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Generative · AI Governance & Standards · reviewed 2026-04

NIST AI RMF Maturity Model

Framework for assessing AI risk maturity based on NIST standards.

Visit arxiv.org/abs/2401.15229
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What it does

A framework for assessing organisational maturity in AI risk management, based on NIST's AI Risk Management Framework. Provides a structured approach to measuring and improving AI governance capabilities across multiple dimensions.

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Security relevance

Maps AI risk management capabilities to maturity levels, helping organisations understand where they stand and what to prioritise. Useful for building a roadmap from ad-hoc AI usage to structured AI governance, with clear milestones along the way.

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When to use it

Use when building an AI governance roadmap or assessing current maturity for leadership reporting. Requires mapping to your organisation's specific processes and capabilities — not just reading the framework but applying it to your context.

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OWASP coverage

Risks addressed — mapped to both OWASP Top 10 standards. 0 in LLM, 0 in Agentic.

LLM Top 10 · 2025 · 0/10 covered
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Agentic Top 10 · 2026 · 0/10 covered
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The raw record

What Yuntona stores. Single source of truth — fork it on GitHub.

name: NIST AI RMF Maturity Model
slug: nist-ai-rmf-maturity-model
type: Generative
category: AI Governance & Standards
url: https://arxiv.org/abs/2401.15229

reviewed:   2026-04
added:      2026-04
updated:    2026-04

risks:
  llm:  []
  asi:  []

complexity:    Guided Setup
pricing:       —
audience:      Blue Team
lifecycle:     [govern]

tags: [Framework, NIST, Risk]