Many people assume AI is either “always right” or “obviously wrong.” The legal issue is usually different: whether the care team used tool output appropriately, verified it against the patient’s symptoms and objective findings, and escalated when risk indicators suggested the diagnosis should be challenged.
In Ardmore, common real-life settings where diagnostic problems can escalate include:
- Emergency visits during peak hours when clinicians must triage quickly
- Follow-up gaps after discharge when symptoms persist or worsen
- Transfer coordination between facilities where records and test results must flow correctly
- Imaging/lab turnaround issues where results may be available but not acted on promptly
Even if AI was only “part of the process,” the question becomes: What did the tool recommend, what did the clinician do with that information, and how did the documentation reflect clinical reasoning?


