From GDPR to AI Act: The Evolution of Data and AI Security in the EU

The European Union’s AI Act is the world’s first comprehensive law governing artificial intelligence. Building on the foundations of the GDPR and other digital regulations, it defines how organizations must develop, deploy, and secure AI systems responsibly. But to understand how to achieve EU AI Act compliance, and how those compliance efforts connect to AI data security, we must trace its evolution through the EU’s broader digital governance framework.

The Foundation: GDPR’s Lasting Influence on AI Data Security

The General Data Protection Regulation (GDPR) remains the cornerstone of EU digital regulation. Its core principles – such as transparency, minimization, and integrity and confidentiality – establish baseline requirements that every subsequent regulation builds upon.

For the purposes of interpreting the AI Act, several GDPR provisions are particularly critical:

Article 22 addresses automated decision-making and profiling, and directly informs the AI Act's approach to human oversight requirements for high-risk systems. When an AI system makes decisions that have significant impacts on individuals, both the GDPR and AI Act demand safeguards, including meaningful human review.

Similarly, GDPR's Article 35 on Data Protection Impact Assessments (DPIAs) provides the methodological template for the AI Act's risk management framework. Organizations already conducting DPIAs for high-risk data processing will recognize the AI Act's conformity assessment procedures. Both require systematic evaluation of risks to fundamental rights, documentation of mitigation measures, and ongoing monitoring.

Finally, the GDPR’s “privacy by design and by default” principle (Article 25) has evolved into “AI security by design.” Modern DSPM for AI strategies apply these same ideas: embedding data protection and access controls into systems from the ground up.

Prohibited Practices: Defining Ethical Boundaries for AI

Like its predecessors, the AI Act establishes clear prohibitions to protect fundamental rights. The AI Act's Article 5 bans AI practices that pose unacceptable risks, including manipulative systems that exploit vulnerabilities, social scoring by governments, real-time biometric identification in public spaces (with narrow exceptions), and biometric categorization based on sensitive characteristics.

These prohibitions draw directly from GDPR's Article 9, which restricts processing of special categories of personal data including biometric data for uniquely identifying individuals, and from the Digital Services Act (DSA) Article 28, which prohibits targeted advertising based on sensitive data or targeting minors. When the AI Act bans emotion recognition systems in certain contexts or prohibits AI that manipulates human behavior in harmful ways, it extends the protective logic already established in data protection and platform regulation.

The DSA's Article 34, which requires Very Large Online Platforms to assess systemic risks including effects on civic discourse and democratic processes, similarly informs how we should interpret the AI Act's prohibitions on AI systems that threaten democratic values. EU AI Act compliance requires organizations to respect the bright lines regulators have drawn around practices that threaten human dignity and democratic society.

Risk-Based Regulation: The Core of EU AI Act Compliance

Risk-based regulation is perhaps the most significant shared feature across the EU's digital laws. The GDPR implicitly operates on a risk-based model, requiring heightened protections (like DPIAs) for processing that poses high risks to individuals' rights and freedoms. The DSA makes this explicit with its tiered approach, imposing the strictest obligations on Very Large Online Platforms whose scale creates systemic risks.

The AI Act adopts this risk-based architecture most comprehensively, creating four risk tiers: unacceptable (prohibited), high (heavily regulated), limited (transparency requirements), and minimal (largely unregulated).

For high-risk AI systems, the AI Act mandates risk management systems, data governance protocols, technical documentation, transparency, human oversight, and accuracy requirements. These obligations closely parallel the GDPR's requirements for high-risk data processing. Practitioners familiar with conducting DPIAs will recognize the systematic approach: identify risks, assess severity and likelihood, implement mitigation measures, document everything, and continuously monitor.

An effective AI security platform can help automate this process, unifying visibility across models, datasets, and environments to ensure ongoing risk monitoring.

