AI Compliance Checklist for Enterprises 2025

Organizational Structure

• Designated executive accountable for AI governance
• Established AI governance committee with cross-functional representation
• Defined roles and responsibilities for AI development and deployment
• Clear escalation paths for AI-related decisions and incidents
• Regular board-level reporting on AI initiatives and risks

Policies and Documentation

• AI acceptable use policy documented and communicated
• AI risk classification framework established
• Data governance policies covering AI training and inference data
• Vendor management policy for third-party AI tools
• Incident response procedures specific to AI systems
• Documentation of all AI systems in use (AI inventory)

Risk Assessment

• Risk assessment conducted for each AI system before deployment
• High-risk AI systems identified and documented
• Risk mitigation measures implemented for identified risks
• Regular reassessment of AI risks (at least annually)
• Documentation of risk assessment methodology and results

Risk Categories Addressed

• Bias and fairness risks assessed
• Privacy and data protection risks assessed
• Security and adversarial risks assessed
• Reliability and accuracy risks assessed
• Transparency and explainability risks assessed
• Human oversight requirements identified

Security Controls

• Access controls implemented for AI systems and data
• Encryption for AI data at rest and in transit
• Prompt injection and adversarial attack protections
• Secure development practices for AI components
• Regular security testing of AI systems

Guardrails and Safety Controls

• Input validation and filtering implemented
• Output filtering for harmful or inappropriate content
• PII detection and protection mechanisms
• Hallucination detection and mitigation
• Human-in-the-loop for high-risk decisions
• Kill switch or emergency shutdown capability

Data Management

• Data inventory documenting AI training and inference data
• Data quality assessment and documentation
• Legal basis established for data processing
• Data retention policies applied to AI data
• Cross-border data transfer mechanisms in place

Privacy Controls

• Privacy impact assessments for AI systems processing personal data
• Data subject rights processes (access, deletion, correction)
• Consent mechanisms where required
• Data minimization principles applied
• Purpose limitation enforced

User-Facing Transparency

• Users informed when interacting with AI systems
• AI-generated content clearly labeled where required
• Explanation of how AI decisions affect users (where applicable)
• Complaint and appeal mechanisms for AI decisions

Technical Documentation

• Model cards or documentation for AI models
• Training data documentation
• Performance metrics and limitations documented
• Version control and change documentation

Continuous Monitoring

• Real-time monitoring of AI system behavior
• Performance metrics tracked and reported
• Drift detection for model performance
• Anomaly detection for unexpected behavior
• User feedback collection and analysis

Audit and Logging

• Comprehensive logging of AI inputs and outputs
• Audit trail maintained for compliance review
• Log retention per regulatory requirements
• Regular compliance audits conducted
• Third-party audits for high-risk systems

High-Risk AI Systems (If Applicable)

• Conformity assessment completed
• CE marking affixed (if required)
• Registration in EU AI database
• Quality management system implemented
• Post-market monitoring plan in place
• Serious incident reporting procedures established

General-Purpose AI (If Using Foundation Models)

• Technical documentation from provider reviewed
• Compliance with copyright requirements verified
• Systemic risk assessment (for high-capability models)

• Model risk management framework (SR 11-7 compliant)
• Fair lending compliance for credit decisions
• Anti-money laundering controls
• Regulatory reporting capabilities

• HIPAA compliance for PHI handling
• FDA requirements for clinical AI (if applicable)
• Clinical validation documentation
• Patient consent mechanisms

• FedRAMP authorization (if cloud-based)
• Executive Order 14110 requirements
• Agency-specific AI guidance compliance
• Procurement requirements satisfied