Unified Governance, the key to Data and AI governance in the EU

Introduction

In a world accelerating toward the intelligent edge, artificial intelligence is reshaping everything—from how we work to how we live. But innovation without intention can’t scale trust. That’s why, at the heart of Europe’s digital future, the EU AI Act sets a bold new standard—one that empowers progress while safeguarding what matters most: our rights, our data, and our humanity.

Yet true progress doesn’t come from regulation alone. It comes from coherence. The EU’s General Data Protection Regulation (GDPR) already leads the world in protecting personal data—the lifeblood of modern AI. When AI governance meets data governance, organizations face not two separate mandates, but one shared responsibility: to design systems that are secure, fair, and accountable by default.

This whitepaper explores the intersection of these defining frameworks. Because siloed compliance overlooks the broader perspective. And in today’s interconnected landscape, understanding how the EU AI Act and GDPR converge isn’t just helpful—it’s essential.

We believe the future of responsible AI isn’t built in fragments. It’s built on unified governance, intelligent, intentional, and seamlessly aligned with regulation. This paper offers a clear path forward: one that integrates legal clarity with design simplicity, enabling organizations to build AI that not only complies but also earns trust.

Figure 1: Intersection of AI and data governance in the EU

Executive summary
In the European Union, the future of technology is being shaped by two landmark regulations: the AI Act and the General Data Protection Regulation (GDPR). Each is a cornerstone in its own right—one setting the guardrails for ethical AI, the other defining how personal data is handled with care and respect. But when viewed together, something more powerful emerges: a vision for unified AI governance that’s not just about meeting requirements, but about building systems that people believe in.

This whitepaper makes the case for a unified governance strategy—one that doesn’t separate AI from data, but connects them through a shared foundation of responsibility, transparency, and trust. Because managing these frameworks in isolation creates complexity, it fragments oversight, multiplies effort, and ultimately puts both innovation and compliance at risk.

Instead, we propose something different: governance that’s harmonized by design. It is built on six key pillars;

1. Consistent training

2. Integrated legal frameworks

3. Cross-functional collaboration

4. Harmonized risk assessments

5. Centralized documentation

6. Unified incident response

This approach transforms regulatory obligations into organizational advantages. The result? Greater efficiency. Deeper compliance. Clearer accountability. And AI systems that are not only smarter, but also safer and more human-centric.

Inside, you’ll find a practical roadmap that unpacks how the AI Act and GDPR intersect—from transparency and risk assessment to subject rights and prohibited practices. More than guidance, it’s a blueprint for designing governance that’s as dynamic as the technology it supports.

Why AI governance alone is not enough

The EU AI Act, with its risk-based categorization and specific obligations for different AI systems, inherently interacts with the GDPR. AI systems, particularly those categorized as high-risk, often rely on vast datasets, which frequently include personal information. The quality, processing, and security of this data are governed by the GDPR. Consequently, the effectiveness of AI governance is directly contingent on robust data governance practices, and vice versa.

Managing these two domains in isolation can lead to:

Redundancy and inefficiency: The need for separate risk assessments, documentation processes, and compliance checks for AI and data processing creates unnecessary overhead.

Compliance gaps: A lack of integrated oversight can lead to overlooking crucial interdependencies, potentially resulting in non-compliance with either or both regulations. For instance, biased training data (a GDPR concern regarding data quality and fairness) can lead to discriminatory outcomes in a high-risk AI system (an AI Act concern regarding fundamental rights).

Fragmented understanding of risk: Assessing the risks associated with AI in isolation from the risks associated with the personal data it processes provides an incomplete picture of potential harms to individuals and society.

Figure 2: Unified governance improves efficiency and compliance

Demand for unified governance

Several strategic intersections between the AI Act and the GDPR create a cohesive, unified governance framework that is not only beneficial but also essential.

