Nurses are raising safety concerns after the White House’s new national AI framework omitted any mention of the profession or healthcare and how artificial intelligence is already being used in clinical care.
Released March 20, the National Policy Framework for Artificial Intelligence outlines seven legislative priorities — from child safety to economic competitiveness — but does not reference nurses or the broader healthcare workforce, according to a March 27 news release from Nurse.org. This omission comes despite the growing use of AI in hospitals for triage, clinical documentation, staffing and patient monitoring.
For nurse leaders, the concern reflects a broader risk that national AI policy may be shaped without the input of the clinicians most directly responsible for patient care.
“At the bedside is where patient safety is most directly protected,” said Mandy Richards, DNP, RN, chief nursing executive and president of Children’s Health at Intermountain Health in Salt Lake City. “When nurses aren’t included in policy discussions, we risk creating tools and systems that overlook the realities of front-line caregiving.”
Leaders pointed to a disconnect between how AI is being designed and how care is actually delivered — particularly when front-line nursing input is absent.
“Without their front-line perspective, AI policies may misalign clinical workflows, increasing errors and cognitive burden, and poor adoption,” said Sharon Pappas, PhD, RN, chief nurse executive of Emory Healthcare in Atlanta.
Leaders said the first signs of failure in AI tools often appear at the bedside, where nurses play a key role in managing care.
“Nurses would likely be the first to recognize when an AI tool’s outputs don’t match reality,” said Elizabeth Steger, MSN, RN, chief nursing executive at St. Luke’s Health System in Bethlehem, Pa.
That perspective is especially critical as AI becomes more embedded in nursing workflows, including documentation, patient monitoring, staffing and early warning systems.
Thus, in the absence of detailed national guidance, many health systems are building their own governance structures to ensure those tools are safe and usable in practice.
At Inova Health System in Fairfax, Va., nurses are directly involved in evaluating and governing AI tools through a formal professional governance structure that vets technologies before and after implementation. Chief Nurse Maureen Sintich, DNP, RN, said that involvement helps identify unintended consequences and workflow-level impacts that may not be visible from a policy or technology standpoint.
At Houston Methodist, a similar model is in place, with AI tools trialed through structured governance and front-line input to minimize friction before scaling. “Without nursing input, AI solutions may unintentionally introduce friction, create safety risks, or fail to meaningfully support patient care,” said Gail Vozzella, DNP, RN, chief nurse executive.
Other systems described comparable efforts to integrate nursing voices into AI strategy and oversight. At Duke University Health System in Durham, N.C., Terry McDonnell, DNP, RN, chief nursing executive and senior vice president, said front-line nurses are involved in the development and implementation of AI tools across decision support, clinical deterioration alerts and triage workflows — an approach she said has improved both adoption and clinical confidence.
“We must include those doing the work in the design and adoption of these tools to achieve the best outcomes,” she said. “The best results we have seen come when the technology serves the clinical relationship, not the other way around.”
At Stony Brook (N.Y.) Medicine, nursing leadership is taking a more measured approach, evaluating AI pilots and emphasizing the importance of rigorous testing, training and multidisciplinary input before deployment. Julie Luengas, DNP, RN, chief nursing informatics officer, noted that excluding nurses from policy discussions risks overlooking key issues such as bias, data quality and real-world usability.
At Dartmouth Health in Lebanon, N.H., leaders are exploring AI tools designed to reduce screen time and administrative burden while preserving face-to-face patient care. The goal, leaders said, is to use AI in ways that are “both safe and effective” while keeping “the patient and their experience at the core.”
Across organizations, AI is already being used to reduce documentation burden, improve communication and support earlier clinical intervention.
At Emory, nursing teams are using AI-enabled fall prevention sensors, predictive models to support rapid response activation and ambient listening tools for documentation. At Intermountain Health, leaders are piloting virtual nursing and ambient documentation tools aimed at freeing up time for direct patient care.
At UC San Diego Health, AI tools are being used to support handoffs, patient communication and pre-procedure workflows, with leaders noting that adoption varies by role and requires appropriate training and oversight. Nurses can choose when to use some assistive tools, “with their clinical judgment as the North Star,” said Chief Clinical Officer Margarita Baggett, MSN, RN.
At BayCare Health System in Clearwater, Fla., AI is being applied to streamline documentation, improve handoffs and support staffing decisions. When used thoughtfully, AI can “help preserve the human connection at the bedside,” said Chief Nurse Executive Patricia Shucoski, DNP, RN.
Still, leaders say governance structures — particularly at the national level — are not keeping pace with how quickly AI is being integrated into care.
Several pointed to the need for clearer guardrails, including nurse co-design, workflow impact assessments before deployment, algorithm transparency, bias monitoring and continuous evaluation after implementation. National guidance should make clear that “front-line inclusion, and continuous monitoring for safety and efficacy are not optional features of responsible AI governance,” Dr. Sintich said.
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