Crosswalk pair

EU AI Act and NIST AI Risk Management Framework, control by control

3 canonical controls in Keel’s library satisfy clauses of both EU AI Act and NIST AI Risk Management Framework. Implement each once, attach the evidence once, and it counts toward each standard. The overlap is the work you don’t repeat.

The overlap

What the two libraries have in common

Every figure here counts canonical controls in Keel’s library, not clauses of either standard. Each standard’s own authored count is on its framework page.

3

Controls that satisfy both

Canonical controls that crosswalk to at least one clause of each.

8

In Keel’s library for EU AI Act

38% of them also map to NIST AI Risk Management Framework.

8

In Keel’s library for NIST AI Risk Management Framework

38% of them also map to EU AI Act.

6

Evidence artifacts expected

Across the shared controls, from Keel’s evidence guidance. Gathered once.

  • EU AI Act 2024 38%

    3 controls of 8 in Keel’s library for EU AI Act also map to NIST AI Risk Management Framework.

  • NIST AI Risk Management Framework 1.0 38%

    3 controls of 8 in Keel’s library for NIST AI Risk Management Framework also map to EU AI Act.

The mapping

Controls that satisfy both

Each row is one control in Keel’s library and the clauses it answers on each side. Do the work once; both columns are then evidenced by the same artifacts.

EU AI Act and NIST AI Risk Management Framework controls that satisfy both, with the clauses each maps to
Canonical control EU AI Act clauses NIST AI Risk Management Framework clauses
AI risk management process A process to identify, analyze, prioritize, and treat the risks an AI system can pose, tracked over its lifecycle. HREQ-1 MEASURE-1.1, MANAGE-1.2, MANAGE-1.3
AI verification, validation & robustness Testing that an AI system meets its requirements and performs with appropriate accuracy, robustness, and security before and during use. HREQ-7 MEASURE-2.3, MEASURE-2.4, MEASURE-2.5, MEASURE-2.7
AI monitoring & malfunction reporting Ongoing monitoring of AI systems in operation, with a process to detect, communicate, and report malfunctions and serious incidents. HOBL-5, HOBL-6, HOBL-7 MANAGE-4.1, MANAGE-4.3

Beyond the pair

Where else this work counts

A framework is lit when a shared control above also maps to it. Unlit means none of them do — an absence, not a judgment about that standard.

Also reached by these 3 controls

  • AI Governance Essentials
  • Amazon Appstore Child-Directed Apps
  • Apple App Store Kids Category
  • CIS Critical Security Controls
  • COPPA
  • ESG Essentials
  • GDPR
  • Google Play Families
  • HIPAA
  • ISO 9001
  • ISO/IEC 27001
  • ISO/IEC 42001
  • NIST Cybersecurity Framework
  • NIST SP 800-171
  • NIST SP 800-53
  • PCI DSS
  • SOC 2
  • SOX (Sarbanes-Oxley) Section 404
  • US Employment Law - Federal Baseline

The thesis

Why this is one project, not two

On a crosswalk-native model, NIST AI Risk Management Framework mostly lights up controls you already built for EU AI Act. You’re not re-uploading the same screenshot for a second audit. You apply the framework and see the genuine delta worth working. That’s the whole idea behind collect once, comply everywhere.

Next step

Add NIST AI Risk Management Framework to the work you already did

Apply both frameworks in one workspace and see the overlap measured against the controls you already hold.