Why “experiment first, govern later” is unsafe in healthcare AI—and how to implement governance, monitoring, and accountability before deploying AI into clinical workflows.
A practical filter hospitals can use to choose a first AI project with fast, measurable impact, strong data readiness, low clinical risk, and feasible integration—plus common starter use-case examples and pilot guidance.
Why “experiment first, govern later” is unsafe in healthcare AI—and how to implement governance, monitoring, and accountability before deploying AI into clinical workflows.
A practical filter hospitals can use to choose a first AI project with fast, measurable impact, strong data readiness, low clinical risk, and feasible integration—plus common starter use-case examples and pilot guidance.