Most AI tools work like this: you enter details (injury type, symptoms, treatment, work impact), and the tool generates a range or a list of missing variables. That can reduce uncertainty—but it doesn’t replace legal evaluation.
In Plainfield cases, the most common reason an AI estimate feels “off” is that it can’t see how evidence will be challenged. For example, insurers may focus on:
- Whether your symptoms began soon after the incident (or were reported later)
- Whether your treatment followed a consistent plan (not necessarily “more,” just documented and reasonable)
- Whether imaging/clinical findings align with the impairment you describe
- Whether your day-to-day limitations are supported by medical notes and functional accounts
An AI output is best treated as a checklist—something that helps you identify what documentation you still need before a value conversation starts.


