A new investigation into how artificial intelligence is evolving nursing education has highlighted the need to foster nurse professionals who can help standardize nurse-generated data and architect systems consistent with patient-care ethics.Nurses need to understand, not only how to use AI tools, but also how the systems work and how bias or inaccurate outputs can affect patient care, nursing education researchers said in their report, published in the May-June edition of Nursing Outlook.They also need formal evaluation frameworks and scientific methods to measure accuracy, reliability, bias, staffing impacts, documentation demands and patient outcomes because AI systems could add to costs and workflow burdens."A technically impressive system can still fail if it does not fit how nurses actually deliver care or if it increases burden instead of reducing it," coauthor Antonia Villarruel, RN, dean of the University of Pennsylvania School of Nursing, warned in a UPenn Leonard Davis Institute of Health Economics announcement this week.WHY IT MATTERSFollowing a comprehensive two-day Center for Health Outcomes and Policy Research workshop in January 2025, nursing science leaders analyzed the proceedings to examine the clinical, ethical and social implications of AI integration in nursing science. Participants – 48 experts in nursing, medicine, AI and data science, ethics and the healthcare industry – engaged in facilitated roundtable discussions between presentations, and Villarruel and fellow researchers analyzed the dialogue.They considered how AI is reshaping nursing science and outlined both its potential to transform care delivery and clinical practice risks. They said they looked at AI "both as a topic of study and as a methodological tool, while addressing its opportunities and concerns." Their report, "Artificial Intelligence and Nursing Science: Opportunities, Challenges, Implications and Guidelines," calls for nurses to participate in AI development teams that include engineers, data scientists, hospital leaders, ethicists, regulators and patients.With AI literacy among nurse educators currently limited and a lack of standardized AI education, new roles and opportunities are emerging for nursing science, they said. "Throughout this paper, we strive to demonstrate how advances in research on the application of AI to nursing science challenges may, in fact, lead to changes needed in the educational sector, and, importantly, due to the rapid adoption of AI strategies in the practice setting, how emerging AI-informed care may contribute to nursing science."Nursing science is uniquely positioned to guide AI integration because of its focus on patient-centered care and clinical workflow, and the "theoretical perspectives and epistemological contributions" must be at the table, the researchers argued.Beyond automating administrative tasks, improving clinical decision-making and enabling more personalized patient care, AI analyzes large datasets to identify patient needs and population health risks.The researchers offered five key guidelines for integrating AI into nursing science:Expand AI education in nursing to improve literacy Integrate nurses in AI developmentEnsure nurses rigorously test AI before widespread use Measure both financial and nurse workflow costsBuild ethical safeguards and transparency informed by nursesNurses' stakeholders – providers and other healthcare organizations – must assure patient privacy, informed consent, data use and bias prevention, while patients should be educated on how AI influences clinical decisions and how their personal data may be used to train or operate such systems, they noted.THE LARGER TRENDThough nurses have expressed distrust in AI, they have also rolled up their sleeves to innovate on the best possible uses of the transformative technology to advance workflows and patient care."We have seen again and again that adoption improves when nurses drive the improvements themselves," said Theresa McDonnell, DNP, RN, chief nurse executive and senior vice president at Duke University Health System and a practicing oncology nurse"Participation in pilot testing, feedback loops and workflow redesign gives staff a sense of agency," she told Healthcare IT News last year during a conversation on the pros and cons of AI in nursing. "That agency reframes AI from something being done to them into something being done with them."ON THE RECORD"Nurse scientists contribute expertise in the clinical and relational aspects of care, while AI designers and engineers bring essential technical insight," researchers said in their new report. "Such reciprocal partnerships will be essential to embed nursing science into AI development and to support the iterative innovation cycle that requires ongoing validation and trust."HIMSS is hosting the one-day AI Executive Leadership Summit in Boston on June 24, 2026, followed by its AI in Healthcare Forum June 25–26. Register separately for the two events here and here. Andrea Fox is senior editor of Healthcare IT News.Email: [email protected]Healthcare IT News is a HIMSS Media publication.