PROGRAM SUMMARY

Rapidly expanding artificial intelligence (AI) tools are becoming integral to healthcare, influencing everything from clinical documentation to revenue cycle management and administrative workflows. As vendor and payer systems incorporate more AI capabilities, small and rural hospital leaders have an opportunity to shape these tools to strengthen performance, reduce administrative burden, and support long-term goals. Doing so will require deliberate evaluation, alignment with organizational priorities and appropriate governance from the outset. Drawing on focus groups with hospital executives and early AI adopters, this three-part webinar series will walk you through what AI can do today, what’s coming next and how to rightsize structures to support safe, sustainable implementation.


WHAT YOU’LL LEARN

Webinar 1 – Foundations of AI in Rural Healthcare ꟾ April 10

This session will examine how AI is currently applied in small and rural hospitals, including clinical documentation, ambient listening, decision support, and administrative workflows. Through real-world implementation examples, we’ll identify common challenges in resource-constrained environments and outline baseline policies, consent considerations, and governance structures needed before expanding AI usage.

Webinar 2 – Strategy, Governance and Vendors ꟾ May 8

To move from exploration to structured implementation this session will define governance models appropriate for your organization’s size and complexity. You’ll learn how to assess vendors using an evaluation framework, decision authority for AI investments, and communication strategies that build AI literacy, reduce resistance, and strengthen workforce confidence during implementation.

Webinar 3 – Implementation, Metrics and Sustainability ꟾ June 5

This session will cover operationalizing AI strategies developed in earlier sessions. Topics include defining metrics aligned with organizational goals, scaling successful pilots through phased implementation, and addressing emerging challenges such as data quality, cybersecurity, and ethical oversight. We’ll also outline sustainability structures, including institutional memory, continuous learning processes and a practical 30-60-90-day action plan for your organization.


OVERALL LEARNING OBJECTIVES

By the end of this three-part series, participants will be able to:

  • Assess your organization’s AI readiness and identify strategic implementation opportunities.
  • Develop governance structures and policies to support responsible AI adoption.
  • Navigate common challenges including budget constraints, vendor selection, and employee anxiety.
  • Build organizational AI literacy and reduce organizational resistance to change.
  • Create strategic roadmaps for sustainable AI integration aligned with institutional goals.