• Transparency and information obligations: Both the AI Act (Articles 13, 52, etc.) and GDPR (Articles 12-14) mandate transparency. For AI systems processing personal data, organizations must provide comprehensive and coherent information about both the AI's functionality and the data processing involved. A unified approach ensures consistent and user-friendly disclosures.
  
  

• Risk assessment and mitigation: The AI Act (Article 9) requires risk assessments for high-risk AI systems, encompassing potential impacts on fundamental rights. When personal data is involved, these assessments must inherently consider data protection risks (Article 35 GDPR). A unified framework enables a comprehensive evaluation of all potential harms.
  
  

• Data governance for high-risk AI: Article 10 of the AI Act emphasizes the quality and governance of data used in high-risk AI. This directly aligns with GDPR principles of data quality, accuracy, and purpose limitation (Article 5, GDPR). Unified governance ensures that data used for AI adheres to both sets of requirements.

Find more about Empowering data products with comprehensive governance and stewardship>>

• Rights of data subjects and affected persons: The AI Act grants a "right to explanation" (Article 86) to individuals affected by decisions based on certain high-risk AI systems. This right interacts with GDPR's data subject rights (Articles 15-22), particularly concerning automated decision-making (Article 22 GDPR). A unified approach ensures seamless handling of these interconnected rights.

  
  

• Prohibited practices and special categories of data: Certain AI practices prohibited under the AI Act (Article 5), such as biometric categorization based on sensitive data, directly implicate the strict rules for processing special categories of personal data under GDPR (Article 9). Unified governance ensures consistent adherence to these prohibitions and safeguards.

Figure 3: Comparison of EU AI Act and GDPR

Benefits of a unified governance strategy

Adopting a unified AI governance framework for the intersection of the EU AI Act and data protection laws offers a multitude of strategic advantages that extend beyond mere regulatory compliance. By integrating the management of AI systems and personal data, organizations can unlock significant benefits across various dimensions:

Figure 4: Strategic advantages of unified governance

1.  Enhanced efficiency and reduced operational costs

• Streamlined processes: Rather than operating parallel workflows for risk assessment, documentation, auditing, and reporting across AI and data domains, a unified governance model enables streamlined, integrated processes. This approach minimizes redundancy, enhances operational efficiency, and ensures smarter use of time and resources.

  
  

• Centralized oversight: A single governance framework provides a holistic view of compliance obligations, reducing the need for multiple monitoring systems and specialized personnel for each domain.

  
  

• Cost optimization: Consolidating governance activities can lead to lower operational costs associated with software, training, and personnel.

2. Improved and comprehensive data compliance

• End-to-end risk management: A unified governance framework enables an improved understanding and management of risks that span both AI systems and personal data. This includes identifying and mitigating interconnected risks, such as bias in AI stemming from flawed data.

  
  

• Reduced compliance gaps: By considering the interplay between the AI Act and GDPR, organizations can avoid overlooking crucial obligations that might fall between the cracks of siloed governance structures.

  
  

• Consistent interpretation and application: A unified approach fosters a consistent understanding and application of the legal requirements across the organization, reducing the risk of misinterpretations and non-compliance.

3. Reinforcing ethical AI through unified governance and trust

• Integrated ethical considerations: A unified framework facilitates the integration of ethical principles into both AI development and data processing practices, fostering a more responsible and trustworthy approach to technology deployment.

  
  

• Increased transparency and accountability: Centralized governance provides a clearer understanding of how AI systems operate and how personal data is utilized, thereby enhancing transparency for stakeholders and strengthening accountability mechanisms.

  
  

• Building user and public trust: Demonstrating a commitment to both robust AI governance and stringent data protection builds user confidence and public trust in the organization's AI systems and data handling practices.

  
  

4. Facilitation of responsible innovation

   
   

• Clear and integrated guidelines: A unified framework provides developers and innovators with clear and consistent policies that encompass both AI and data protection considerations, enabling them to innovate responsibly within defined ethical and legal boundaries.

