Get audit-ready for NIST AI RMF
NIST AI RMF 1.0 · AI Risk Management Framework
NIST framework for managing risks associated with AI systems throughout their lifecycle, organized around four core functions: Govern, Map, Measure, and Manage.
NIST AI RMFWhat is NIST AI RMF?
NIST framework for managing risks associated with AI systems throughout their lifecycle, organized around four core functions: Govern, Map, Measure, and Manage.
Who it applies to
Organisations designing, deploying or procuring AI systems. Voluntary, and frequently the reference point when a customer asks how AI risk is managed but does not require ISO 42001.
How the standard is organised
Organised around four functions - govern, map, measure and manage - applied across the AI lifecycle rather than as a control checklist.
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NIST AI RMF on the Bitkosh platform
The 72 NIST AI RMF controls sit in one workspace with gap assessment, evidence collection and your readiness score, and shared controls count towards the equivalent requirement in the other 47 ready frameworks at the same time — so a second framework costs a fraction of the first.
How the platform worksSample controls
Six controls from the platform's control library, chosen because they are the most specific to this framework.
- GOVERN 4.1Safety-first mindset
Put policies and practices in place that foster critical thinking and a safety-first mindset across the AI lifecycle.
GOVERN 4 — Risk-aware organisational culture - MANAGE 2.2Sustaining deployed value
Apply mechanisms to sustain the value of deployed AI systems.
MANAGE 2 — Benefit maximisation and impact minimisation - MANAGE 2.4Supersede or deactivate
Assign responsibilities and apply mechanisms to supersede, disengage or deactivate systems whose performance is inconsistent with intended use.
MANAGE 2 — Benefit maximisation and impact minimisation - MAP 1.2Interdisciplinary AI actors
Ensure the actors establishing context reflect diversity and broad expertise, document their participation and prioritise interdisciplinary collaboration.
MAP 1 — Context is established - MAP 5.1Impact likelihood and magnitude
Identify and document likelihood and magnitude of beneficial and harmful impacts using expected use, past uses, incident reports and external feedback.
MAP 5 — Impact characterization - GOVERN 1.7Safe decommissioning
Define processes for decommissioning and phasing out AI systems safely without raising risk or reducing trustworthiness.
GOVERN 1 — Policies, processes and practices for AI risk
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Frequently Asked Questions
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See how the Bitkosh Readiness Platform gets you audit-ready for NIST AI RMF — and the other 47 ready frameworks — from a single control library.