Most AI tools work like a worksheet: you enter a few facts (injury severity, age, treatment type) and the tool outputs a projected settlement range. That can be a helpful starting point.
But in real Oakley cases, the dispute is often not the injury label—it’s what the record proves.
Common reasons AI estimates fall short include:
- Unclear causation: The insurer may argue your symptoms were pre-existing or not caused by the crash.
- Incomplete functional documentation: Even when imaging shows injury, the claim value depends on documented limits—mobility, transfers, bowel/bladder function, skin risk, and need for assistance.
- Mismatch between “future care” assumptions and a California life-care plan: Future medical costs often rise or fall based on how care is actually recommended and scheduled.
AI can’t review your MRI reports, neuro exams, therapy notes, and clinician expectations the way attorneys do when building a settlement-ready case.


