The exposure is in your book. The data is not.
EHR vendors have not published hallucination rate, error type, severity, or risk disclosure for the summary and scribe features driving loss development on your insured providers. You cannot underwrite what the vendor will not measure. Idem Labs gives MPL carriers portfolio-level and matter-level evidence on the AI deployed across the book.
Loss development is being driven by an exposure category that is not yet in the underwriting questionnaire.
By the end of 2025, roughly half of US non-federal acute care hospitals were using EHR-integrated generative AI in clinical care. Few carriers currently track which insured providers have which AI features turned on, at what version, in which clinical workflows, with what governance. The Coalition for Health AI, the Joint Commission, and ONC's HTI-1 rule have named the metrics that matter. Few insured hospitals can produce them on demand.
In May 2026, Ontario's Auditor General found inaccuracies in all 20 AI scribes approved for clinical use in the province. Twelve captured the wrong drug. Seventeen missed important mental-health details. That pattern is now in the legal medical record of the insured population whose claims your book will adjudicate over the next renewal cycle.
Two engagement types built for the carrier seat.
A structured read of AI exposure across a sample of insured hospitals: which features are live, vendor disclosure quality, governance posture, HTI-1 compliance, contract and indemnification structure, audit-trail integrity. Output is structured for direct use as schedule-rating-modifier input, risk-class assignment, or renewal pricing review.
The same scope as the defense-counsel engagement, applied to specific claims involving AI-generated content. Used for claims handling, reserve setting, and reinsurance audit. Run under written conflict checks tied to the specific matter.
Who it is for
Chief Underwriting Officers, Chief Risk Officers, Chief Actuaries, and Claims VPs at MPL carriers writing physician groups, hospitals, and health systems with material AI exposure. Reinsurers requesting structured AI risk documentation from cedents.
Read the evidence.
Then let's talk.
The June 2026 white paper documents what EHR-native AI features are doing in the medical record and what your organization is on the hook for.