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Compliance profile
WFM Assistant
high-riskL3Regulated-gradeHandles accruals, balances, and time-off requests, including transactional writes. · production · risk owner P. Weasley · next review 2027-06-24
Risk classification
proposed from registry metadata; a compliance officer approves and signsProposed
Registry metadata: transactional writes · approves time-off requests
Annex III 4(b) — decisions affecting terms of the work relationship
Approved — M. McGonagall (AI Governance Officer) · 2026-06-24
Unambiguous: the agent takes actions that grant or refuse leave. Affirmed at annual review.
Readiness
applicable controls with current evidenceEU AI Act13 of 14· 1 gap
NIST AI RMF6 of 7· 1 gap
ISO 420015 of 7· 2 gaps
SOC 24 of 4
US emp. law1 of 2· 1 gap
Internal5 of 5
EU AI Actregulation
Regulation (EU) 2024/1689Art. 6(3)–(4) + Annex III 4(b)
Documented risk classification
met
Art. 9(1)–(2)
Risk management system
met
Art. 9(6)–(8)
Testing against predefined metrics
met
Art. 10(2)–(3)
Data governance and bias examination
Bias examination incomplete: part-time cohort flagged refused-at-2.3× on equivalent balances — no fairness suite bound yet. The fairness build (§67) closes this.
gap
Art. 10(5)
Special-category data safeguards
met
Art. 11 + Annex IV
Technical documentation
met
Art. 12(1)–(2)
Automatic record-keeping
met
Art. 13(1)–(3)
Transparency to deployers
met
Art. 14(1)–(4)
Human oversight
met
Art. 15(1)–(3)
Accuracy, declared and maintainedNM
met
Art. 15(4)
Robustness and fail-safetyAD
met
Art. 15(5)
Cybersecurity incl. AI-specific attacksAD
met
Art. 72
Post-market monitoringDR
met
Art. 73
Serious-incident reporting
met
NIST AI RMFvoluntary framework
NIST AI 100-1 · GenAI Profile AI 600-1MEASURE 2.3
Performance under deployment conditions
met
MEASURE 2.4
Production behaviour monitoredDR
met
MEASURE 2.5
Valid and reliableNM
met
MEASURE 2.6
Safety evaluated regularlySF
met
MEASURE 2.9
Model output explained and validated
met
MEASURE 2.11
Fairness and bias evaluatedFR
Time-off approval reduces to a decision label — cohort comparison is required and not yet bound. Fairlearn suite scoped; closes with the §67 fairness build.
gap
MANAGE 4.1
Post-deployment monitoring plan
met
ISO/IEC 42001certifiable standard
ISO/IEC 42001:2023 (AIMS)A.5.2
AI system impact assessment process
met
A.5.4
Impact on individuals and groupsFR
Group-impact assessment incomplete: the part-time cohort disparity is exactly what A.5.4 asks about.
gap
A.6.2.4
AI system verification and validation
met
A.6.2.6
Operation and monitoringDR
met
A.6.2.8
Recording of event logs
met
A.7.4
Quality of data for AI systems
Drift acknowledged and previewed; auto-refresh lands with the substrate adoption.
partial
A.7.5
Data provenance
met
SOC 2 Type IIauditor attestation
AICPA 2017 TSC (2022 points of focus)PI1.3
Processing per specification
met
PI1.4
Output completeness and delivery
met
CC7.2
Anomaly monitoring
met
CC8.1
Change management
met
US employment-AI lawstate & local law
NYC Local Law 144 · Illinois HB 3773 (in force 2026-01-01)NYC LL144 §20-871(b)
Annual independent bias auditFR
Time-off approval isn't hiring/promotion screening — outside LL144's AEDT definition. HB 3773 covers it instead.
n/a
IL HB 3773 (775 ILCS 5)
No discriminatory effect on terms of employmentFR
Discharge/discipline/terms standard applies to time-off decisions. The 2.3× part-time refusal disparity is an open disparate-impact exposure until the cohort eval lands and the gap closes.
gap
IL HB 3773 — notice
Employees notified when AI touches their terms
met
UKG AI Quality Policyinternal policy
UKG AI Quality Policy v2.1AIQ-1
Regulated numbers never judged by an LLMNM
met
AIQ-2
Judges gate only while calibrated
met
AIQ-3
Overrides attributed, justified, time-boxed
met
AIQ-4
Production data enters test data scrubbedSF
met
AIQ-5
Dataset composition pinned and revalidated
met