As health systems race to embed AI into clinical and administrative workflows, many are discovering that deploying the technology is only part of the challenge. Preparing the workforce may prove even more complex.
Across the industry, leaders told Becker’s that while AI tools are moving from pilot projects into daily operations, staff readiness is just as critical to ensuring AI delivers results. Many healthcare organizations are responding with systemwide AI literacy training that explains what the technology is and how it should be used responsibly.
Seattle Children’s is taking that approach. Zafar Chaudry, MD, chief digital officer and chief AI and information officer, said the organization provides foundational AI literacy training that explains AI concepts in plain language for all staff and “reinforces our commitment to using tools responsibly and ethically.”
At John Muir Health in Walnut Creek, Calif., early efforts have similarly focused on core education — what AI is, how it works and how to use it safely while understanding associated risks, Priti Patel, MD, chief medical information officer, told Becker’s. Training today is delivered on a tool-by-tool basis, though a broader strategy is under development.
“Today, informatics provides AI training and support on an application-specific basis, ensuring teams have the skills they need for each AI tool we deploy,” Dr. Patel said.
The organization’s AI Governance Council and workforce development teams are designing a more formal, systemwide readiness framework.
“We are still in the early stages of this work and have not yet implemented a comprehensive, organizationwide AI training program,” Dr. Patel said.
While some health systems are building formal education tracks, others are taking a different approach.
Omaha-based Nebraska Medicine has focused less on centralized training programs and more on making approved AI tools accessible across roles and encouraging peer-led learning.
“One of the things that we’ve been pretty diligent about is making tools available to our staff, whether you’re a back-office staff member, a clinician, a researcher or an educator,” Michael Hasselberg, PhD, chief transformation and digital officer, told Becker’s.
Rather than relying solely on top-down instruction, the organization encourages staff to demonstrate how they use AI in their own roles.
“We actually lean on our staff to create the education for other staff in their areas,” Dr. Hasselberg said. “They’ll hold internal meetings to showcase how they use it.”
The health system’s internal data science and engineering teams also round on clinical floors to ensure AI development reflects real-world workflow needs.
“They’re actually out on the floors with our clinicians, really understanding the workflows that our clinicians identify as having pain points,” Dr. Hasselberg said.
When Nebraska Medicine develops AI use cases, clinicians and operational experts are embedded directly in the build process.
“When we develop our use cases, it is done shoulder to shoulder with the content experts,” he said. “They are working hand in hand with the data scientists to build the tool and provide UI and UX feedback so it’s continuously refined.”
Even as workforce education expands, leaders said cultural alignment can prove more difficult than technical deployment.
“The biggest hurdle has been managing the ‘Hype-to-Fear’ pendulum,” Dr. Chaudry said. “Initially, we saw staff overwhelmed by the hype of what AI could do. As news of AI ‘hallucinations’ spread, we had to pivot our literacy efforts toward risk mitigation and trust-building.”
Managing expectations and trust is now as important as rolling out tools.
Meanwhile, Pat Leonard, CEO of CorroHealth, said many organizations underestimate the operational shift automation requires.
“The biggest challenge in AI upskilling is helping people adapt their mindset and approach to work,” Mr. Leonard told Becker’s. “Automation requires rethinking clinical and financial workflows and focusing on quality.”
He said organizations cannot simply layer AI onto existing processes.
“Fear of job loss often overshadows opportunities for job redesign, and simply adding AI to current processes rarely works,” he said.
Many health systems, he added, are underinvesting in the workforce capabilities required to implement and sustain automation at scale.
“Most are unprepared to implement, manage or optimize automation effectively,” Mr. Leonard said. “Therefore, additional investment is needed in professionals skilled in change management and process redesign.”
While approaches vary — from structured literacy programs to embedded, peer-led models — leaders agree on one point: workforce readiness is crucial to AI’s success.
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