Learning hubCase studies across regulated industries
Four detailed, step-by-step scenarios showing how organizations put AI governance principles into practice — from clinical AI to claims handling.
Health system
Healthcare — Meridian Health System
Governing clinical AI, vendor contracts, fairness, and monitoring across a hospital network — with ten implementation steps and scenario branch analysis.
- AI committee chartering and clinical risk tiering
- Vendor model-card requirements and audit rights
- Continuous fairness and drift monitoring
Logistics & procurement
Supply Chain — GlobalTech Logistics
Tiered risk, differential privacy, and continuous audit across procurement, freight forecasting, and route-planning copilots.
- Three-tier AI risk framework
- Differential privacy for supplier data
- 5-step continuous audit pipeline
Regional retail bank
Retail Banking — Northmark Bank
Extending SR 11-7 model risk management to cover ML credit decisioning, real-time fraud, and a customer-service GenAI copilot.
- SHAP-based Regulation B adverse-action reasons
- Fair-lending testing with BISG proxies
- NPI-redaction gateway for GenAI
Property & casualty insurer
Insurance Claims — Cedarline Insurance
FNOL triage, computer-vision auto-damage estimation, and fraud detection under one governance council aligned to the NAIC AI Model Bulletin.
- Adversarial-image screening on photo intake
- Human-review floor on all SIU referrals
- Explainability written into the claim file