AI tools can be useful for thinking about categories of loss, but they often miss the things that matter most in real trucking cases—especially when the crash happens during rush-hour traffic or in areas where vehicles are frequently changing lanes and speeds.
Common ways an AI estimate falls short:
- It can’t confirm the timeline. In Massachusetts, medical records and symptom progression are key. If care was delayed or inconsistent, the value can change.
- It can’t evaluate “who did what.” Truck crashes frequently involve multiple decision points—driver behavior, company policies, and vehicle condition.
- It can’t account for dispute risk. Insurers may challenge causation (whether the truck crash caused the injuries) or argue the injuries were pre-existing.
- It doesn’t know what evidence exists locally. The strength of photos, witness information, dashcam/video availability, and the crash report can affect negotiation.
A number from a calculator is not a settlement offer. It’s only a rough prompt—one you still need to verify against your evidence.


