As AI tools make their way into everyday clinical workflows, nurse leaders are grappling with a pressing challenge: how to prepare front-line staff for AI adoption without adding to the technology fatigue that already strains the workforce.
Becker’s connected with chief nursing informatics officers on how they approach AI readiness among nurses. Their responses point to a shared strategy: Empower staff early, begin with small pilots and ensure AI is viewed as a partner rather than a burden.
At Philadelphia-based Jefferson Health, CNIO Colleen Mallozzi, BSN, RN, is piloting ambient documentation using an opt-in model. Rather than mandating adoption, her team invites units to volunteer, which has sparked strong enthusiasm across practice groups. She said the key is ensuring nurses shape the technology instead of feeling like it is imposed on them.
“AI in nursing won’t stick if it feels like another tech fad,” Ms. Mallozzi said. “Empowerment beats a mandate every time.”
Los Angeles-based UCLA Health is following a similar path. CNIO Donna Wellbaum, MSN, RN, described a phased rollout that begins with pilots in innovation units, supported by governance councils and staff focus groups. The intent is to keep exposure manageable, reduce fatigue and build confidence before scaling across the system.
Other leaders emphasized that the type of AI being introduced matters greatly. At Akron, Ohio-based Summa Health, CNIO Marc Benoy, BSN, RN, said conversational AI is often easier to adopt because it provides consistent, rule-based responses while keeping clinicians in control. Generative or agentic AI, however, can be less predictable, requiring more scrutiny and governance to ensure safety.
“Without strong safeguards, clinicians may worry about unintended consequences or errors being introduced into workflows,” Mr. Benoy said. “These concerns can amplify technology fatigue, not only from the effort required to learn new interaction styles but also from uncertainty about the logic driving the system.”
At Tampa, Fla.-based Moffitt Cancer Center, CNIO Marc Perkins-Carrillo, MSN, RN, relies on early adopters to serve as peer coaches. By empowering front-line nurses to take ownership, his team has fostered a grassroots movement that builds trust and credibility.
For Tucson, Ariz.-based TMC Health, empathy and clarity guide AI adoption. CNIO Amanda Klopp, DNP, RN, focuses on explaining the “why” behind the technology — whether reducing documentation time or improving patient safety — and integrating tools seamlessly into workflows. Her team avoids extra logins or standalone apps and favors short, role-specific training over lengthy sessions.
“AI should feel like a relief, not a responsibility,” Dr. Klopp said. “When nurses see that it helps them spend more time with patients and less time on screens, adoption becomes a shared success.”
R. Jared Houck, RN, CNIO at Charleston, S.C.-based Roper St. Francis Healthcare, echoed the importance of trust and change management. He said much of the work lies in setting realistic expectations, clarifying what AI tools can and cannot do, and ensuring they truly save time.
“Preparing nurses for AI is less about the technology itself and more about change management, workflow integration and trust,” Mr. Houck said.
