AI COMPLIANCE
Navigate the complex landscape of AI-specific regulations and compliance frameworks. From the EU AI Act to GDPR, CCPA, NIST guidance, and industry-specific requirements—understand what applies to your AI systems and how to achieve compliance.
319 Pre-Built Compliance Controls
Access our comprehensive Control Library with expert-designed controls covering all major frameworks. Connect to virtually any compliance framework and implement controls for your AI models with detailed implementation guidance, testing procedures, and evidence requirements.
Major AI Compliance Frameworks
Key regulations and standards governing AI development and deployment worldwide.
| Effective Date | Requirements | Description | |||
|---|---|---|---|---|---|
Algorithmic Accountability Act | United States (Proposed) | MEDIUM | Pending congressional approval |
+3 more | Proposed federal legislation requiring impact assessments for automated decision systems. |
CCPA / CPRA | California, USA | HIGH | CCPA: 2020, CPRA: 2023 |
+3 more | California Consumer Privacy Act and Privacy Rights Act establish consumer data rights including AI transparency. |
EU AI Act | European Union | CRITICAL | Progressive implementation 2024-2027 |
+3 more | The world's first comprehensive AI regulation, establishing a risk-based framework for AI systems deployed in the EU. |
GDPR | European Union | HIGH | In effect since May 2018 |
+3 more | General Data Protection Regulation governs personal data processing, including AI systems that use personal data. |
HIPAA | United States | CRITICAL | In effect since 1996, updated regularly |
+3 more | Health Insurance Portability and Accountability Act governs protected health information (PHI) in AI healthcare applications. |
NIST AI RMF | United States | MEDIUM | Published January 2023 |
+3 more | National Institute of Standards and Technology AI Risk Management Framework providing voluntary guidance. |
Core Compliance Pillars
Fundamental principles that span across all AI compliance frameworks.
Implementation Examples:
- Model cards and documentation
- Explainable AI techniques
- User-facing transparency notices
- Audit trail maintenance
Implementation Examples:
- Bias testing across demographics
- Fair lending compliance
- Equal opportunity analysis
- Disparate impact assessments
Implementation Examples:
- Data minimization practices
- Encryption and access controls
- Privacy impact assessments
- Secure data handling pipelines
Implementation Examples:
- Human-in-the-loop workflows
- Override mechanisms
- Regular human review
- Escalation procedures
How Aegis Oversight Ensures Compliance
Automate compliance across all major frameworks with built-in checks and comprehensive documentation.
Built-in Framework Support
- Pre-configured compliance checks for EU AI Act, GDPR, CCPA, NIST, and HIPAA
- Automated violation tracking with SLA monitoring and escalation
- Risk-based assessment and classification
- Continuous monitoring and alerting
Audit-Ready Documentation
- One-click compliance reports with score trends
- Complete audit trail with timeline visualization
- Evidence collection and remediation tracking
- Export in multiple formats (PDF, CSV, Text)
Comprehensive Control Library
Connect to virtually any compliance framework with our library of 319 expert-designed controls.
What's Included:
- 319 pre-built controls across 9 framework categories
- Detailed implementation steps and testing procedures
- Evidence requirements and regulatory references
- Priority and difficulty ratings for planning
Connect Any Framework:
- Flexible framework configuration for custom regulations
- Industry-specific compliance requirements (finance, healthcare, etc.)
- International and regional regulations worldwide
- Custom internal policies and organizational standards
Browse the full Control Library to view all available controls, implementation guidance, and assign controls to your AI models.
Frequently Asked Questions
Common questions about AI compliance and how Aegis Oversight helps.
AI compliance is the practice of ensuring artificial intelligence systems meet legal, regulatory, and ethical requirements across their lifecycle. It spans data privacy (GDPR, CCPA), sector-specific rules (HIPAA), risk frameworks (NIST AI RMF), and AI-specific regulation (EU AI Act), covering transparency, fairness, accountability, and human oversight.
AI systems are subject to a layered set of laws: the EU AI Act for systems used in the EU, GDPR and CCPA/CPRA for personal data processing, HIPAA for healthcare PHI, NIST AI RMF as the operational baseline (mandatory for US federal agencies), plus sector-specific rules in finance, employment, and critical infrastructure. The applicable set depends on where you operate and what data your AI touches.
The EU AI Act (Regulation 2024/1689) is the first comprehensive AI law, using a risk-based approach with four tiers. It entered into force in August 2024, prohibited practices apply from February 2025, general-purpose AI obligations from August 2025, and full high-risk system requirements from August 2026. Penalties reach up to €35 million or 7% of global annual turnover.
AI fairness is ensured through bias and fairness testing using demographic parity, equal opportunity, equalized odds, and disparate impact metrics across protected characteristics. Organizations should test before deployment, monitor in production, document results, and apply mitigation techniques when bias is detected — a requirement under GDPR Article 22 and increasingly under CCPA ADMT rules.
A DPIA is a structured assessment required under GDPR Article 35 for high-risk personal data processing, which includes most AI profiling and automated decision-making. It documents the processing purposes, necessity, proportionality, risks to individuals, and mitigations. Aegis Oversight automates DPIA generation from your model inventory and data sources.