  
  

• Reduced uncertainty: A clear understanding of the integrated regulatory landscape reduces uncertainty, enabling organizations to explore and deploy AI technologies confidently.

  
  

• Competitive advantage: Organizations with strong, unified governance frameworks can gain a competitive advantage by demonstrating their commitment to ethical and responsible AI, attracting customers and partners who value these principles.

  
  

5. Improved data quality and utilization

• Consistent data governance practices: A unified framework ensures consistent data governance practices are applied across all data used in AI systems, leading to improved data quality, accuracy, and reliability.

  
  

• Enhanced data insights: Higher quality and well-governed data lead to more reliable insights and better performance of AI models.

  
  

• Effective data sharing and collaboration: Unified governance can establish clear rules and protocols for data sharing and collaboration, fostering innovation and knowledge sharing within the organization while maintaining compliance.

Unified governance implementation

Establishing a successful unified governance framework under EU law demands a holistic approach, one that thoughtfully aligns people, processes, and technology to reflect the interconnected nature of AI and data governance.

People: Fostering collaboration and expertise

The foundation of unified governance lies in building the right teams and fostering a culture of collaboration and shared responsibility.

• Establish cross-functional teams: Break down silos between AI development, data protection, legal, and ethics departments. Create dedicated teams or working groups with representatives from each area to ensure a holistic understanding of interconnected requirements.  

  
  

• Define clear roles and responsibilities: Clearly delineate responsibilities for AI governance and data governance within these cross-functional teams. Identify individuals accountable for specific aspects of compliance under both the AI Act and GDPR.

  
  

• Appoint ai ethics and data protection champions: Designate individuals within the organization to champion ethical considerations in AI development and the principles of data protection. These champions can advocate for integrated approaches and raise awareness.  

  
  

• Invest in training and awareness: Implement comprehensive training programs that educate all relevant personnel on the fundamental principles and practical implications of both the EU AI Act and GDPR. Emphasize the interconnectedness of these regulations and the importance of a unified approach.

  
  

• Promote a culture of shared responsibility: Foster a culture where all employees understand their role in ensuring compliance with both AI and data governance frameworks. Encourage open communication and collaboration across teams.

Figure 5: People centric approach

Process: Designing integrated frameworks and workflows

Establishing well-defined and integrated processes is crucial for effective unified governance.

• Develop an integrated policy framework: Create overarching policies and procedures that explicitly address the requirements of both the AI Act and GDPR. Map overlapping obligations and ensure consistency in approach.

  
  

• Harmonize risk assessment methodologies: Implement a unified risk assessment process that evaluates both AI-specific risks (e.g., bias, lack of robustness) and data protection risks (e.g., privacy breaches, unlawful processing) within a single framework.

  
  

• Establish unified documentation and record-keeping: Implement centralized systems for documenting AI system development lifecycles, data processing activities, risk assessments, compliance measures, and decision-making processes related to both AI and data.

  
  

• Design integrated transparency and consent mechanisms: Develop clear and user-friendly mechanisms for providing information and obtaining consent (where necessary) that address the transparency requirements of both the AI Act and GDPR in a coherent manner.

  
  

• Create unified incident response and data breach procedures: Establish a single protocol for identifying, managing, and reporting security incidents and data breaches that may involve both AI systems and personal data.

  
  

• Implement integrated audit and monitoring processes: Establish regular audit and monitoring processes that assess compliance with both the AI Act and GDPR in a coordinated manner.

Figure 6: Process: Integrated framework and workflows

Technology: Leveraging tools for integrated compliance

Technology can play a crucial role in supporting and enabling unified governance.

• Utilize integrated Governance, Risk, and Compliance (GRC) platforms: Explore GRC tools that can help manage and track compliance obligations across both AI and data governance frameworks. These platforms can centralize documentation, automate workflows, and provide a holistic view of risk.

  
  

• Implement Privacy-Enhancing Technologies (PETs): Explore and deploy PETs that can facilitate data processing for AI development while minimizing privacy risks and supporting GDPR principles.

