Nurses at Munson Medical Center in Traverse City, Michigan, have secured a voice in how artificial intelligence tools are adopted at the hospital. The contract provision, won after months of bargaining by the Traverse City Munson Nurses Association, reflects a growing push among nursing unions to negotiate AI safeguards amid rising use of clinical algorithms and automated note-taking systems.
Union pushes for protections
Union president Laura Nilsson laid out the stakes at a rally earlier this year. "We understand technology is coming," she said. "We generally want it to be good for us and our patients, but right now, there's a lot of unknowns. What we don't want technology to do is replace nursing judgment. We don't want it to take jobs." The union's new contract does not block AI, but it ensures nurses will help decide how software is introduced on the floor.
That concern extends far beyond Michigan. A nurses' union in New York City with more than 10,000 members added AI protections to its contract this winter. James Walker, a critical care nurse at Munson and a bargaining committee member, raised a common scenario: a blood pressure cuff placed incorrectly feeds a wrong reading directly into a clinical system. "That value could potentially lead to a wrong decision," he said. An AI tool might process that data without the physical presence of a nurse to catch the error.
What the research shows
Evidence backs the caution. In a recent study from Stanford and Harvard researchers, top-performing AI models from Anthropic and Google produced 12 to 15 severely harmful errors per 100 cases. The worst models made mistakes in 40 out of 100 cases. Max Topaz, a professor of nursing at Columbia University, said new technology is often handed to nurses with little thought about how it will fit into daily practice. "These technologies have to be vetted and validated, and we need to know what the error rates are," Topaz said.
Nurses' concerns highlight the need for rigorous validation of AI tools, a topic that healthcare professionals can explore further through dedicated AI for Healthcare training.
Hospital agrees to collaborate
Jenn Standfest, chief nursing officer at Munson Medical Center, represented the hospital at the negotiating table. She said AI can reduce clerical tasks that lead to burnout. "It's trying to support a reduction in some of the clerical tasks," Standfest said. "It's a really important space and we want to get it right." The agreement means that if the hospital buys new AI software, nurses in northern Michigan will participate in how it is rolled out.
Why this matters for healthcare professionals
Nursing unions are shifting from reactive concerns to formal bargaining demands, inserting themselves into AI procurement and implementation. For clinicians on the front lines, that means a growing expectation to evaluate tools for accuracy and safety rather than simply adopting whatever technology arrives. The Michigan contract is one example, but the pattern - and the data on error rates - suggest that clinical oversight of AI is becoming a standard part of labor negotiations in healthcare.
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