NIST AI Risk Management Framework Playbook
Summary
NIST has published the AI Risk Management Framework Playbook as a companion resource to the AI RMF Core (Tables 1–4 in AI RMF 1.0). The Playbook provides suggested actions organized under the four AI RMF functions—Govern, Map, Measure, and Manage—and is explicitly voluntary, allowing organizations to adopt as many or as few suggestions as apply to their use case. The resource is described as a living document that will evolve approximately twice per year as AI technology advances, with community feedback encouraged via AIframework@nist.gov.
“Playbook suggestions are voluntary. Organizations may utilize this information by borrowing as many – or as few – suggestions as apply to their industry use case or interests.”
About this source
NIST AI RMF is a voluntary framework for managing risks from AI systems, developed by the US National Institute of Standards and Technology. It structures AI risk management around four functions: govern, map, measure, manage. This feed tracks every public update: profile releases for specific domains (generative AI, critical infrastructure), playbook updates, concept notes, and the engagement calendar for working group meetings. Around 7 major publications a year. AI RMF has become the de facto US AI standard. Federal contracts and state laws increasingly reference it. Watch this if you advise on AI governance, run a model risk function, manage generative AI deployments, or write AI policy that cites a recognized framework.
What changed
The NIST AI RMF Playbook has been published as an accompanying resource to the AI Risk Management Framework Core. It maps suggested actions to each sub-category within the four AI RMF functions—Govern, Map, Measure, and Manage—providing organizations with practical guidance for achieving the framework's outcomes. The Playbook explicitly states it is neither a checklist nor a comprehensive step-by-step process, and its suggestions are entirely voluntary. Organizations across sectors may selectively adopt suggestions relevant to their industry use case or operational interests. The Playbook is positioned as a living resource subject to periodic updates, with community feedback welcomed through NIST's designated contact point.
Organizations seeking to implement AI risk management practices should note that the Playbook offers suggested actions only—there are no mandatory requirements or compliance obligations imposed by this resource. Organizations in sectors such as technology, healthcare, government, and manufacturing that develop or deploy AI systems may find value in reviewing the Govern function guidance, particularly for governance structures and accountability mechanisms, as well as the Map function for risk identification workflows. Since the resource is voluntary and iterative, organizations should monitor for periodic updates released approximately twice per year.
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Mar 25, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
NIST AI RMF Playbook
The Playbook provides suggested actions for achieving the outcomes laid out in the AI Risk Management Framework (AI RMF) Core (Tables 1
– 4 in AI RMF 1.0). Suggestions are aligned to each sub-category within the four AI RMF functions (Govern,
Map, Measure, Manage).
The Playbook is neither a checklist nor set of steps to be followed in its entirety.
Playbook suggestions are voluntary. Organizations may utilize this information by borrowing as many – or as few –
suggestions as apply to their industry use case or interests.
Download the NIST AI RMF Playbook
Explore the Playbook
Community feedback
The playbook is a living resource and is expected to evolve as AI technology advances — Individuals are
encouraged to provide feedback about the content of the Playbook by emailing AIframework@nist.gov. Playbook updates will be released
approximately twice per year.
Aspects related to the presentation and delivery of Playbook suggestions are under development. Future online
versions may include options for filtering or tailoring information to user preferences and requirements.
See the page previously known as "Terms" in the AI RMF Appendix A: 📚Descriptions
of AI Actor Tasks
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