AI tools usually work by taking inputs (crash description, injury type, treatment duration, and work loss) and generating a rough damages range. That can be useful when you’re trying to understand which categories—medical costs, lost income, and non-economic harm—tend to move a settlement number.
But the reason estimates often miss the mark in real Laurel cases is simple: the model can’t fully evaluate credibility, fault disputes, or the strength of your medical timeline.
In Maryland, insurers may focus on questions like:
- whether the crash is consistent with the documented injuries,
- whether treatment was timely and medically necessary,
- whether another condition could explain your symptoms,
- and how fault is supported by evidence.
A good lawyer doesn’t treat an AI number as a “real offer.” Instead, it’s used to help you ask smarter questions while evidence and records are gathered.


