AI tools generally work by sorting your answers into damage categories (medical bills, lost wages, pain and suffering) and then applying simplified assumptions.
In real cases, however, the outcome usually turns on issues AI cannot truly “see,” such as:
- Medical causation: whether the provider’s conduct actually caused your specific harm (not just whether the injury occurred during treatment)
- Standard of care: what a reasonably careful clinician would have done in the same circumstances
- Documentation quality: whether the chart supports the timeline and severity of injury
For Hutchinson residents, this can be especially important because many people rely on a network of providers over time (primary care follow-ups, referrals, imaging, therapy). If the record is fragmented—different systems, different dates—AI may produce a misleading range.


