Most AI tools are built to output a number using simplified inputs (like injury severity, age, and treatment assumptions). That can be useful as a starting point, but it often fails to reflect what actually moves value in American Fork cases—especially when the injury is catastrophic.
Common gaps include:
- Local medical documentation gaps: An insurer may argue that early records don’t prove the long-term functional impact.
- Unclear causation: In crash cases, disputes about speed, impact, and timing of symptoms can change how damages are valued.
- Future-cost modeling that doesn’t match your life-care needs: Spinal injuries often require long-term planning, but AI tools rarely capture the practical details that Utah adjusters expect to see.
The result? A tool may produce a “reasonable” estimate that doesn’t match the evidentiary story a claim needs to be treated seriously.


