NIST AI RMF Cookbook: Operational Templates and Schemas for AI Governance Implementation

Description The NIST AI RMF Cookbook provides practical, framework-aligned infrastructure for implementing the NIST AI Risk Management Framework (AI RMF 1.0). While the AI RMF establishes what organizations should consider when managing AI risks, this resource addresses how to operationalize those principles through ready-to-use policy templates, structured documentation schemas, and regulatory crosswalks. This release (v0.1.0-alpha) includes: AI Acceptable Use Policy template with customization guidance YAML schemas for model cards, data cards, risk assessments, control mappings, and evaluation plans Framework crosswalks mapping NIST AI RMF to ISO/IEC 42001, ISO/IEC 23894, NIST SP 800-53 Rev. 5, and EU AI Act requirements Implementation guidance for GRC teams, ML engineers, and compliance officers Problem addressed: Organizations face increasing pressure to demonstrate AI governance maturity, but few free, production-ready resources exist to bridge the gap between abstract frameworks and operational compliance. This cookbook synthesizes AI governance best practices into reusable artifacts designed for organizational adoption. Intended audience: Governance, Risk, and Compliance (GRC) professionals, AI/ML engineering teams, information security officers, and policy teams building or maturing AI risk management programs. Status: Foundational release establishing core templates and schema definitions. Future releases will include validation tooling, OSCAL export capabilities, and additional policy templates.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-12
DOI
https://doi.org/10.5281/zenodo.17332823
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

NIST AI RMF Cookbook: Operational Templates and Schemas for AI Governance Implementation

Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

NIST AI RMF Cookbook: Operational Templates and Schemas for AI Governance Implementation

article en

Abstract

Description The NIST AI RMF Cookbook provides practical, framework-aligned infrastructure for implementing the NIST AI Risk Management Framework (AI RMF 1.0). While the AI RMF establishes what organizations should consider when managing AI risks, this resource addresses how to operationalize those principles through ready-to-use policy templates, structured documentation schemas, and regulatory crosswalks. This release (v0.1.0-alpha) includes: AI Acceptable Use Policy template with customization guidance YAML schemas for model cards, data cards, risk assessments, control mappings, and evaluation plans Framework crosswalks mapping NIST AI RMF to ISO/IEC 42001, ISO/IEC 23894, NIST SP 800-53 Rev. 5, and EU AI Act requirements Implementation guidance for GRC teams, ML engineers, and compliance officers Problem addressed: Organizations face increasing pressure to demonstrate AI governance maturity, but few free, production-ready resources exist to bridge the gap between abstract frameworks and operational compliance. This cookbook synthesizes AI governance best practices into reusable artifacts designed for organizational adoption. Intended audience: Governance, Risk, and Compliance (GRC) professionals, AI/ML engineering teams, information security officers, and policy teams building or maturing AI risk management programs. Status: Foundational release establishing core templates and schema definitions. Future releases will include validation tooling, OSCAL export capabilities, and additional policy templates.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 44%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.