Most healthcare organizations have a governance structure for technology, but few have one that actually works for implementing AI. Significantly, traditional oversight committees move at the pace of procurement cycles and annual reviews, but AI moves at the pace of rapid updates. The result is a growing accountability gap. Organizations that close the gap are the ones that can clearly identify who owns AI decisions, who responds when something goes wrong, and what is the protocol before a problem occurs.

In this course, you will develop the structural components of an AI governance framework; evaluate the ethical, legal, and consent considerations that any responsible deployment requires; and produce a governance charter and policy document grounded in your organizational context. You'll work through questions that most organizations haven't answered yet: Who owns AI decisions, what transparency standards apply, when patient consent is required, and what happens when a deployed model starts to drift. By working through a fictionalized healthcare case, you'll practice building an effective AI governance package for your own organization.

You are required to have completed the following courses or have equivalent experience before taking this course:

  • Examining the AI Landscape in Healthcare Delivery
  • Designing Clinical Workflows for AI Adoption
 

How It Works

Course Length
2 weeks

Effort
4 to 6 hours of study per week

Format
100% online, instructor-led
  • C-suite and senior healthcare executives (CEOs, CMOs, CIOs, CDOs, CNOs, COOs) responsible for strategic AI investment, governance, and enterprise-wide adoption
  • VPs and directors of digital health, clinical operations, and innovation leading AI pilot design, workflow transformation, and scale-out execution
  • Hospital and health system administrators overseeing operational transformation and resource allocation for AI initiatives
  • Physician leaders and clinician-executives (medical directors, department chairs) serving as clinical champions and bridging practice with technology strategy
  • Health IT and informatics professionals (directors of health IT, clinical informaticists, CTOs) moving from technical implementation into strategic and governance roles
  • Healthcare consultants and strategy advisors serving delivery organizations who need credentialed expertise in AI procurement, governance, and ROI
  • Regulatory, compliance, and legal professionals navigating HIPAA, FDA classification, algorithmic bias, and evolving U.S. state-level AI legislation
  • Healthcare project and program managers, quality improvement directors, and technical product managers leading cross-functional AI implementation and outcomes measurement
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