Many AI tools work by comparing the details you enter to generalized patterns. That can feel reassuring when you’re dealing with pain, missed shifts, and uncertainty.
In real Faribault cases, however, the outcome often turns on details that an AI tool can’t reliably see, such as:
- Whether your treating provider’s records clearly connect symptoms to work restrictions
- Whether the insurer disputes the timeline, the mechanism of injury, or causation
- Whether wage loss is supported by payroll records and consistent employment history
- Whether your claim has reached a point in the process where impairment and future treatment are being evaluated
If your claim involves documentation gaps—something that can happen when schedules are tight, travel to appointments is difficult, or symptoms change midstream—an AI range may understate what the evidence can support.