Transparency and Accountability in AI Operations

The principle of transparency also cuts across EU digital regulations. The GDPR requires organizations to inform individuals about how their personal data is processed, including information about automated decision-making. The Digital Markets Act (DMA) requires gatekeepers to provide transparency about how they rank and display results. The DSA mandates that platforms explain how their recommender systems work and offer users at least one non-profiled alternative.

The AI Act synthesizes these transparency obligations into a comprehensive framework. EU AI Act compliance requires providers of high-risk AI systems to ensure transparency for deployers and affected persons. That includes disclosing when people interact with AI systems and how automated decisions are made.

For general-purpose AI models (like large language models), providers must document training data sources, computational resources, and model limitations. This level of disclosure mirrors the DSA’s requirements for platform transparency, ensuring that both algorithms and AI models remain accountable to public scrutiny.

Data Governance: Fueling Secure and Compliant AI Systems

AI systems are fundamentally data-driven, making the intersection of the AI Act with data governance regulations particularly important. The Data Governance Act (DGA) and Data Act set strict conditions for accessing, sharing, and processing data used in AI training.

Organizations developing or deploying AI must ensure:

• Legal data access under the Data Act for IoT and connected devices.
  
• Transparency obligations if operating as data intermediaries under the DGA.
  
• Compliance with DMA restrictions if they are gatekeepers handling platform data.
  

Here, DSPM for AI plays a vital role, offering visibility into where sensitive data lives, who accesses it, and how it flows into AI models. This not only strengthens compliance but also prevents data leakage and misuse.

Practical Implications: Reading the AI Act Holistically

For practitioners, understanding the AI Act requires seeing it as part of this larger regulatory ecosystem. To achieve true EU AI Act compliance, organizations must align multiple regulatory obligations:

• GDPR: lawful data processing and privacy safeguards
  
• DSA: content moderation and algorithmic transparency
  
• DMA: platform accountability and anti-monopoly data use
  
• DGA & Data Act: fair data sharing and access rights
  

Each law reinforces the others, forming a coherent digital-rights framework that balances innovation with trust and safety.

Conclusion: The Future of AI Data Security in the EU

The EU's approach to digital regulation, from GDPR through the AI Act, reflects a coherent vision: technology must serve human dignity, fundamental rights, and democratic values. Each regulation addresses a different facet of the digital economy, but they share common principles: transparency, accountability, and risk-based proportionality.

For organizations deploying AI systems in or affecting the EU market, this interconnectedness means compliance cannot be siloed. Achieving EU AI Act compliance requires understanding GDPR's processing principles, DSA's platform obligations, DMA's gatekeeper restrictions, and Data Act provisions governing your data sources. When operating together, these laws constitute an integrated framework where each regulation reinforces and clarifies the others.

Modern AI security platforms such as Cyera empower enterprises to operationalize these principles, mapping sensitive data, enforcing least-privilege access, and embedding compliance automation across AI workflows.

Frequently Asked Questions

What is the EU AI Act?
It’s the EU’s comprehensive regulation governing AI systems, classifying them by risk and enforcing strict rules for high-risk applications.

How does GDPR relate to the AI Act?
The AI Act builds on GDPR’s data-protection principles, extending them to algorithmic decision-making, AI risk management, and transparency.

What is DSPM for AI?
Data Security Posture Management (DSPM) for AI continuously monitors how sensitive data flows into and through AI models, ensuring compliance and reducing exposure risks.

Who must comply with the AI Act?
Any organization developing or deploying AI systems in the EU, or offering AI-driven services to EU residents, falls under its jurisdiction.

Ready to Strengthen Your AI Security and Compliance Strategy?

Achieving EU AI Act compliance requires visibility, governance, and control across your data ecosystem. Cyera’s AI security platform helps you unify GDPR, AI Act, and Data Act compliance, protecting sensitive data while enabling innovation. 👉 Get a Demo to see how Cyera can help your organization stay secure, compliant, and future-ready.