AI tools typically take details you enter—crash location, injury type, treatment length—and generate an approximate value based on patterns from other cases. That can be useful when you want to understand which categories of losses matter most (medical care, lost wages, and non-economic harm).
Still, the biggest limitation is that an AI estimate can’t see the evidence the way an attorney does. In Kearny, common crash dynamics—like sudden merges, turning vehicles at busier corridors, or lane changes amid congestion—often turn into disputes about what each driver saw and when. If the tool doesn’t capture those facts accurately, the estimate can land too high or too low.
Also, AI usually can’t account for how NJ insurers evaluate credibility when there are gaps in treatment, unclear symptom timing, or conflicting accounts of the crash.


