Many people assume an AI error means the software “made a mistake.” In real cases, the legally important question is different: how the care team used (or failed to verify) machine-assisted outputs and whether the diagnosis met accepted standards of medical practice.
That can include situations like:
- A risk score or decision-support suggestion that wasn’t treated as one input among many
- Imaging or lab interpretation assistance that wasn’t reconciled with the patient’s symptoms
- Documentation errors that made it harder to recognize abnormal findings
- A follow-up plan that depended on information being reviewed promptly—then wasn’t
If you’re trying to understand whether your case could involve an automated workflow, we focus on what Oklahoma providers were expected to do at the time and whether their process handled risk appropriately.


