The EU AI Act is no longer a future concern. It’s here, and organizations deploying AI systems need to understand their obligations. This isn’t just a European issue. If your AI systems affect EU citizens, these requirements likely apply to you.
Here’s what you need to know to navigate compliance.
The Risk-Based Approach
The EU AI Act categorizes AI systems by risk level, with requirements scaling accordingly:
Unacceptable Risk (Prohibited)
Certain AI applications are banned outright:
- Social scoring systems by governments
- Real-time biometric identification in public spaces (with limited exceptions)
- AI that exploits vulnerabilities of specific groups
- Subliminal manipulation that causes harm
If your AI falls into this category, there’s no compliance path. Don’t build it.
High Risk (Heavy Regulation)
AI systems in these categories face significant requirements:
- Critical infrastructure (energy, transport, water)
- Education and vocational training
- Employment and worker management
- Essential services (credit, insurance, emergency services)
- Law enforcement and justice
- Migration and border control
- Biometric identification
High-risk systems must meet requirements for data governance, documentation, transparency, human oversight, accuracy, robustness, and cybersecurity.
Limited Risk (Transparency Obligations)
Systems like chatbots and emotion recognition have transparency requirements. Users must know they’re interacting with AI.
Minimal Risk (No Specific Requirements)
Most AI applications fall here. No specific compliance requirements, though general principles apply.
Key Requirements for High-Risk Systems
If you’re deploying high-risk AI, here’s what compliance looks like:
Risk Management System
Implement a documented process to identify, analyze, estimate, and evaluate risks. This isn’t a one-time assessment. It’s ongoing throughout the system lifecycle.
Data Governance
Training, validation, and testing datasets must meet quality criteria. You need documented processes for data collection, preparation, and bias mitigation.
Technical Documentation
Comprehensive documentation that demonstrates compliance. This includes system architecture, design choices, training methodologies, and testing results.
Record Keeping
Automatic logging of system operation. Logs must be retained and accessible for compliance verification.
Transparency
Clear instructions for users, including system capabilities, limitations, and known risks. Users should understand what the AI does and doesn’t do.
Human Oversight
Design systems to allow effective human oversight. This includes the ability to understand outputs, intervene when necessary, and override or reverse decisions.
Accuracy, Robustness, and Cybersecurity
Systems must achieve appropriate levels of accuracy for their intended purpose. They must be resilient to errors and attacks, with cybersecurity measures appropriate to the risk.
Timeline and Enforcement
The regulation is being phased in:
- February 2025: Prohibitions on unacceptable risk AI take effect
- August 2025: Requirements for general-purpose AI models
- August 2026: Full requirements for high-risk systems
Penalties for non-compliance are significant: up to 7% of global annual turnover for the most serious violations.
Practical Steps to Prepare
Compliance isn’t achieved overnight. Start now:
1. Inventory Your AI Systems
Document all AI systems you develop, deploy, or use. Classify them according to the Act’s risk categories.
2. Gap Analysis
For high-risk systems, compare current practices against Act requirements. Identify gaps in documentation, governance, and technical controls.
3. Governance Framework
Establish or update your AI governance framework. Define roles, responsibilities, and processes for AI development and deployment.
4. Documentation Sprint
Technical documentation is a significant requirement. Start building comprehensive documentation for high-risk systems now.
5. Training
Ensure your teams understand the requirements. This includes developers, data scientists, compliance staff, and leadership.
6. Vendor Assessment
If you use third-party AI systems, assess their compliance. Your obligations don’t disappear because you’re using someone else’s technology.
The Broader Governance Context
The EU AI Act doesn’t exist in isolation. It’s part of a broader movement toward AI governance:
NIST AI Risk Management Framework provides complementary guidance for organizations regardless of EU exposure.
ISO 42001 offers a management system standard for AI that aligns with regulatory requirements.
Industry-specific regulations may add additional requirements depending on your sector.
Smart organizations are building governance frameworks that address multiple standards and regulations, not just point compliance with single requirements.
Moving Forward
Compliance with the EU AI Act isn’t optional if you’re affected. But it’s also an opportunity. Organizations that build robust governance now will be better positioned for:
- Regulatory requirements in other jurisdictions
- Customer and stakeholder trust
- Reduced risk from AI failures
- Competitive advantage in regulated markets
The investment in compliance today is an investment in sustainable AI adoption.
Need help assessing your compliance position? Our governance team can help you inventory systems, identify gaps, and build a roadmap to compliance. Schedule a conversation to discuss your situation.