AI tools can be helpful for organizing details, but they often make assumptions that don’t match your case. Common ways AI estimates go wrong include:
- Symptom timing doesn’t match the model. Concussion and other TBI symptoms can appear immediately or evolve over days/weeks. If your medical record shows a different timeline, the AI range may be off.
- Gaps in treatment get weighted too heavily. If you had to pause care due to scheduling, transportation issues, or insurance delays, AI may treat that as weakening the claim—while Wisconsin cases may still be supported depending on the full explanation and documentation.
- Local facts change liability. A crash involving turning movements, distracted driving, or lane changes on a high-traffic route can affect fault analysis. Property-condition issues (like lighting, uneven surfaces, or missing warnings) can affect slip-and-fall liability.
The key takeaway: use AI to identify questions—not to decide what your claim “should” be worth.


