Three years after their last strike, nearly 15,000 New York City nurses walked off the job and returned to the picket lines in January 2026.

What are nurses fighting for? Like last time - safe staffing ratios, workplace violence protections, and better pay. But this time, they're also fighting for job security as AI becomes more widely implemented in healthcare settings.

AI will undoubtedly disrupt the nursing workforce. The irony is AI might actually solve the very problem driving these strikes: the bedside nursing shortage.

Burnout has led to a nationwide nursing staffing shortage. By 2038, the HRSA projects a nursing shortage of 11% in non-metropolitan areas. And this varies greatly by state, with California expecting a 22% state-wide nursing shortage by 2038.

How did we get here? Bedside nurses are vital and the backbone of our fragmented healthcare system. A good nurse who understands the hospital system and has the skill, time, and bandwidth can make a huge difference in advancing care and preventing complications. Placing a cap on the number of patients a single nurse can care for has been shown to lead to better patient care as well as retention of nurses. Unfortunately, most states do not have fixed nursing to patient ratios. Nurses make up a large proportion of fixed hospital operating costs, and like most things in healthcare, preserving the bottom line gets in the way.

For example, in 2004, California was the first state to implement minimum nurse-to-patient ratios for every unit (i.e. at least one nurse for every five patients on Med-Surg units). These ratios were intended to reduce burnout and keep nurses at the bedside, though implementation cost each hospital $700,000 to $800,000. More recently, in 2024, Oregon mandated fixed ratios for certain units including Med-Surg. But in states with no fixed cap on daily workload, full-time bedside nurses burn out, resulting in high turnover. Hospitals are then forced to rely on more expensive, temporary nursing solutions.

The supply problem was recently amplified by the Covid-19 pandemic, where one-third of nurses reported leaving their jobs. Once again, bedside nurses were on the front lines, managing unprecedented patient volumes while taking on occupational health risks and emotional challenges. 

So, if this burnout leads to high turnover rates,where do nurses go? Behind a computer and phone.

It is no secret that healthcare has exploded in bureaucratic complexity. As an internal medicine resident physician, I am often frustrated by “non-physician tasks” that take my time and burn out my capacity. But I recognize that my “non-physician tasks” are made less burdensome because of “non-nursing tasks”. 

Who triages the deluge of patient messages and refill requests? Who conducts patient outreach to optimize patients pre-op? Who captures missing billing codes when physicians under-document? Who performs retrospective quality review to ensure care delivery and patient outcomes meet regulatory standards (and if so, qualify for those bonus checks)? Nurses with clinical backgrounds. These tasks keep hospitals financially solvent and compliant but pull experienced nurses away from the bedside.

With more training and credentialing, nurses nowadays have numerous career advancement opportunities that offer better wages, predictable workloads, and a perfect escape from the emotional and physical toll of bedside nursing.

AI is putting an end to this perfect escape. These non-bedside nursing roles are being automated - not theoretically, but right now. And the results show both cost savings and improved patient outcomes.

Who triages the deluge of patient messages and refill requests?

Who conducts patient outreach to optimize patients pre-op?

Who captures missing billing codes when physicians under-document?

Who performs retrospective quality review to ensure care delivery and patient outcomes are meeting regulatory standards (and if so, qualify for those bonus checks)?

AI will inadvertently solve the nursing shortage by eliminating the administrative advancement opportunities that depleted bedside nursing in the first place.

If we fix the supply problem, we can fix the staffing ratio problem. If we mandate fixed nursing to patient ratios, we achieve better safety and patient outcomes and improve retention. Nurses spend less time behind computers and more time where they're needed most - at the bedside.

AI is disrupting healthcare. It will be scary. It will completely transform our workflows and we will be forced to embrace a new normal. There is no question it will take away jobs. It will take away opportunities for advancement, and it will shift money away from nurses and their families to AI companies. Unexpected change is uncomfortable, and it is important to recognize and reflect on the impact these changes will have on nurses.

But the outcomes speak for themselves. AI replacing administrative nursing roles is leading to better patient outcomes, improved patient satisfaction, and ultimately, better operating margins.

The solution? Healthcare systems should take the cost savings from AI and feed them into solving the root cause of nursing shortages - better, safer working conditions. Hire more nurses. Guarantee fixed nursing-patient ratios. Then, we can ensure safe working conditions and focus on improving retention rates.

Alyssa Chen, MD, is currently completing her 3rd year as an Internal Medicine resident at Mount Sinai Hospital. She studied computer science at MIT, received her MD and MPH at UT Southwestern and is headed to UCSF to complete her fellowships in gastroenterology and clinical informatics. Her experiences as an engineer and physician-innovator have shaped her interests in developing, implementing, and advocating for data-driven tools that transform care delivery and disease detection and prevention.

Reviewed and edited by Jared Dashevsky, MD, and Angela Zhang

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