Many AI tools work like this: you enter a diagnosis, an injury date, and a few details about treatment and time off, and the tool returns a “range.” For Oakley residents, the problem is that the range often assumes your case is moving smoothly.
In real California practice, factors like the following can dramatically shift outcomes:
- Commuter-based wage impact doesn’t always match what payroll shows. If your injury affects overtime, scheduled shifts, or the ability to handle longer commutes, the economic impact may be underrepresented unless the right records and restrictions are documented.
- Treatment gaps can become leverage for the defense. If appointments are missed due to scheduling, transportation, or work conflicts, insurers may argue your symptoms aren’t as limiting as claimed.
- Work restrictions have to be specific and consistent. General “can’t work” notes usually don’t carry the same weight as restrictions tied to functional abilities (lifting, standing, bending, repetitive use).
That’s why a tool’s output should be treated as a starting point—not a prediction.


