Conducting a successful pilot is a great start, but it's only evidence that the conditions were ideal during the pilot: Your AI tool champions were motivated, the workflow was smooth, and the vendor was still in the room to lend a hand. When those ideal conditions don't travel, the tool can encounter obstacles that weren't noticed during the pilot.

Scaling an AI tool across an organization is a different discipline from piloting one. It requires an honest assessment of whether your organization is actually ready, a sequenced plan that accounts for how things break differently at volume, and a monitoring strategy that watches for the right signals long after the vendor has left.

In this course, you will diagnose scaling readiness across five pillars: clinical integration, operational workflow, financial viability, technical architecture, and governance. You will build a 30-60-90-day roadmap with milestones, phase gates, and a risk register, and design a continuous monitoring plan spanning technical, clinical, human, and operational dimensions.

By working through a fictionalized healthcare case, you will develop the skills and frameworks to build a scaling plan for your own organization and bring a recommendation your leadership can act on.

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
  • Building an AI Governance Framework for Healthcare
  • Evaluating Costs, Contracts, and ROI for Healthcare AI
 

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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