AI deployments due to compliance uncertainty
- Increased liability exposure from uncoordinated governance
Moving Forward: Integrated Compliance as Competitive Advantage
The organizations that thrive in the age of AI regulation won’t be those that merely achieve minimum compliance, but those that transform compliance from a burden into a strategic advantage. By implementing integrated compliance frameworks like eyreACT, businesses can:
- Accelerate AI deployment with confidence in regulatory alignment
- Reduce compliance costs through unified processes and automation
- Build stakeholder trust with demonstrable commitment to both data protection and AI safety
- Future-proof operations as regulations continue to evolve
- Gain competitive edge by moving faster than competitors still struggling with compliance complexity
The gap between GDPR and the AI Act represents both a challenge and an opportunity. Organisations that recognise this missing compliance layer and address it proactively will not only avoid regulatory pitfalls but position themselves as leaders in responsible AI innovation.
eyreACT provides the compliance infrastructure that bridges GDPR and EU AI Act requirements, enabling organisations to deploy AI systems confidently while maintaining comprehensive regulatory alignment across both frameworks.
FAQ
How can integrated compliance frameworks give businesses a competitive advantage in AI deployment?
By streamlining compliance, reducing costs, accelerating deployment, and demonstrating responsible AI practices, businesses can move faster than competitors, build stakeholder trust, and future-proof their operations.
Why is bridging the GDPR-AI Act compliance gap now more critical than ever?
With phased implementation and higher penalties for non-compliance under the AI Act, organizations must avoid siloed efforts, inconsistent assessments, and documentation gaps to mitigate risks, liabilities, and reputational damage.
What role does the eyreACT solution play in addressing compliance gaps between GDPR and the AI Act?
eyreACT provides a unified risk assessment framework, integrated documentation, dual-framework monitoring, automated compliance mapping, and governance coordination, bridging the gaps between GDPR and the AI Act for more efficient compliance.
How do GDPR and the EU AI Act overlap and differ in their compliance requirements?
Both frameworks require transparency, risk assessment, documentation, and respect for individual rights, but they differ in methodologies, documentation specifics, and governance structures, creating gaps in compliance when implementing both regulations.
What are the main differences between GDPR and the EU AI Act?
GDPR primarily focuses on the protection of personal data and applies to any processing of personal data, whereas the EU AI Act concentrates on safety and fundamental rights concerns related to AI systems, with a risk-based approach and technical requirements.
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