AI-Powered Medical Summarization is a Commodity: Work Comp Specific Medical Insights are the Competitive Advantage

“Medical summarization” is a top priority for many claims teams. But most tools are not built specifically for a line of business, and what actually drives results is the line-of-business-specific insights.

EvolutionIQ

September 4, 2025

In Brief

“Medical summarization” is a top priority for many claims teams. But most tools are not built specifically for a line of business, and what actually drives results is the line-of-business-specific insights. These are the details that tell a Workers’ Comp adjuster whether a new impairment rating changes reserves, or warns an Auto Liability desk that a demand package just doubled the exposure. Generic LLM outputs? Tools that say they work equally well across any carrier line of business? Cute demo; zero operational lift.

Why “Just Summarize the Chart” Fails to Deliver Value

Inconsistent output = governance nightmare.
Feed the same 200-page file into a vanilla LLM ten times and you’ll get ten different takeaways which is exactly the opposite of the reproducibility regulators expect.
Signal-to-noise ratio is still awful.
Experienced adjusters care about impairment ratings, causation red flags, RTW dates, not every lab result since 2014. Generic models don’t know what moves a claim vs. whatjust clogs a PDF
“One size” ignores wildly different LOB realities.
Workers’ Comp = statutory timelines & steady drip of medical updates. Auto Liability = litigation, massive demand packages, negotiation theatrics. Treat them the same and you’re playing water polo with a chess clock.

Anatomy of a LOB-Ready Medical Insight Engine

What It Must Do (Workers’ Comp Example)	Why Executives Should Care
Instant compensability cues (pre-existing conditions, conflicting provider opinions)	Cuts investigation time & indemnity drift.
Live change detection on every new record drop	Prevents missed treatment escalations and reserve surprises.
Return-to-Work trajectory tracking (restrictions, RTW recs, clearance dates)	Speeds RTW, trim wage-loss payments.

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Five Questions for Every Vendor Pitch

How many production models are LOB-specific?
(Translation: Do you actually understand Workers’ Comp vs. Disability vs. Auto, or is this one model wearing different hats?)
Can you guarantee deterministic outputs on identical inputs?
No? Enjoy your next regulator Q&A.
Which desk-level KPIs improved in pilot?
Cycle time ⬇, indemnity ⬇, litigation rate ⬇, show me the receipts.
How do you ingest incremental records post-FNOL?
Summaries at first notice are cute; real life is a document firehose.
What transparency do adjusters get into ranking logic?
Adoption dies the moment a frontline adjuster can’t see why the AI flagged something.

The Bottom Line

AI value doesn’t live in PDFs, it lives in the moment-to-moment decisions each adjuster makes. If your solution isn’t purpose-built for their line of business, it’s shelf-ware with a fancy chatbot front end. Demand LOB-specific insight or keep writing checks for tools your desks will quietly ignore.