Most AI tools work like this: you enter injury details (body part, date of injury, treatment, wage loss), and the tool returns a predicted range based on patterns from other cases.
That can feel helpful—but it can also be misleading when your claim depends on issues AI can’t verify, such as:
- Whether Utah medical records clearly connect your symptoms to the work incident (not just “you were injured”)
- Whether work restrictions were documented in a way insurers accept (especially when you’re asked to return to modified duties)
- Whether wage loss evidence matches how you actually work (overtime schedules, shift changes, or variable hours common in local industries)
- Whether the insurer is contesting key facts early—because the “value” changes dramatically depending on dispute posture
In Millcreek, many working people are juggling treatment while commuting to job sites or facilities. If your timeline shows gaps—missed appointments, delayed reporting, or inconsistent restrictions—AI estimates tend to assume “average” behavior, even though insurers often scrutinize inconsistencies.


