Nurses demand seat at AI table as hospitals deploy clinical tools without their input

Nurses are pushing back. After years of watching hospitals deploy artificial intelligence tools without consulting the people who would actually use them—the 4 million nurses who form the backbone of American health care—they're demanding a seat at the table where these decisions get made.

The frustration runs deep. Nurses' own data—their logs of vital signs, their medication records—has become the fuel powering a new generation of clinical AI systems, like automated sepsis alerts. Yet when those algorithms malfunction, when they trigger false alarms or miss a patient entirely, it's the nurses who bear the consequences. They're the ones waking up to phantom alerts at 3 a.m., the ones responsible for responding to a system that cried wolf, the ones left to catch what the machine missed. "That's where the tension is," said Jing Wang, dean of the Florida State University College of Nursing. "I had a bad experience with technology before that didn't work. What do you expect me to do?"

Wang has spent the last two years trying to reshape that dynamic. In 2024, FSU launched the first nursing degree with a concentration in artificial intelligence—a deliberate effort to train nurses who can think critically about these tools before they arrive in their units. The program doesn't ask nurses to become computer scientists. Instead, it teaches them to ask the right questions: What happens when this fails? Who is responsible? Will this actually give me more time with patients, or just more screens to watch? By the time students graduate, they've spent a semester working with hospital systems and private companies, learning to evaluate vendors, assess cybersecurity, and understand what appropriate guardrails look like.

The need for that training is urgent. Cathy Kennedy, a president of National Nurses United, has watched newer nurses—those without years of bedside experience—simply accept whatever an algorithm tells them to do. They lack the lived experience to question a system's output, to recognize when something doesn't add up. "We're trying to explain it's important to use your critical-thinking skills," Kennedy said. In unionized hospitals, nurses have leverage. They can bargain collectively over any change to working conditions, including the introduction of new technology. In nonunion facilities, that power evaporates. Nurses who push back risk their jobs. Many have simply left the profession.

Rae Walker, who directs the nursing PhD program at UMass Amherst, has documented what happens in those environments. Patients arrive sicker than ever. Nurses face mounting demands. And when hospitals introduce AI systems designed to improve efficiency, what actually happens is that nurses spend their shifts responding to continuous monitors and automated alerts—work that often exceeds human capacity. In 2025, Walker published the Digital Defense Toolkit, a resource guide for nurses and care workers trying to protect themselves and their patients. It offers concrete questions: What recourse do I have if something goes wrong? Who is liable for any harms? If a tool is supposed to free up my time, how will we actually measure whether it does?

Walker is also building an index to measure how AI tools affect nurse well-being and work environment—a metric that rarely gets tracked. Hospital administrators often use algorithmic outputs to determine staffing levels, which means a flawed AI system can become an excuse to reduce the number of trained nurses on a unit. "The tech is becoming more and more an excuse to reduce the degree to which there is a human workforce that is trained and consistent to be able to meet the needs," Walker said. Nurse administrators find themselves in an impossible position: responsible for staffing their units but lacking the budget power or decision-making authority to push back.

FSU's approach is gaining traction. This month, Wang and her colleagues received a $1.6 million grant from the National Institutes of Health to train nurse scientists to develop AI solutions and evaluate their impact on patient outcomes. The school has also launched a consortium of AI developers, health systems, and educators to create guidelines for how nurses should participate in AI governance and adoption. The theory is straightforward: if these tools are meant to help clinicians provide better care, then involving the people who actually deliver that care—from the beginning—will produce solutions that actually work.

But the technology is moving faster than anyone can manage. "It's coming so fast," Kennedy said. "We really need to get a handle on this to make sure we're doing right by patients." The question now is whether hospitals will listen before the next generation of nurses burns out, or whether the profession will have to fight for a voice it should have had all along.