Regulatory requirements for AI UX

Regulatory frameworks increasingly shape how organizations design AI experiences, making compliance a fundamental design consideration. These requirements directly influence interface design, information architecture, and governance practices.

• GDPR fundamentals for AI design: The GDPR establishes key principles affecting AI design, including purpose limitation, data minimization, and transparency requirements. For example, purpose limitation requires that personal data collected for one purpose cannot be repurposed for incompatible uses without appropriate safeguards. Data minimization means AI systems should use only necessary data for their function, which may require pseudonymization techniques.^[1]
• EU AI Act risk classification system: The EU AI Act introduces a risk-based approach with specific categories. "Unacceptable risk" systems, like social scoring AI, are banned outright. "High-risk" AI systems in areas like education, employment, and law enforcement require human oversight, transparency, and robustness. Even systems not classified as high-risk must comply with transparency requirements, especially when they interact directly with humans.^[2]
• Cross-industry compliance integration: Different sectors face additional requirements beyond general regulations. Organizations must integrate these diverse requirements into coherent design approaches. This requires close collaboration between legal, design, and technical teams to create experiences that satisfy regulatory requirements without compromising user experience.