Many AI tools are trained to look for broad patterns—injury type, reported symptoms, time off, and treatment duration. That can be directionally helpful.
In Stuart, though, workplace routines often add variables that calculators can’t see, such as:
- Seasonal workload changes (and whether your missed time was treated as temporary vs. disability)
- Job-site documentation quality (especially where reports are created quickly after an incident)
- Return-to-work expectations that don’t match medical restrictions
- Commuting/transport realities if your restrictions affect your ability to get to or safely perform tasks
When those details aren’t reflected in the inputs—or aren’t reflected accurately—the estimate can end up too low (or sometimes too optimistic), which can affect your next decision.


