AI Compliance
Definition
Meeting regulatory and industry requirements for AI systems. AI compliance covers data protection (GDPR, CCPA), industry standards (SOC 2, HIPAA, ISO 27001), AI-specific regulations (EU AI Act, NIST AI RMF), and audit requirements (explainability, traceability, accountability). Technical AI compliance requires mechanisms that produce evidence — not just policies that claim compliance.
Why It Matters
Regulators are increasingly requiring AI systems to be auditable, explainable, and governed. The EU AI Act mandates risk management, human oversight, and technical documentation for high-risk AI systems. Organizations deploying AI agents in regulated industries need evidence of governance — audit trails, access logs, and enforcement records.
How Exogram Addresses This
Exogram produces the compliance evidence that regulators require: immutable audit trails, cryptographically chained event logs, PII scrubbing before storage, hard deletion (GDPR right to erasure), and exportable records of every evaluation (pass or block). Compliance as infrastructure, not as documentation.
Related Terms
Key Takeaways
- → Compliance requires evidence, not just policies
- → Immutable audit trails satisfy SOC 2, GDPR, and EU AI Act requirements
- → PII air gap + hard deletion = GDPR-compliant AI governance
Comparison
| Regulation | Key Requirement | Exogram Coverage |
|---|---|---|
| EU AI Act | Risk management & transparency | Full audit trail + deterministic enforcement |
| GDPR | Data protection & erasure | PII air gap + hard deletion |
| SOC 2 | Security controls & monitoring | Cryptographic event chain + policy enforcement |
| HIPAA | PHI protection | PII scrubbing + namespace isolation |
| NIST AI RMF | Risk management framework | Governance + monitoring + audit |