AI settlement tools typically work by taking the details you enter—such as your injury type, treatment timeline, missed work, and stated restrictions—and then comparing that information to patterns the system has seen before.
In real California workers’ compensation practice, however, outcomes often turn less on the “headline” injury and more on evidence quality and how the claim develops procedurally. That’s where AI can be off.
Common ways AI estimates go wrong include:
- Overlooking California-specific medical milestones, such as when your treating physician documents stabilization/maximum medical improvement.
- Missing restrictions that are inconsistent across visits (a frequent issue when appointments are delayed or work status changes).
- Underestimating wage impact when overtime, shift differentials, or schedule changes aren’t clearly reflected in the record.
- Assuming the work injury is undisputed, even though insurers often investigate incident reports, notice timing, and causation.
If you’re using an AI tool, treat the output as a starting point for questions, not a prediction you should rely on.


