AI tools typically work by taking inputs (diagnosis, treatment, symptom duration) and producing a rough range. That can feel helpful, but it often misses the realities that affect valuation in North Dakota:
- Winter and road-condition claims: When slick roads, poor visibility, or snow/ice maintenance issues are involved, liability can depend heavily on documentation. If the file doesn’t clearly explain the conditions and timing, insurers may argue causation is weak.
- Delayed symptom reporting: In many TBI cases, the first visit may happen after the initial collision or slip occurs. AI outputs don’t always account for how those delays are explained by medical guidance and follow-up care.
- Functional impact vs. diagnosis label: Insurers and adjusters care less about the name of an injury and more about what the injury changed—work capacity, concentration, driving safety, household tasks, and daily reliability.
Takeaway: if you use an AI estimate, treat it like a checklist. The “number” is only useful if your medical records and evidence tell the same story.


