Many clinicians already use AI assistants at work. The open question for health system leaders is which one to put in every clinician’s hands. That choice goes beyond features and price. It comes down to trust, safety, and how well the tool fits into clinical workflows.
An assistant that understands the patient in front of the clinician works very differently from a general-purpose chatbot. One draws on the patient’s record to be useful at the point of care; the other answers in a vacuum. A tool that can scale across an entire system takes clear requirements from the start, not after the rollout stalls.
In this session, health system leaders share how they evaluate clinical AI assistants: what patient context really means in the exam room, how these tools fit into everyday clinical workflows and what a systemwide deployment demands.
You’ll learn:
- Why patient context matters, and how an assistant built on the patient’s record differs from a general-purpose AI tool
- How health systems evaluate clinical AI assistants, and the selection criteria that matter most
- What it takes to fit an assistant into clinicians’ daily workflows so it gets used
- The governance, integration and support required to put one assistant in every clinician’s hands