In a community where many residents manage tight schedules, it’s common to feel pressure to “move on” after a complication—especially if the provider offers reassurance quickly. But when AI tools are involved, problems often hide in the workflow rather than in a single dramatic event.
For example, AI may appear indirectly through:
- Automated imaging interpretation or tool-assisted measurements
- Algorithm-driven risk scoring used during decision-making
- AI-supported documentation that affects how the chart is written and reviewed
- Decision-support outputs that clinicians rely on under time constraints
The key difference in these cases is that the investigation must be able to answer: What did the system output? Who saw it? What did the clinical team do with it? Those details matter for settlement leverage—especially when insurers argue the outcome was a known risk.


