Is your organization adopting AI because everyone's doing it and it's expected of you or because you've completed a structured case showing it makes sense for your business? You want to be able to evaluate the contract terms, the true cost, or the build-versus-buy question before you commit, and you can't count on the vendor to provide that information for you.

The information vendors share is designed to sell, not to surface hidden costs, contract risks, or the internal investment your organization would actually need to make the tool work. Healthcare systems can get caught off guard if they don't uncover the hidden costs and value. Making a strong business case means gathering evidence the vendor doesn't volunteer, reading the contract terms that actually carry risk, and honestly deciding whether it's better to buy the tool or build one yourself.

In this course, you will ensure that you're making an informed decision by conducting three connected analyses for a fictionalized AI initiative: a financial model that captures the true total cost of ownership and the full range of direct and indirect value; a vendor evaluation that weighs contract terms, data rights, liability, and procurement risk; and a build-versus-buy decision grounded in your organization's capabilities.

By working through a fictionalized healthcare case, you will gain the knowledge and skills to prepare a business case recommendation that's tailored to the unique needs of your 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
  • Building an AI Governance Framework for Healthcare
 

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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