Risk Identification
Identify foreseeable harms, affected parties, operational dependencies, and conditions that could make an AI system unsafe or inadmissible.
TA-14 AI Governance Library
AI Risk Management
Explore the governance processes used to identify, evaluate, control, monitor, and preserve evidence of AI-related risk.
Risk Analysis
Evaluate likelihood, severity, exposure, uncertainty, and the evidence supporting each risk determination.
Risk Treatment
Define controls, restrictions, human review, escalation paths, and execution boundaries for identified risks.
Residual Risk
Preserve what remains unresolved after controls are applied and determine whether execution should be allowed, held, denied, or escalated.
Risk Monitoring
Track drift, incidents, control failures, environmental changes, and new evidence throughout the AI system lifecycle.
Risk Evidence
Bind risk conclusions to attributable records, governing authority, review history, and preserved outcomes.