Risk teams structure AI controls using NIST AI RMF functions for a courts chatbot. Which framework application is this?

The NIST AI Risk Management Framework organizes AI risk work through functions commonly summarized as Govern, Map, Measure, and Manage, helping teams structure controls across the AI lifecycle.

Applying those functions to a municipal courts chatbot is the correct framework application: courts AI touches liberty-adjacent or highly sensitive civic processes, so risk teams should map context, measure trustworthiness, manage risks, and govern roles—not treat the bot as informal Q&A. NIST AI RMF provides a spine for control design without replacing local court rules.

Applying NIST CSF 2.0 functions to structure controls for a municipal courts chatbot fails by concept: those are cybersecurity functions, not the AI RMF's Govern, Map, Measure, and Manage functions for AI risk. Applying NIST AI RMF functions to authorize controls for a municipal courts chatbot fails on purpose: the AI RMF structures and manages AI risk through its functions, it does not grant system authorization. Applying NIST AI RMF clauses to structure controls for a municipal courts chatbot fails on terminology: the AI RMF is organized into functions like Govern, Map, Measure, and Manage, not clauses.

Exam caveat: NIST AI RMF application means structuring and mapping controls to its functions—not using NIST CSF 2.0 functions, authorizing controls with AI RMF functions, or mislabeling AI RMF functions as clauses.

Operational check: produce a RMF-style control map for the courts chatbot covering governance owners, context mapping, measurement metrics, and management playbooks before wider resident use.