With nearly 18 million U.S. employees, healthcare is the largest private-sector employer in the nation, yet the industry’s workforce has consistently been characterized by shortages, stress and burnout, according to a report from the National Center for Health Workforce Analysis (NCHWA).
As a result, many American patients are left without access to care, which can lead to worse outcomes and escalating costs. According to the report, in 2025, approximately 92 million people lived in a primary care Health Professional Shortage Area (HPSA) and 137 million lived in a mental health HPSA.
Unfortunately, the problem is projected to worsen if the industry continues on its current trajectory. Across all U.S. physician specialties, there is a projected shortage of 141,160 physicians by 2038, with rural areas affected more acutely than metro regions. For licensed practical nurses (LPNs), the numbers are even more concerning: Demand is expected to outweigh supply, resulting in a shortage of 245,950 LPNs by 2038.
Aging and attrition are also taking a serious toll on the workforce, as 28% of healthcare workers and 41% of nurses indicate they intend to leave their jobs within two years.
However, the healthcare workforce situation may not be as bleak as it seems. Artificial intelligence (AI) offers the potential to relieve many of the issues associated with the healthcare worker shortage and are likely to drive a “skills rotation” that could reshape how the work of healthcare gets done.
A rotation towards domain expertise
In software development, we are already witnessing the early stages of this skills rotation. To draw a parallel: When excavators became available, fewer people were needed to shovel, but the construction industry didn’t shrink.
Instead, it rotated. Demand shifted toward engineers, architects and equipment operators. The same dynamic is now unfolding in healthcare technology.
As AI abstracts away the screen, the traditional model of navigating modules, manually entering orders, and toggling between interfaces will give way to agent-driven workflows. For example, rather than clicking through an orders module to submit a prescription, a clinician might simply instruct an AI agent to draft the order based on clinical context.
Physicians, nurses and other clinical professionals are stepping into technology roles where their understanding of care delivery informs how agentic systems are designed and built. AI can abstract away the act of writing code, but it cannot replace the lived experience of someone who has spent years at the bedside. In this regard, the domain expertise of clinicians is incredibly valuable when leveraged to create more useful technology.
The future of clinical work
This skills rotation extends beyond software development. On the clinical side, AI has the potential to reshape how care is delivered. Patients are already using consumer AI tools to research conditions and organize their health histories before stepping into a provider’s office, transforming rushed appointments into focused, high-impact encounters. Patients are more likely to come to visits well informed and empowered as advocates and more active participants in their own care journeys.
On the ambulatory side, for example, pre-chart visit preparation tools can summarize a patient’s history so providers can absorb critical information before an appointment. Similarly, other AI tools can pull patient data from health information exchanges, consolidate it and highlight the most relevant details within the native health record.
These are practical examples of how AI reduces cognitive burden, giving clinicians more bandwidth to focus on the patient rather than the screen.
AI can augment the administrative and analytical tasks that pull clinicians away from hands-on work that only a human can do.
What AI cannot replace is the trust that patients place in a clinician and the ownership that a clinician assumes for a patient’s wellbeing. This is especially true in acute care settings, where physical presence and rapid decision-making are non-negotiable and patient safety risks heighten.
The combined result of these factors is not fewer healthcare jobs, but a reallocation of effort toward higher-value work where clinical judgment is irreplaceable.
The way forward
While our industry is under immense pressure from provider shortages, demoralizing burnout and rising patient demand, AI offers a path forward that does not entirely depend on adding more people to the system.
Rather, AI enables the healthcare workforce to shift away from repetitive, screen-bound tasks and toward roles that demand domain expertise, clinical insight and human connection. A very practical “north star” approach to AI is to focus on automating and streamlining the unpleasant work. Free clinicians to focus more on the creative, cognitively demanding work that is more fulfilling and enjoyable.
When we look back on this period in healthcare’s evolution, the most successful organizations will not be those that implemented AI simply to satisfy their boards or to tout innovation on their websites.
By investing in tools that address deep pain points and comprehensive training to prepare clinicians for this skills rotation, organizations will find themselves in a stronger, more sustainable position as healthcare continues to evolve.
Because while healthcare is a business, it is a business of people. And AI’s ROI will ultimately hinge on its ability to deliver real relief to the people entrusted to deliver care and support patients.
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