01
Govern
Establish AI governance structures, policies, roles, and accountability for AI risk across the organization.
Framework Overview
AI risk management for trustworthy systems
The NIST AI Risk Management Framework helps organizations manage risks associated with AI systems across the lifecycle—govern, map, measure, and manage. It is increasingly referenced in procurement, regulation, and responsible AI programs.
Who it's for: Teams shipping AI features, using LLMs in production, or responding to customer and regulator questions about AI governance.
How NIST AI RMF breaks down across the program lifecycle.
01
Establish AI governance structures, policies, roles, and accountability for AI risk across the organization.
02
Contextualize AI systems, identify stakeholders, and map risks and benefits across the AI lifecycle.
03
Define metrics, testing, and evaluation approaches for model performance, bias, safety, and reliability.
04
Prioritize and respond to identified risks—mitigation, monitoring, incident response, and decommissioning.
05
Maintain model cards, use-case inventories, and evidence that supports customer and auditor inquiries.
06
Align AI governance with existing security, privacy, and compliance programs rather than a siloed initiative.
A visual overview of how we typically structure a NIST AI RMF engagement—from discovery through audit-ready operations.
It is voluntary in the US, but customers, partners, and emerging regulations increasingly expect structured AI risk management aligned to NIST guidance.
Yes. You remain responsible for how AI is used in your product—vendor due diligence, data handling, monitoring, and user-facing risk disclosures still apply.
ISO 42001 is a certifiable AI management system standard. NIST AI RMF provides flexible functions and categories that map well to ISO 42001 control themes.
Book a free scoping call—we'll map your compliance goals, recommend the right engagement tier, and outline a clear path forward.