AI calculators typically ask for inputs like your diagnosis, the body part injured, the date of injury, treatment history, and whether you missed work. Then they generate a range based on patterns from past cases.
The problem is that Paterson claims often turn on documentation and work-status details that an AI tool can’t truly verify. For example:
- Urban commuting and schedule changes: If your ability to get to work, complete breaks, or perform shift duties changes after the injury, that functional impact may not be captured by a calculator that only “sees” time missed.
- Multiple job sites and variable duties: In many industries common in the area, workers may cover different tasks depending on the day. If restrictions affect only certain duties, the settlement value can hinge on how well those restrictions were recorded.
- Treatment gaps caused by logistics: In a dense city environment, transportation, scheduling, and appointment delays can influence the medical timeline. Insurers may argue the injury is improving sooner than it actually is—unless the record tells a clear story.
An AI estimate may look convincing, but it can still be built on assumptions that don’t match your medical record or the specific disputes an insurer is likely to raise.


