AI and automation aren’t “villains” by default. But in real medical settings, problems can occur when:
- A tool’s output is treated like a final answer instead of a prompt for clinician review
- Abnormal results aren’t escalated or communicated clearly
- Triage or routing decisions delay the right level of evaluation
- Documentation is generated or streamlined in a way that omits key context
- Imaging or lab interpretation is influenced by workflow shortcuts
In a New Britain-area context, these issues can be more likely to surface in fast-paced settings—busy urgent care visits, high-volume clinics, or systems that rely heavily on standardized electronic workflows.


