AI tools typically produce a range based on simplified inputs—injury severity, age, and reported care needs. That can be helpful for orientation, but it often breaks down when the real case hinges on details that aren’t captured by a questionnaire.
In Lawrence, those details commonly include:
- Winter traction and roadway conditions affecting fall/collision mechanics (which can change causation arguments).
- Consecutive medical events (e.g., additional surgeries, infections, or complications after an initial spinal injury) that expand future care needs.
- Long commutes and shift work schedules that affect lost earning capacity, documentation, and the timeline of “functional decline.”
- Care logistics for families in the Greater Lawrence area—transportation, home accessibility, and ongoing attendant needs.
An AI calculator can’t verify what your neurologic exam showed, how your function changed week to week, or what your treating team recommended for long-term management. In Massachusetts, that record-backed explanation is what typically shapes credibility during settlement discussions.


