Introduction
AI compliance is rapidly evolving with new regulations like the EU AI Act, updated GDPR interpretations, and industry-specific requirements. Organizations must proactively implement compliance frameworks to avoid penalties and maintain trust.
EU AI Act Overview
The EU AI Act categorizes AI systems by risk: Prohibited (social scoring, manipulation), High-risk (hiring, credit scoring), Limited risk (chatbots), Minimal risk (games). Each category has specific requirements for transparency, accuracy, human oversight, and documentation.
GDPR and AI Systems
GDPR applies to AI processing personal data. Key requirements: lawful basis for processing, data minimization, purpose limitation, automated decision-making rights, and data protection impact assessments. AI systems must implement privacy by design.
Industry-Specific Regulations
Healthcare: FDA AI/ML guidance, HIPAA compliance. Financial: Model risk management, fair lending laws. Automotive: Safety standards for autonomous systems. Each industry has specific AI requirements beyond general regulations.
Compliance Implementation
Establish governance frameworks, implement explainable AI, maintain audit trails, conduct bias testing, create documentation standards, train staff on requirements, and establish regular compliance reviews. Compliance must be built into AI development processes.
Future-Proofing Strategy
Monitor regulatory developments, participate in industry standards, implement flexible compliance frameworks, maintain detailed documentation, establish legal expertise, and build relationships with regulators. Proactive compliance reduces future adaptation costs.