AI models can organize inputs (injury type, treatment history, symptom duration) and produce a rough range. That can be useful when you’re overwhelmed. However, San Diego cases often involve real-world complexities that generic models don’t reliably capture, such as:
- Delayed symptom reporting after a crash or fall (common when people initially “push through” headaches or dizziness)
- Multiple incident locations (commutes, parking lots, rideshare drop-offs, or transit-related events)
- Disputed accident narratives—for example, conflicting witness accounts near high-traffic intersections or event venues
- Document gaps tied to treatment access or scheduling delays
In short: AI can suggest what categories might matter, but it can’t confirm what caused the injury, how severe it is, or how California insurers typically evaluate the evidence.


