AI Compliance
AI compliance is the practice of ensuring artificial-intelligence systems meet applicable legal, regulatory, and ethical requirements throughout their lifecycle.
AI compliance covers the controls, documentation, and governance needed to demonstrate that an AI system is developed and operated responsibly. It spans risk classification, data governance, transparency, human oversight, and ongoing monitoring of model behavior.
The regulatory landscape for AI is expanding quickly. Frameworks such as the EU AI Act impose obligations based on a system's risk level, while voluntary frameworks like the NIST AI Risk Management Framework provide structured guidance for identifying and mitigating AI risks.
In practice, AI compliance combines traditional security and privacy controls with AI-specific requirements: documenting training data provenance, evaluating models for bias, maintaining audit trails of decisions, and ensuring meaningful human review of high-impact outcomes.
Related terms
- EU AI ActThe EU AI Act is the European Union's regulation for artificial intelligence, applying tiered obligations to AI systems according to the level of risk they pose.
- NIST AI RMFThe NIST AI Risk Management Framework is a voluntary US framework that helps organizations identify, assess, and manage risks associated with AI systems.
- GRCGRC stands for Governance, Risk, and Compliance — an integrated approach to aligning an organization's strategy, risk management, and adherence to regulations and standards.
- Continuous ComplianceContinuous compliance is the practice of monitoring controls and collecting evidence on an ongoing basis, so an organization remains audit-ready at all times rather than only before an audit.