Many AI tools ask for basic details—age, the incident type, and sometimes broad financial information—to generate an estimated recovery range. That approach can be tempting in Lansing because fatal incidents often happen quickly around familiar routines: commuting corridors, intersections, construction zones, and busy sidewalks near schools and downtown.
The problem is that AI can’t see what matters most to adjusters and juries:
- Whether fault is realistically provable from the scene evidence (signals, markings, speed indicators, witness accounts).
- Whether causation is disputed (for example, if medical records suggest other contributing factors).
- Whether the losses are documented (receipts, wage records, proof of dependency, medical billing timelines).
In other words, an AI estimate may produce a plausible-looking figure—but it can’t tell you whether your case is likely to be accepted, challenged, or reduced.


