AI Risk Management
The systematic process of identifying, assessing, mitigating, and monitoring risks associated with AI systems. NIST's AI Risk Management Framework provides a comprehensive approach.
Why It Matters
AI risk management is becoming a regulatory requirement. NIST AI RMF and the EU AI Act both mandate structured risk management for AI systems.
Example
A company categorizing AI risks across dimensions: bias risk (medium), security risk (high), privacy risk (high), reliability risk (medium) — with mitigation plans for each.
Think of it like...
Like enterprise risk management applied specifically to AI — identifying what could go wrong, how likely it is, and what to do about it.
Related Terms
Risk Assessment
The systematic process of identifying, analyzing, and evaluating potential risks associated with an AI system. Risk assessment considers both the likelihood and impact of potential harms.
AI Governance
The frameworks, policies, processes, and organizational structures that guide the responsible development, deployment, and monitoring of AI systems within organizations and across society.
AI Safety
The research field focused on ensuring AI systems operate reliably, predictably, and without causing unintended harm. It spans from technical robustness to long-term existential risk concerns.
Compliance
The process of ensuring AI systems meet regulatory requirements, industry standards, and organizational policies. AI compliance is becoming increasingly complex as regulations proliferate.
EU AI Act
The European Union's comprehensive regulatory framework for artificial intelligence, establishing rules based on risk levels. It categorizes AI systems from minimal to unacceptable risk with corresponding compliance requirements.