Picture a bodily injury demand that shows up with medical records nobody had at the last evaluation. The new records point to a different prognosis, but the reserve and the damages assessment are still sitting on the old information. Now the adjuster must figure out what those records actually establish and whether the current evaluation still holds up.
AI can save real time here by finding and organizing those records. But that's table stakes. What I want is for it to help the adjuster get further into the work: tie the new information back to the existing assessment, show the evidence that supports or challenges it, and be clear about what is still unresolved. That is where I see the real opportunity for AI in complex claims.
A seasoned adjuster can work through all of this. The problem is time. Every hour spent tracking down documents and rebuilding the file history is an hour not spent on exposure or on strategy with defense counsel. We should be intentional about using technology to give that time back.
Evaluations Go Stale Faster Than Files Do
An evaluation is a snapshot. It reflects what we knew at a specific point in time. As the claim develops, the adjuster must keep asking whether the assumptions behind that number still hold. And I have seen this repeatedly. A file can look perfectly healthy, with current notes and diaries closed out on time, while the evaluation underneath it has not been touched since the facts changed.
Good AI should make that visible. Going back to the bodily injury example, a different prognosis might warrant a fresh look at damages. It might also raise causation questions or point to the need for more medical information. The adjuster needs to see how the new records fit with everything else in the file before deciding what they mean for the claim.
That is where accuracy comes in, and I mean accuracy in context. A summary can pull a statement correctly and still leave you with the wrong impression if it skips the contrary evidence or treats an allegation like an established fact. A useful review separates what the records support from what is still uncertain.
Timing matters too. You cannot judge a file as if the adjuster had today's information on day one. A review should show how the evidence developed and whether the response made sense at each stage. An earlier evaluation may have been completely reasonable, even if the facts today call for a different approach. Anyone who has been on the receiving end of a hindsight audit knows exactly what I am talking about.
Claims Expertise Must Drive the Review
At Elysian, we start with claims expertise. Our reviews are grounded in structured claims standards and client guidelines, and every finding ties back to the evidence in the file. That matters because a meaningful review depends on knowing what should trigger more investigation or an escalation, and when.
"Investigation incomplete" does not give an adjuster much to work with. If the insured and a witness gave materially different accounts, the finding should call out that conflict and show whether the liability analysis addresses it. Now the adjuster can decide whether another interview is needed or whether other evidence already resolves it, and the supervisor has something specific to talk through.
The same goes for gaps in the record. If there is no documented reserve review in what the system had access to, the finding should say exactly that. Then a reviewer can figure out whether it was missed, recorded somewhere else, or just poorly documented. Those are different situations with different fixes. Lumping them together as one deficiency makes the review less useful, not more.
Leave Room for Judgment
Experienced claims professionals shine in the gray areas, where the evidence is incomplete and reasonable people can land in different places. They are weighing the strength of a liability position, sizing up the uncertainty in damages, and figuring out how to move a file toward resolution. AI should help them make those calls with a clearer picture of the file. It should not make the calls for them.
That means giving them the supporting records and the room to push back on an interpretation. An adjuster may decide the current reserve is still right, or that an apparent investigation gap is explained by information the system never had. Either way, the reasoning gets documented, and accountability stays with the people responsible for the claim.
Technology needs the same scrutiny. Experienced reviewers should be testing its findings and looking hard at the material issues it misses. When a reviewer and the system disagree, that's useful information. It can point to a problem with the interpretation, an incomplete record, or a standard that is being applied too broadly. I will also be the first to say you are never going to get to 100% agreement, because two of the most seasoned people reviewing the same file will not always agree either. What you can get to are decisions that are consistent and repeatable. And that work does not stop at launch. It must keep going as the system, and the claims it reviews, change.
For me, the opportunity is simple: give the claims professional a clearer view of the file while there's still time to change its direction. The hours we get back from assembling facts can go toward evaluating exposure, collaborating with counsel, or having the conversation that finally moves a tough claim toward resolution. That is a far better use of the talent we already rely on.
