AI tools typically generate a range by using generalized inputs (injury severity, age, and reported needs). That can be useful as a starting point. However, Sheridan cases often hinge on details insurers scrutinize closely, such as:
- what neurologic function tests actually showed at specific medical milestones
- whether symptoms worsened after the accident or were present but missed
- how quickly the injury was evaluated and documented
- whether the record supports a credible future care plan (not just immediate hospital bills)
In other words, an AI estimate can’t verify the medical narrative. It also can’t account for how fault is contested after a crash, fall, or workplace incident—especially when witnesses disagree or documentation is incomplete.


