AI-GRACE: a use-case operationalization framework for agentic AI (arXiv:2609.21192v1)
AI-GRACE is a proposed use-case operationalization framework that connects organizational governance to technical implementation for agentic AI. The paper defines objectives and obligations, assesses risks across seven domains, and derives assurance requirements, runtime controls, and evidence needs, introducing constructs such as an Agent Operating Envelope and Risk-Aligned Independence Levels (RAIL); a fictional retail-banking example illustrates the method and the authors note empirical evaluation is required to confirm deployment benefits.