AI tools are designed to be fast and easy to use. They generally take input about the type of injury, the timeline of care, and the rough costs or impacts you report, then apply simplified assumptions to produce a range. That can feel reassuring when you want clarity, especially when you are trying to decide whether it is worth pursuing a claim at all. But the output is not a substitute for legal analysis, and it cannot reliably determine whether a provider’s care fell below the accepted standard or whether the negligence caused your harm.
In real medical malpractice cases, the most important questions are usually not “How bad is the injury?” but “What did the provider do, what should they have done instead, and what medical evidence shows the difference mattered?” Those questions require review of charts, diagnostic reasoning, operative reports, nursing documentation, lab results, imaging, and follow-up notes. AI can’t verify those documents, evaluate expert opinions, or weigh credibility the way a legal team does.
Vermont’s legal process also places heavy emphasis on building a coherent case narrative supported by evidence. Settlements often reflect the strength of liability proof and the defensibility of damages, not just the severity of the outcome. That means two cases with similar injuries can settle for very different amounts depending on the quality of the medical record, the clarity of causation, and whether the defense believes it can challenge the claim effectively.


