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261 Staff, 6 weeks, 500+ AI Assistants: How UR Medicine Activated Frontline Staff as AI Builders

Related Topics:
WorkforceHealth Technology Artificial Intelligence
Relevant Roles:
Chief Information OfficersChief Medical Information Officers Chief Transformation Officers

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261 Staff, 6 weeks, 500+ AI Assistants: How UR Medicine Activated Frontline Staff as AI Builders

Most health systems face the same constraint: a small central IT team cannot identify every workflow that AI could improve. Staff who encounter those workflows daily rarely have a structured path to act on what they see. The result is slow adoption, missed use cases, and governance built after the fact rather than into the process from the start.

At University of Rochester Medicine, a 32,000-person academic health system, leaders closed that gap by opening AI development to every employee, not only the IT department. A six-week "Build Your Own AI Assistant" challenge gave 261 frontline staff the tools, training, and oversight to build solutions themselves, producing 500 or more custom AI assistants and a model other health systems can implement.

In this webinar, leaders from UR Medicine walk through how the program worked. Viewers will leave with a working framework for running a build-a-thon at their own institution, guidance on pairing no-code platforms with structured training and peer support, and a candid account of what governance is required once frontline staff take on the role of developer.

Key Learnings & Speakers

Key Learnings

  1. Staff closest to the work spot problems that central IT rarely sees. A structured build program gives them a way to act on it.

  2. Structure turns a no-code platform into finished tools. Weekly training, office hours, and peer support carry people from curiosity to a working assistant.

  3. Community transforms isolated builders into a connected network. A shared channel for questions links departments that have never worked together before.

  4. Governance from day one builds trust. Review baked into the process protects patient safety and gives the program room to scale.

Speakers

  • Kathleen Fear, PhD, Senior Director of Digital Health and AI Initiatives, University of Rochester Medicine

  • Lisa Nelson, PharmD, Chief Applications Officer, University of Rochester Medicine

  • Moderator: Rose Maher, VP of AI Transformation, Qualified Health