Most AI tools work like a worksheet: you enter details (injury level, age, treatment) and the tool outputs a range. The problem is that spinal cord injury cases are documentation-driven—and the documentation is rarely complete at the moment people start searching.
In Atlantic City, the gaps that skew estimates often come from situations like:
- Tourist-heavy incidents where witnesses may not stay available long enough for follow-up statements.
- Fast-moving crash scenes where evidence (vehicle data, surveillance footage, hazard conditions) can disappear quickly.
- Event and construction timelines where responsibility can be shared among property operators, contractors, and traffic-control parties.
- Delayed symptom reporting when the injury is initially misunderstood as “back pain” or a minor strain.
An AI estimate can’t reliably account for those real-world evidence issues—yet insurers absolutely do.


