AI tools generally work like a questionnaire: you enter injury details, and the model returns a rough range. That can be a helpful starting point, but it often misses the realities that matter most in settlement talks—especially in cases involving serious neurological damage.
In Pomona, common claim complications include:
- Traffic-pattern injuries where the collision severity and timing of symptoms are disputed (rear-end impacts, lane changes, and fast merges on busy corridors)
- Delayed discovery of neurological issues—where the first ER visit looks “minor,” but later testing confirms spinal trauma
- Comparative fault arguments—insurers may claim the injured person contributed to the crash (for example, alleged sudden stops, visibility issues, or failure to wear a seatbelt)
AI can’t reliably weigh these factual disputes the way attorneys do after reviewing photos, medical notes, and incident documentation.


