Most AI tools build estimates from general patterns—age, relationship, and broad categories of loss. That approach breaks down in real cases where the outcome turns on details such as:
- How fault is allocated (for example, disputes over speed, visibility, roadway conditions, or compliance with safety requirements)
- Whether causation is contested (especially when medical records show complications or intervening factors)
- What documentation actually exists (police reports, employer incident documentation, medical timelines, and witness statements)
- How Louisiana courts view damages evidence when insurers push back
In other words, two families can enter the same inputs into an AI calculator and get the same “range,” yet face very different settlement leverage depending on proof and liability issues.


