Regulatory Crosswalk · AIMSS v1.0

One certification.
Every major regulation.

AIMSS is designed to be sufficient — passing the standard demonstrably satisfies the substantive requirements of the world's most-cited AI regulations. The map below shows where each AIMSS clause aligns with the EU AI Act, NYC Local Law 144, ISO/IEC 42001, and the Colorado AI Act. Use it to scope compliance work, audits, or procurement reviews.

AIMSS clausePillarEU AI ActNYC Local Law 144ISO/IEC 42001Colorado AI Act

AIMSS §4.1

AI inventory & system register

Governance

Article 49 requires registration of high-risk systems in the EU database.

Art. 49

AEDT must be identified and disclosed publicly, but no central register.

Annex A.6 governs the AI system life cycle, including AI system documentation and inventory.

Annex A.6

Deployers must document high-risk systems used; no public register.

AIMSS §4.3

Risk classification & impact assessment

Governance

Risk categories and conformity assessments mandated.

Art. 6, Annex III

Bias audit required, but no broader impact assessment.

Annex A.5 requires an AI system impact assessment process (alongside risk assessment in Clause 6.1).

A.5.2–A.5.4

Annual impact assessment required for high-risk AI.

§6-1-1703

AIMSS §5.1

Independent ethics review

Ethics

Fundamental rights impact assessment required for some deployers.

Not addressed.

Encourages ethics consideration but no independent body required.

Reasonable care duty; no independent ethics body.

AIMSS §5.4

Disclosure to affected persons

Ethics

Article 50 transparency obligations for AI systems interacting with humans.

Art. 50

Candidates must be notified at least 10 business days in advance.

Annex A.8 stakeholder communication required.

Consumer notice required before consequential decision.

§6-1-1704

AIMSS §6.2

Training & inference emissions accounting

Climate

GPAI providers must report energy use of training.

Art. 53(1)(a)

Not addressed.

Environmental impact among AI objectives.

Not addressed.

AIMSS §6.4

Emissions reduction targets

Climate

Not addressed.

Not addressed.

Continual improvement applies if scoped to emissions.

Not addressed.

AIMSS §7.1

Data-worker labour conditions

Labour

Data governance Art. 10 implies labelling quality; no direct labour standards.

Not addressed.

Resource & competence clauses cover staff but not contractors broadly.

Not addressed.

AIMSS §7.3

Red-team psychological safeguards

Labour

Adversarial testing required for systemic-risk GPAI.

Art. 55

Not addressed.

Not addressed.

Not addressed.

AIMSS §8.1

Bias & disparate-impact testing

Society

Art. 10 data and bias requirements for high-risk systems.

Art. 10

Mandatory annual independent bias audit with published summary.

Annex A.7 data quality & bias considerations.

Algorithmic discrimination duty of reasonable care.

§6-1-1702

AIMSS §8.4

Misuse & dual-use assessment

Society

Systemic-risk evaluation for advanced GPAI.

Art. 55

Not addressed.

AI risk assessment may cover misuse.

Not addressed.

AIMSS §9.1

Post-market monitoring & incident reporting

Lifecycle

Articles 72 & 73 mandate post-market monitoring and serious-incident reporting.

Art. 72–73

Annual re-audit obligation.

Clauses 9 & 10 cover performance evaluation and improvement.

Deployers must monitor and report algorithmic discrimination within 90 days.

AIMSS §9.3

Public complaints register

Lifecycle

Right to lodge complaint with market surveillance authority.

Art. 85

Not addressed.

Not addressed.

Consumer right to appeal a consequential decision.

AIMSS §10.1

Continuous integrity programme

Governance

Conformity reassessment after substantial modification.

Art. 43

Annual bias audit obligation only.

PDCA-style continual improvement (Clause 10).

Annual impact assessment review required.

AIMSS §4.2

Documented AI policy & accountable executive

Governance

Quality-management system required for providers of high-risk AI.

Art. 17

Not addressed.

Clauses 5.1–5.3 require leadership commitment, AI policy, and assigned roles.

Risk-management programme required for deployers of high-risk AI.

§6-1-1703(2)

AIMSS §4.4

Third-party & supply-chain AI obligations

Governance

Importer, distributor and downstream-deployer obligations defined.

Art. 23–27

Independent auditor required, but no broader supplier regime.

Annex A.10 covers third-party relationships and customer obligations.

Developers must disclose to deployers all info needed for impact assessments.

§6-1-1702(2)

AIMSS §5.2

Human oversight & meaningful intervention

Ethics

Human oversight measures mandated for high-risk AI.

Art. 14

Not addressed.

Annex A.9 addresses human oversight as a control objective.

Consumer right to human review of consequential decisions.

§6-1-1704(3)

AIMSS §5.3

Explainability of automated decisions

Ethics

Right to explanation of individual decisions for high-risk AI.

Art. 86

Disclosure of data categories and source, not per-decision explanation.

Transparency to users required as a control objective.

Plain-language explanation of the decision must be provided on request.

§6-1-1704(3)(b)

AIMSS §6.1

Water & cooling impact disclosure

Climate

GPAI Code of Practice asks for compute-environment energy reporting; water not specified.

Art. 53

Not addressed.

Environmental impact considered within the AI management system scope.

Not addressed.

AIMSS §6.3

Lifecycle carbon disclosure to buyers

Climate

GPAI providers must document known or estimated energy consumption in technical documentation passed to downstream providers.

Art. 53(1)(a), Annex XI

Not addressed.

Information for interested parties (Annex A.8) can include climate data.

Not addressed.

AIMSS §7.2

Pay-floor & overtime limits for data workers

Labour

Not addressed.

Not addressed.

Not addressed.

Not addressed.

AIMSS §7.4

Workforce displacement notice & re-skilling

Labour

Workers' representatives must be informed before workplace AI deployment.

Art. 26(7)

Candidate notification of AEDT use required.

Stakeholder engagement covers affected staff (Annex A.8).

Not addressed.

AIMSS §8.2

Demographic-data governance for fairness testing

Society

Permitted processing of special-category data to detect and correct bias.

Art. 10(5)

Sex, race/ethnicity categories required for the bias audit.

Data quality and bias controls referenced (Annex A.7).

Impact assessment must describe data used and limitations.

AIMSS §8.3

Accessibility for users with disabilities

Society

Compliance with EU accessibility requirements mandated.

Art. 16(l)

Not addressed.

Interested-party needs include accessibility considerations.

Not addressed.

AIMSS §8.5

Content provenance & synthetic-media labelling

Society

Machine-readable marking of AI-generated and deepfake content.

Art. 50(2)–(4)

Not addressed.

Information to users covers disclosure of AI involvement.

Not addressed.

AIMSS §9.2

Cybersecurity & adversarial robustness

Lifecycle

Accuracy, robustness and cybersecurity requirements for high-risk AI.

Art. 15

Not addressed.

Security controls extended to AI assets (Annex A.7, A.9).

Reasonable-care duty includes safeguarding against discrimination risk.

AIMSS §9.4

Audit trail & technical documentation

Lifecycle

Automatic logs and detailed technical documentation required.

Art. 11–12, Annex IV

Bias audit results must be publicly published and retained.

Documented information requirements throughout the standard (Clause 7.5).

Impact assessments must be retained and available to the Attorney General.

AIMSS §10.2

External assurance & independent re-audit

Governance

Notified-body conformity assessment for many high-risk systems.

Art. 43, Annex VII

Annual independent bias audit by a qualified auditor.

Designed for accredited third-party certification.

Attorney General oversight; no mandatory third-party audit.

✓ Full coverage · ◐ Partial coverage · — Not addressed

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