AI Is Ready. Is the Healthcare Workforce?

Byline by: Michael Betz, Chief Growth and Innovation Officer and President, Walden University, initially published on LinkedIn.

The biggest unlock for AI in healthcare isn't the technology. It's the workforce prepared to use it. Our partnership with Google Cloud is built to close that gap. Education is where that preparation happens—for the student training for their first clinical role and for the practicing clinician building toward their next one. It's the position Covista occupies. And it's the problem we're built to solve.

This conviction is driving everything we're building right now. Health systems have made the AI investment. The tools are deployed. What I hear most often from healthcare leaders isn't "how do we implement this"—it's "how do we get our people ready to use it." By the time that question reaches a health system, it's already late. The answer has to start in the classroom.

Through the Covista Care Capacity Monitor, we've documented the scale of that gap. Three-quarters of healthcare executives say AI has a positive impact on care quality—and 65% believe it can help address staffing shortages. Yet 59% of executive leaders say most of their clinical workforce needs upskilling or reskilling in AI.

We are America's largest healthcare educator. No institution is better positioned to help close it.

Healthcare AI Credentials: Delivering Now

We started with what students and clinicians need most right now: practical, relevant preparation they can apply in the care settings they're already working in or moving toward.

Last fall, we announced healthcare-specific AI professional certificates in partnership with Google Cloud. Those credentials are now live across all five of our institutions—available to enrolled students, Covista alumni and healthcare professionals seeking continuing education, with flexible coursework built around the schedules of those already in practice.

The curriculum covers AI applications that support clinical practice, ethical considerations of AI use and patient safety. Graduates who earn these certificates enter the workforce with meaningful progress toward AI readiness—equipped to engage with these technologies thoughtfully as they become a standard part of care delivery.

More than 3,400 learners enrolled within the first week of launch. Students and clinicians didn't wait to be asked. That response tells you everything about where the demand is—and it tells me we're moving in the right direction.

The Classroom of the Future

Credentials address what a student knows. What I think about most is how they learn—and whether the learning environment they're in is built to drive real depth of understanding.

I've believed for a long time that AI would do for mastery what the internet did for access. The evidence is starting to bear that out. Study after study shows that when you individualize education, students are more successful. We're already seeing this at scale—more than half of Chamberlain's nursing students are using our AI-powered tutoring tool, with over a million interactions, getting the support they need in any language at any hour.

The classroom of the future is the next horizon. In active development with Google Cloud, we're building a learning environment designed to know each student as an individual—built from their course materials, responsive to how they absorb and retain content and continuously anticipating where they need support. Embedded directly in Canvas, the platform our students already use every day, it brings together Google's LearnLM, Gemini and NotebookLM in a single connected experience.

We expect to bring an early version to student environments later this year. I believe this is some of the most important work we are doing—for students and for the health systems that will hire them.

Keeping It Grounded: The Healthcare AI Readiness Council

What we build has to reflect what care settings require. So alongside our work with Google Cloud, we convened the Healthcare AI Readiness Council—a group of leading clinicians, health system executives and clinical educators whose job is to make sure what we're creating is grounded in the genuine requirements of clinical practice.

Members include Dr. Toby Cosgrove, former President and CEO of Cleveland Clinic; Dr. Betty Jo Rocchio, Chief Nursing Officer at Advocate Health; and leaders from UChicago Medicine and Trinity Health, among others. They advise on curriculum, evaluate how tools perform in real settings and define what a prepared graduate looks like from a health system's perspective. Their involvement is what keeps this work connected to the floor of a health system—and what gives me confidence that what we're building will matter when our graduates walk through the door.

A Broader Healthcare Ecosystem

The work with Google Cloud is one dimension of a broader commitment to building the AI-ready workforce healthcare needs. Through our collaboration with Hippocratic AI, we've trained more than 3,000 healthcare professionals on AI integration in clinical settings, with 99% committing to apply what they've learned in practice. We're also working with GE Healthcare's Hello AI program to advance AI readiness among professionals and students across the U.S. market.

Together these partnerships serve both students entering the workforce and health systems whose existing staff need upskilling now. The knowledge has to be built in—not added on afterward. When clinicians understand what a tool is doing they use it effectively and confidently.

From the Inside Out

All of this requires something underneath it to work: an organization that is itself serious about building these skills.

Last week, we launched an enterprise-wide AI upskilling journey for our 10,000 faculty members and colleagues—a multiphase commitment to develop transferable skills and an AI-first mindset across every role. The faculty member helping a nursing student think critically about AI in a clinical setting needs to be on that same journey. The commitment runs in both directions—and now it does.

What This Means for Health Systems

The organizations that will see the greatest return on their AI investments are the ones building readiness before the hire—through deliberate, sustained preparation. A graduate who enters with a meaningful foundation in AI doesn't need onboarding on top of orientation. They can help lead adoption from day one.

The workforce readiness problem in healthcare is solvable. It requires education that keeps pace with the industry, partnerships grounded in clinical reality and a genuine commitment to building these skills at scale. It's what we're positioned to deliver—and it's what today's announcement reflects.

The communities that depend on a strong healthcare workforce can't wait. Neither can we.