Most AI calculators use simplified assumptions. They may ask for information like the type of injury, how long recovery lasted, whether there were surgeries or complications, and the rough amount of medical bills or lost income. Then the tool applies a generic model to generate a range. That can help you understand common damage categories in a broad sense, but it does not perform the real legal work of a malpractice case.
A key reason is that medical negligence claims are evidence-driven. The calculator does not “read” the medical record the way a qualified legal team does, and it cannot evaluate the credibility of experts, the adequacy of documentation, or the specific timeline that supports causation. In Colorado, the difference between a bad outcome and a legally actionable one often turns on details like whether the provider followed accepted standards, what should have been done differently, and whether those deviations are proven to have caused the harm.
Another limitation is that AI typically cannot account for how the defense frames the facts. Insurance and medical provider risk teams often contest liability and causation. When liability is disputed, the settlement range can swing dramatically based on what the medical evidence will show and how the parties assess the risk of litigation.


