Many AI tools generate a range by asking for inputs like injury type, treatment dates, and symptom severity. That can help you organize information. But the output often fails to reflect how claims are evaluated in real life—especially when the evidence is split between emergency care, follow-up visits, and how the injury affected your ability to function in a specific setting.
In Gardner, common real-world complications include:
- Commute and work demands: Many residents rely on predictable schedules for shift work or commuting. Brain injuries can disrupt attention, reaction time, and stamina—issues that don’t always show up in a quick medical note.
- Mixed transportation risks: Collisions involving passenger vehicles, trucks, and bicycles (and pedestrian accidents near busier corridors) can create disputes over speed, lane position, and where impact occurred.
- Seasonal activity changes: When symptoms flare after exertion, weather changes, or return to routine, insurers may argue the injury “should have improved sooner.”
An AI number can’t weigh those facts the way a lawyer does when building the claim around proof of causation and documented functional impact.


