AI tools typically work by comparing your inputs to patterns from other cases. That can be useful for setting expectations—but it often overlooks local, practical issues that show up in Nevada workers’ comp files, such as:
- Jobsite documentation gaps (especially when injuries occur on active construction, ranching-related operations, mills, or industrial sites).
- Commute and route changes after restrictions—when your transportation routine changes, your job impact and reporting can look different.
- Timing and reporting friction—in smaller communities, people may delay paperwork, wait to “see if it improves,” or provide incomplete statements before the medical record is fully established.
- Wage structure differences—overtime, shift patterns, and inconsistent schedules can make wage loss harder to calculate unless payroll records and medical work limits are lined up.
When those factors aren’t captured by an AI questionnaire, the estimate can end up either too low (undercounting future needs or restrictions) or too high (assuming facts that your file doesn’t support).


