Cross-Framework Mapping

CDP (formerly Carbon Disclosure Project)vsNIST AI 600-1 Generative AI Profile

See exactly how CDP (formerly Carbon Disclosure Project) controls map to NIST AI 600-1 Generative AI Profile. Pre-computed mappings, identified gaps, and coverage analysis.

34
Controls Mapped
0
Gaps Found
38%
Coverage

According to the TheArtOfService Compliance Knowledge Graph:

CDP (formerly Carbon Disclosure Project) maps to NIST AI 600-1 Generative AI Profile with 38% coverage across 12 directly mapped controls. Analysis of 32 CDP (formerly Carbon Disclosure Project) controls identifies 20 compliance gaps — primarily concentrated in Risk Management.

Source: TheArtOfService Knowledge Graph | 32 controls analysed | 693 frameworks | 819K+ cross-framework mappings

Control Mappings

Showing 20 of 34 mapped controls across 5 domains. Sign up to explore all 819K+ mappings across 693 frameworks.

Climate Change Performance(4 mappings)

CDP-CC-1GHG Emissions Reporting2 targets
NIST-AI600-MEA-4Environmental Impact Measurement
NIST-AI600-RISK-04Environmental Impacts
CDP-CC-2Emissions Reduction Targets2 targets
NIST-AI600-MEA-4Environmental Impact Measurement
NIST-AI600-RISK-04Environmental Impacts

Environmental Performance(8 mappings)

CDP-EP-3Biodiversity Impacts4 targets
AIRMF-MAP-02AI Risk Identification
NIST-AI600-MAP-1GAI Risk Identification
NIST-AI600-MEA-4Environmental Impact Measurement
NIST-AI600-RISK-04Environmental Impacts
CDP-EP-4Plastics4 targets
AIRMF-MAP-02AI Risk Identification
NIST-AI600-MAP-1GAI Risk Identification
NIST-AI600-MEA-4Environmental Impact Measurement
NIST-AI600-RISK-04Environmental Impacts

Governance and Strategy(4 mappings)

CDP-GS-1Board Oversight of Environmental Issues4 targets
AIRMF-MAP-02AI Risk Identification
NIST-AI600-MAP-1GAI Risk Identification
NIST-AI600-MEA-4Environmental Impact Measurement
NIST-AI600-RISK-04Environmental Impacts

Metrics, Targets, and Scoring(2 mappings)

CDP-MT-3Verification and Assurance2 targets
NIST-AI600-MEA-4Environmental Impact Measurement
NIST-AI600-RISK-04Environmental Impacts

Risk Management(2 mappings)

CDP-RM-1Risk Identification Process2 targets
AIRMF-MAP-02AI Risk Identification
AIRMF-MAP-03AI Impact Assessment

+14 more mappings

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Related Comparisons

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What are the key differences between CDP (formerly Carbon Disclosure Project) and NIST AI 600-1 Generative AI Profile?

CDP (formerly Carbon Disclosure Project) has 32 controls across its framework, while NIST AI 600-1 Generative AI Profile covers 43 controls. Direct mapping analysis identifies 12 overlapping controls (38% coverage). The frameworks diverge most significantly in Risk Management, where 10 CDP (formerly Carbon Disclosure Project) controls have no direct NIST AI 600-1 Generative AI Profile equivalent.

How many controls map between CDP (formerly Carbon Disclosure Project) and NIST AI 600-1 Generative AI Profile?

Of 32 total CDP (formerly Carbon Disclosure Project) controls, 12 map directly to NIST AI 600-1 Generative AI Profile controls — representing 38% coverage. The remaining 20 controls represent compliance gaps requiring additional documentation or compensating controls to satisfy both frameworks simultaneously.

What are the compliance gaps when mapping CDP (formerly Carbon Disclosure Project) to NIST AI 600-1 Generative AI Profile?

20 CDP (formerly Carbon Disclosure Project) controls have no direct equivalent in NIST AI 600-1 Generative AI Profile. The highest concentration of gaps is in Risk Management with 10 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 CDP (formerly Carbon Disclosure Project) and NIST AI 600-1 Generative AI Profile?

The domain with the highest gap count is Risk Management (10 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.