Many AI tools work by asking for basic details (age, relationship, type of incident, some financial numbers) and then generating a projected range. That can be a starting point—but it often misses what matters most in real cases.
In Winona, liability and damages frequently turn on issues like:
- Whether the fatal incident occurred during commuting traffic, school schedules, or evening travel (and what that means for witness accounts and timing)
- Road and visibility conditions—fog, glare, snow/ice patterns, wet pavement, and night driving realities on local routes
- Pedestrian and bicycle exposure near downtown corridors, trails, and high-foot-traffic areas
- Event-related surges that increase congestion and complicate “who had the right of way” questions
When an AI tool doesn’t see the scene details, it can’t account for how Minnesota juries and insurance companies tend to weigh credibility, causation, and fault.


