AI tools usually work by collecting basic inputs—where the crash occurred, what injuries were diagnosed, and how long treatment took. They then apply generalized patterns drawn from prior claims.
That approach can be misleading when your case depends on details like:
- Who had the right of way at a specific intersection (and what signals, turn lanes, or sightlines were involved)
- Whether roadside conditions played a role (freshly placed signage, lane shifts, temporary markings, or uneven surfaces)
- Timing and documentation (injuries can evolve after a crash—especially back, neck, concussion-related symptoms, or shoulder trauma)
In New York, insurers may also focus heavily on what evidence ties your medical treatment to the crash. If your records are incomplete or inconsistent, an AI estimate may look “accurate” on paper but still not reflect the way liability and causation are argued in negotiations.


