Cross-Framework Mapping

NIST AI Risk Management Framework (AI RMF 1.0)vsAutomotive SPICE (ASPICE) v4.0 - Process Assessment Model

See exactly how NIST AI Risk Management Framework (AI RMF 1.0) controls map to Automotive SPICE (ASPICE) v4.0 - Process Assessment Model. Pre-computed mappings, identified gaps, and coverage analysis.

23
Controls Mapped
29
Gaps Found
10%
Coverage

According to the TheArtOfService Compliance Knowledge Graph:

NIST AI Risk Management Framework (AI RMF 1.0) maps to Automotive SPICE (ASPICE) v4.0 - Process Assessment Model with 10% coverage across 5 directly mapped controls. Analysis of 52 NIST AI Risk Management Framework (AI RMF 1.0) controls identifies 47 compliance gaps — primarily concentrated in AI RMF Functions.

Source: TheArtOfService Knowledge Graph | 52 controls analysed | 718 frameworks | 332K+ cross-framework mappings

Control Mappings

Showing 20 of 23 mapped controls across 1 domains. Sign up to explore all 332K+ mappings across 718 frameworks.

AI RMF Functions(20 mappings)

AIRMF-GOV-01AI Risk Management Policies7 targets
MLE.1Machine Learning Requirements Analysis
MLE.1Machine Learning Requirements Analysis
MLE.2Machine Learning Architecture
MLE.2Machine Learning Architecture
MLE.3Machine Learning Training
MLE.3Machine Learning Training
SUP.11ML Data Management Support
AIRMF-GOV-02AI Risk Culture5 targets
MLE.1Machine Learning Requirements Analysis
MLE.1Machine Learning Requirements Analysis
MLE.2Machine Learning Architecture
MLE.2Machine Learning Architecture
SUP.11ML Data Management Support
AIRMF-MEA-01AI Performance Metrics4 targets
MLE.1Machine Learning Requirements Analysis
MLE.1Machine Learning Requirements Analysis
MLE.3Machine Learning Training
MLE.3Machine Learning Training
AIRMF-MEA-03AI Transparency and Explainability4 targets
MLE.1Machine Learning Requirements Analysis
MLE.1Machine Learning Requirements Analysis
MLE.2Machine Learning Architecture
MLE.2Machine Learning Architecture

+3 more mappings

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Related Comparisons

Other NIST AI Risk Management Framework (AI RMF 1.0) comparisons

Other Automotive SPICE (ASPICE) v4.0 - Process Assessment Model comparisons

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What are the key differences between NIST AI Risk Management Framework (AI RMF 1.0) and Automotive SPICE (ASPICE) v4.0 - Process Assessment Model?

NIST AI Risk Management Framework (AI RMF 1.0) has 52 controls across its framework, while Automotive SPICE (ASPICE) v4.0 - Process Assessment Model covers 31 controls. Direct mapping analysis identifies 5 overlapping controls (10% coverage). The frameworks diverge most significantly in AI RMF Functions, where 26 NIST AI Risk Management Framework (AI RMF 1.0) controls have no direct Automotive SPICE (ASPICE) v4.0 - Process Assessment Model equivalent.

How many controls map between NIST AI Risk Management Framework (AI RMF 1.0) and Automotive SPICE (ASPICE) v4.0 - Process Assessment Model?

Of 52 total NIST AI Risk Management Framework (AI RMF 1.0) controls, 5 map directly to Automotive SPICE (ASPICE) v4.0 - Process Assessment Model controls — representing 10% coverage. The remaining 47 controls represent compliance gaps requiring additional documentation or compensating controls to satisfy both frameworks simultaneously.

What are the compliance gaps when mapping NIST AI Risk Management Framework (AI RMF 1.0) to Automotive SPICE (ASPICE) v4.0 - Process Assessment Model?

47 NIST AI Risk Management Framework (AI RMF 1.0) controls have no direct equivalent in Automotive SPICE (ASPICE) v4.0 - Process Assessment Model. The highest concentration of gaps is in AI RMF Functions with 26 unmapped controls. These gaps represent areas where additional controls, policies, or documentation must be created to achieve compliance with both frameworks.

Which control domains have the most gaps between NIST AI Risk Management Framework (AI RMF 1.0) and Automotive SPICE (ASPICE) v4.0 - Process Assessment Model?

The domain with the highest gap count is AI RMF Functions (26 gaps). Export the full domain-by-domain gap breakdown via the Professional tier to generate a prioritised remediation roadmap.

This platform provides educational compliance tools, not legal, regulatory, or professional compliance advice. Cross-framework mappings are AI-assisted interpretations and do not reproduce or replace official standards. Framework names and trademarks belong to their respective owners. Consult qualified professionals for your specific compliance requirements. See our Terms of Service.