AI tools are often built to output a rough range based on inputs like diagnosis, treatment history, and symptom categories. That can feel helpful—until you’re faced with how adjusters actually evaluate claims.
In Lighthouse Point cases, the most common gaps are:
- Documentation timing: If symptoms appear after an accident, your medical timeline has to explain why. Delayed reporting doesn’t always doom a case, but it must be supported.
- Functional impact details: Brain injuries are frequently “invisible.” Without clear evidence of how symptoms affect concentration, memory, sleep, and work performance, an AI-style estimate may understate non-economic harm.
- Causation disputes: Insurers may argue symptoms come from something else (preexisting conditions, stress, migraines, sleep disorders). Your records must connect the accident to the neurological effects.
- Florida claim requirements and negotiations: Even when the injury is real, settlement value hinges on proof, liability posture, and what the defense is likely to contest.
An AI output can help you organize questions, but it should not be treated as a substitute for evidence-based case evaluation.


