Conditional Approval of a Vendor GenAI Pilot in Claims

The material gaps are not independent; together they prevent an informed approval.

• No model inventory entry means the committee cannot tier the use or attach an accountable owner, so the high-PHI nature is not formally recorded.
• No DPIA means the insurer has not mapped PHI flows, minimum-necessary use, retention, or the vendor's prompt-logging and training practices.
• No vendor risk tier means SOC 2 Type II is being treated as sufficient, although it addresses controls, not model training data, subprocessors, or AI-specific risks.
• The 20% discount for opting out of prompt logging creates a financial incentive to accept weaker confidentiality.

The interaction is the key: PHI in claim narratives plus possible prompt logging plus undisclosed training data converts a productivity pilot into a potential privacy and regulatory event. The committee should not debate model accuracy first; it should require a complete inventory entry, a DPIA with the vendor's data flows, an AI risk questionnaire, and a draft data-processing agreement/BAA before evaluating the pilot. Sequencing should be inventory and tier, then DPIA, then contract and security review, then limited pilot design. Without that order, conditions would be unenforceable.

Conditional approval is better than rejection because the use case has plausible value and the risks can be bounded, but not approval as proposed. Conditions:

• Restrict the pilot to 50 adjusters and to de-identified or synthetic claim narratives until the DPIA and BAA are executed.
• Prohibit vendor training on insurer prompts and require no prompt logging beyond 30 days, with audit rights. Accept the 20% cost increase rather than trade PHI confidentiality for a discount.
• Require human review of every AI-drafted denial letter, no auto-send, and a documented override reason.
• Add a kill switch and a named product owner.
• Complete the model inventory entry with a high-risk tier, DPIA sign-off, and vendor risk assessment before go-live.
• Define pilot success metrics and stop criteria in advance.

If the vendor refuses to disclose training-data sources or to contractually exclude PHI from training, the pilot should not proceed even with human review, because review does not cure unauthorized use. The committee should record the rationale and time-bound the approval to 90 days.

Report weekly to the AI governance committee during the pilot, monthly after, and quarterly to the board risk committee. Metrics should cover:

• Privacy and security: number of PHI prompts, vendor logging exceptions, retention violations, access reviews, incidents.
• Quality: adjuster override rate by denial reason, factual error rate in sampled letters, hallucination rate, escalation rate.
• Fairness and consistency: approval and denial patterns by claimant segment where legally permissible, with legal review.
• Operations: latency, availability, adoption, cost per draft.
• Vendor: SLA breaches, subprocessor changes, model version changes.

Set thresholds in advance. Any confirmed PHI exposure or vendor training on insurer data triggers immediate suspension. An override rate above 25% or error rate above 5% triggers model review. Two consecutive weeks of threshold breach escalates to the CISO and CCO. The committee should see raw incident counts, not only vendor dashboards, and should require a close-out report with an expansion recommendation.