  
  

• Utilize AI-powered compliance tools: Explore AI-powered tools that can aid in tasks such as identifying potential bias in datasets, monitoring compliance with transparency obligations, and automating aspects of risk assessment.  

  
  

• Ensure secure and privacy-preserving AI development environments: Utilize secure development environments that incorporate privacy-by-design principles and facilitate compliance with data protection requirements throughout the AI lifecycle.

  
  

• Implement robust data management and security systems: Deploy technologies and processes that ensure the security, integrity, and quality of data used in AI systems, aligning with both the AI Act's data governance requirements and GDPR's security obligations.

Figure 7: Integrated technology solutions

Bringing it together

The EU AI Act and GDPR together signal a bold vision for Europe’s digital future—one that balances the promise of innovation with the protection of fundamental rights. Their intersection is not incidental; it calls for a deliberate shift toward unified governance. By aligning the principles and obligations of both frameworks, organizations can transcend fragmented compliance and adopt a more integrated, ethical, and practical approach to AI. Embracing this is more than regulatory alignment, it is the foundation for building AI that is not only robust but principled, trusted, and built to last in the European Union.

Our offering: Empowering your organization’s unified governance journey

At Fractal, we recognize that navigating the complex intersection of the EU AI Act and data protection laws requires a holistic and integrated approach. Our specialized Unified Governance services are designed to provide organizations with the comprehensive expertise and tailored solutions needed to effectively manage both their AI systems and data assets in a compliant, ethical, and strategic manner.

Our integrated suite of offerings encompasses both data governance and AI governance, ensuring a synergistic approach to your regulatory obligations and innovation goals

Data governance for businesses

• Data governance strategy: Get a clear and actionable data governance strategy aligned with your business objectives and regulatory requirements, including GDPR compliance and its implications for AI.

  
  

• Data quality: Find solutions to ensure the accuracy, completeness, consistency, and timeliness of your data, a critical foundation for reliable AI systems and GDPR compliance.

  
  

• Metadata management: We assist in establishing robust metadata management practices to understand, control, and leverage your data assets effectively, enhancing transparency and facilitating compliance across both AI and data regulations.

  
  

• Master data management: Find a single source of truth for your critical data entities, improving data consistency and enabling more reliable AI insights and GDPR compliance.

  
  

• Data privacy: End-to-end adherence to data privacy regulations, including GDPR, by implementing data protection principles, managing consent, and facilitating data subject rights in the context of AI usage.

  
  

• Data literacy: Programs to enhance data literacy across your organization, empowering employees to understand and utilize data responsibly in AI initiatives while adhering to data governance policies.

Responsible AI

• Responsible AI assessment and recommendation: Evaluate existing AI systems for fairness, bias, and transparency, and deliver actionable improvements aligned to ethical AI principles. Learn more about responsible AI.

  
  

• RAI-by-design: We provide guardrails, frameworks, and processes to govern your AI systems throughout their entire lifecycle, from development and training to deployment and monitoring, ensuring compliance at each stage.

  
  

• AI governance framework design and operationalization: Design and implement scalable governance structures, policies, and processes to ensure accountability and oversight across your AI landscape.

  
  

• RAI culture and literacy: Build organization-wide awareness and skills through targeted trainings that foster a culture of ethical AI understanding and adoption.

  
  

• AI compliance and regulatory advisory: Stay ahead of global AI regulations with expert guidance on legal, ethical, and policy compliance for your AI initiatives.

By leveraging our integrated unified governance offerings, your organization can move beyond siloed compliance efforts and establish a cohesive strategy for managing both your data and AI assets. We empower you to build trustworthy, compliant, and innovative AI solutions, fostering confidence among your users and stakeholders as you navigate the future of AI in the EU with clarity and strategic advantage. Contact us today to learn how our tailored services can support your unique Unified Governance journey.