AI estimates often look persuasive because they produce a number range fast. The problem is that the inputs people use are usually incomplete—particularly for injuries that unfold over weeks.
In a local Missouri claim, common “missing pieces” include:
- Work restrictions that change over time (e.g., you were cleared for light duty later, but your restrictions weren’t consistent in early records)
- Treatment gaps caused by scheduling, transportation, or waiting on authorizations
- Medical findings that don’t match the story you told in the first days
- Wage and work-impact details that aren’t fully supported by pay stubs or consistent documentation
An AI tool can’t verify whether your medical record supports the functional limits you’re relying on. It also can’t predict how the insurer will treat disputed issues like causation, maximum medical improvement, or the credibility of conflicting statements.


