This workshop covered the structure and purpose of the NIST AI Risk Management Framework (AI RMF 1.0) and its application across the AI system lifecycle. Topics: AI risk and trustworthiness characteristics; the AI RMF Core (Govern, Map, Measure, Manage); AI governance, accountability, and risk tolerance; mapping AI risk across context, actors, and lifecycle; measuring AI risk with testing, evaluation, verification, and validation (TEVV); risk prioritization, response planning, residual risk, and continuous monitoring; developing AI RMF Current and Target Profiles; and lifecycle integration, human-AI oversight, and third-party and supply chain risk.