Déjà Vu? Why the EU AI Act Feels Like GDPR All Over Again
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When the EU General Data Protection Regulation (GDPR) took effect in 2018, it reshaped global privacy and compliance expectations overnight. Legal teams scrambled, compliance budgets ballooned, and enterprises realized that “we’ll deal with it later” wasn’t an option.
Now that the EU AI Act is on the horizon, many organizations are experiencing déjà vu. A new regulation, new obligations, and urgent boardroom questions:
Who owns this? What are our risks? Are we ready?
For most, the answer is not yet.
Regulation Catches Up to Innovation
Like GDPR, the EU AI Act is built on a simple premise: innovation without oversight creates risk. Both frameworks emerged after rapid technological adoption left governance behind.
GDPR addressed uncontrolled data collection and opaque consent practices.
The AI Act responds to algorithmic decision-making that now influences banking, healthcare, HR, and defense.
Both place accountability squarely on organizations by demanding proof of responsible operations through structured governance, documentation, and risk assessments.
GDPR and the AI Act: Key Parallels
The AI Act is broader in scope, but the similarities to GDPR are clear and crucial for compliance officers and privacy analysts to understand.
- Extraterritorial Reach
- GDPR applies if you process EU data.
- The AI Act applies if your AI systems impact EU citizens, regardless of where you are based.
- GDPR applies if you process EU data.
- Risk-Based Approach
- GDPR distinguishes between personal data types.
- The AI Act classifies AI systems as minimal, limited, high, or unacceptable risk, requiring proactive AI risk assessment tools to document exposure.
- GDPR distinguishes between personal data types.
- Governance and Documentation
“Trust us” won’t cut it.
- GDPR required privacy programs and data protection impact assessments.
- The AI Act requires documentation of AI systems, technical transparency, and human oversight, ideally managed through privacy management software or a privacy management solution.
- GDPR required privacy programs and data protection impact assessments.
- Serious Penalties for Noncompliance
- The AI Act’s fines can reach €35M or 7% of global turnover, exceeding GDPR’s thresholds.
Regulators learned that meaningful enforcement drives accountability.
- The AI Act’s fines can reach €35M or 7% of global turnover, exceeding GDPR’s thresholds.
The New Challenge: AI Risk Extends Beyond Privacy
GDPR focused on data — who collects it and how it’s used.
The EU AI Act focuses on decisions — how systems process data, produce outputs, and influence outcomes.
This means compliance is no longer limited to privacy teams. Legal, risk, cybersecurity, and data science functions all play a role in AI governance. High-risk systems in healthcare, HR, and financial services must prove explainability, oversight, and fairness.
Organizations need privacy and AI risk assessment tools that track decisions, classify risk, and ensure transparency across vendors and internal teams.
Global Ripple Effects: Compliance Beyond Europe
Just as GDPR inspired global privacy reforms, the EU AI Act is shaping the next wave of international AI regulation.
Countries like Canada, Brazil, Japan, and Singapore are drafting similar frameworks, while U.S. regulators, including the FTC and SE,C are strengthening expectations for AI transparency.
Global organizations must now treat AI governance as part of enterprise risk management, not a regional requirement. Starting early with privacy software for compliance officers and vendor risk assessment tools can streamline readiness across jurisdictions.
What Compliance Leaders Should Do Now
If GDPR taught the privacy community anything, it’s that waiting for enforcement is a costly mistake.
1. Map Your AI Footprint
Identify where AI is used across your organization, including “shadow AI” from vendors or employees using unapproved tools.
2. Classify AI Systems by Risk
Use AI and privacy risk assessment tools to categorize each system and document controls for high-risk applications.
3. Establish Ownership
Define who is accountable for AI compliance and how oversight is documented in your privacy incident management software.
4. Define Human Oversight
Ensure your teams can explain, challenge, or override automated decisions.
5. Strengthen Transparency
Prepare to disclose AI usage and impact to regulators, customers, and investors.
These are not checkboxes; they’re operational disciplines that define responsible governance.
Where Radar Fits In
At RadarFirst, we’ve helped organizations build defensible compliance programs since the dawn of GDPR. The same readiness principles now apply to AI.
- Radar Privacy™ delivers structured, audit-ready documentation for every privacy and incident decision — who decided what, when, and under which law. It’s an ideal HIPAA incident response tool for regulated industries.
- Radar AI Risk™ extends these capabilities to AI systems, mapping legal obligations clause by clause and classifying AI use cases by risk and sensitivity.
Together, these solutions form a privacy management platform that unites data protection, AI compliance, and vendor accountability into a single, defensible record.
Déjà Vu, with a Difference
If GDPR was the wake-up call for data protection, the EU AI Act is the next chapter. It expands accountability from data to decisions.
Organizations that learned from GDPR will recognize the pattern: early preparation, cross-functional alignment, and evidence-based documentation.
Those that don’t will find themselves repeating history — only this time, the risks are broader, the fines are steeper, and the technology is smarter.
AI governance is the new privacy.
And those who master it will lead responsibly into the AI era.
Ready to see how defensible AI governance works in practice?