Summary
Healthcare organizations around the world are confronting a growing workforce crisis. Burnout, administrative burden, staffing shortages, and accelerating retirements are placing unprecedented strain on clinicians and the systems they support. At the same time, artificial intelligence (AI) is rapidly being integrated into healthcare settings, often accompanied by questions about automation and workforce replacement. New research published in The Lancet offers a different perspective. The study was authored by Tinglong Dai, Bernard T. Ferrari Professor at The Johns Hopkins Carey Business School and CIL Core Faculty, Kathryn McDonald, Bloomberg Distinguished Professor at the Johns Hopkins School of Nursing and CIL Affiliate, and Daniel Baumgart, Professor of Medicine at the University of Alberta. The authors argued that AI’s greatest potential lies in helping clinicians remain in practice, reducing unnecessary burdens, and preserving scarce expertise. The central insight is simple but powerful: the future of healthcare may depend less on replacing people with technology and more on using technology to help people do the work only they can do.
The Leadership Challenge
Every leader eventually encounters a resource constraint that cannot be solved through greater efficiency alone.
In healthcare, that constraint is increasingly human expertise.
Demand for care continues to rise as populations age and chronic conditions become more prevalent. At the same time, healthcare organizations face mounting workforce shortages driven by burnout, administrative complexity, and the departure of experienced professionals from the field. The challenge is not simply finding more clinicians. It is creating conditions that allow clinicians to sustain meaningful careers while delivering high-quality care.
For leaders, this presents a difficult balancing act. Organizations must improve access, manage costs, maintain quality, and support workforce wellbeing simultaneously. Traditional solutions often focus on increasing productivity or recruiting additional talent. Yet many healthcare systems are discovering that these approaches alone are insufficient.
The question facing leaders today is not simply how to increase capacity. It is how to preserve and amplify the expertise that already exists.
Getting to the Source of the Problem
Public conversations about AI frequently begin with questions about automation. Which tasks can technology perform? Which jobs might disappear? How much efficiency can organizations gain?
The authors argued that these questions overlook the more pressing challenge facing healthcare.
The problem is not a shortage of technology. It is a shortage of people.
Healthcare systems around the world are struggling to recruit, retain, and support the professionals needed to meet growing demand. Projections suggest a global shortfall of approximately 11 million health workers by 2030. At the same time, many clinicians report spending substantial portions of their day on documentation, billing, coding, scheduling, inbox management, and other administrative responsibilities that compete with patient care.
The researchers therefore asked a different question: What if the most valuable role for AI is not replacing clinical work, but removing the burdens that pull clinicians away from it?
This perspective challenges a common assumption that AI’s primary value lies in substitution. Instead, the authors proposed that AI should be viewed as a workforce strategy—one designed to preserve expertise, reduce burnout, and strengthen the long-term sustainability of healthcare systems.
New Findings with Implications for Organizational Performance
The research highlighted several areas where AI can create meaningful value by reducing friction rather than replacing expertise.
One promising application is ambient documentation. Rather than requiring clinicians to spend hours entering notes and updating records, AI systems can generate documentation automatically during patient encounters. Similar opportunities exist in coding support, claims processing, scheduling, demand forecasting, and inbox triage.
Individually, these applications may appear operational in nature. Collectively, however, they reveal a much larger opportunity.
Each task removed from a clinician’s workload creates space for activities that require human judgment, empathy, teaching, collaboration, and leadership. A physician who spends less time completing documentation has more time to engage patients in meaningful conversations. A nurse who spends less time navigating administrative requirements can devote greater attention to care coordination. A healthcare leader who spends less time processing information can focus more fully on developing people and improving systems.
The authors described this approach as expertise amplification. Rather than attempting to replace highly trained professionals, AI enables them to operate at the top of their capabilities.
The research also pointed to a broader global implication. Workforce shortages have led many high-income countries to recruit healthcare professionals from regions that often face shortages of their own. While this strategy may provide short-term relief, it can deepen global inequities in access to care. By helping organizations use existing expertise more effectively, AI may offer a more sustainable path toward addressing workforce challenges without intensifying competition for scarce talent.
At the same time, the authors cautioned that technology alone cannot solve systemic problems. Poor implementation can create new burdens, increase complexity, and undermine trust. AI does not automatically improve work. Its impact depends on how thoughtfully it is integrated into existing systems and workflows.
What This Means for Leaders
This research invited leaders to rethink how they evaluate the success of AI initiatives.
Too often, conversations about technology focus on efficiency metrics alone. While efficiency matters, it may not capture the outcomes that are most important for organizational sustainability. Leaders should also ask whether AI helps people remain engaged in their work, reduces unnecessary sources of frustration, and strengthens the capacity of professionals to contribute their expertise.
This shift in perspective has important implications for implementation. AI should not be viewed solely as a technology investment. It is also an investment in workforce wellbeing, professional sustainability, and organizational resilience.
Leaders who approach AI through this lens are likely to focus less on headcount reduction and more on expertise preservation. They will involve frontline professionals in implementation decisions, evaluate technologies based on their impact on work rather than technical capabilities alone, and ensure that human judgment remains central to decision making.
Most importantly, they will recognize that technology creates value when it strengthens people rather than substitutes for them.
A Question for Leaders
Organizations across every sector are grappling with how AI will reshape work. Healthcare offers an important lesson.
The most significant contribution of AI may not be its ability to perform tasks that humans once completed. It may be its ability to remove the obstacles that prevent humans from doing their best work.
As workforce shortages, burnout, and growing demands continue to challenge organizations, leaders should ask a simple question: Are we using technology to replace expertise, or are we using it to protect and amplify it?
The answer may determine not only the success of AI initiatives, but also the long-term health of the organizations and people they are intended to serve.
Access the full research paper here: Dai, T., McDonald, K. M., & Baumgart, D. C. (2026). Global advances in health artificial intelligence: A workforce imperative. The Lancet. https://doi.org/10.1016/s0140-6736(26)00693-8
