This guide shows how to quickly assess and manage AI system risk across inherent and residual scores, highlighting the highest-risk systems and why they’re risky. It explains how controls and governance reduce residual risk, how to read system-level details (use cases, data, harm potential, controls %, last reviewed), and how to adjust ratings with required rationale. It also covers the change history so you can track who changed what and when.