Imagine a claims leadership meeting a year after the organization introduced a new AI platform.
Executive Summary
Why did a claims professional reject an AI recommendation?
Did the recommendation conflict with the human's habit or did the override reveal an AI model limitation?
Here, Sedgwick's Steve Ellis and Taylor Smith of Suite 200 Solutions highlight the importance of asking those questions—and more—as they deliver advice on how insurance company claims leaders can measure the value of AI, in contrast to the speed and volume of AI activity.
Claims organizations are getting better at measuring what AI does. The harder task is determining whether it improves the decisions that drive claim outcomes, not merely the speed at which they are made, they believe, introducing measures for better AI scorecards.
They also address the need to build tomorrow's bench of claims professionals when AI can do the tasks that help them learn.
The dashboard looks encouraging. Documents are being summarized. Demand packages are being reviewed faster. The vendor estimates that thousands of hours have been returned to the operation.
By nearly every measure on the screen, the implementation is working.
Then someone asks a different question: Did we make better claim decisions?
Most organizations are better equipped to measure what technology does than what it changes. We can count summaries, minutes saved and tasks automated.
But those figures cannot tell us whether severity was recognized sooner, a reserve was more accurate or the right case was referred to counsel. They cannot tell us if the file was negotiated more effectively or the outcome was better. Nor do they reveal when a professional catches what the system missed or accepts an answer that should have been questioned.
The claims industry is entering the next phase of AI adoption. The question is no longer simply whether the technology works but what “working” means.
The Two Sides Are Optimizing for Different Things
There is a widening difference in how the plaintiffs’ bar and the defense industry appear to be using AI. Broadly speaking, plaintiffs’ firms are using it to maximize outcomes: strengthening demands, organizing evidence, shaping narratives and finding arguments likely to increase claim value.
