Artificial intelligence and nursing science: Opportunities, challenges, implications, and guidelines.

In the era of artificial intelligence (AI), nursing science has the potential to enable transformative change in healthcare driven by the nursing clinical focus, its deep commitment to improving patient and family outcomes, its legacy of compassion, and tradition of creative innovation. Inspired by...

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Publicado en:Nursing Outlook Vol. 74; no. 3
Autores principales: Demiris, George, Oh, Oonjee, Ulrich, Connie M., Bin You, Sang, Cho, Hannah, Villarruel, Antonia M.
Formato: Journal Article
Publicado: Elsevier B.V. May2026
Acceso en línea:Ver este registro en EBSCOhost
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      dt: May2026
      vid: 74
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      pub: Elsevier B.V.
      place: New York, New York
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        194367386
        10.1016/j.outlook.2026.102770
        194367386
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        atl: Artificial intelligence and nursing science: Opportunities, challenges, implications, and guidelines.
      aug:
        au:
          Demiris, George
          Oh, Oonjee
          Ulrich, Connie M.
          Bin You, Sang
          Cho, Hannah
          Villarruel, Antonia M.
        affil: School of Nursing, University of Pennsylvania, Philadelphia, PA
      sug:
        subj:
          Artificial Intelligence Utilization
          Nursing Science
          Nursing Informatics
          Ethics, Nursing
          Education, Nursing
          Commitment
          Outcomes (Health Care)
          Compassion
          Diffusion of Innovation
          Education, Interdisciplinary
          Seminars and Workshops
          Data Science
          Bioethics
          Health Care Industry
          Implementation Science
          Collaboration
          Research Nurses
      ab: In the era of artificial intelligence (AI), nursing science has the potential to enable transformative change in healthcare driven by the nursing clinical focus, its deep commitment to improving patient and family outcomes, its legacy of compassion, and tradition of creative innovation. Inspired by discussions from a 2-day interdisciplinary workshop with experts in nursing, medicine, informatics and data science, bioethics, and the healthcare industry, this white paper provides guidelines for integrating AI in nursing science. Workshop proceedings were transcribed and analyzed. We examined the clinical, ethical, and social implications of AI integration in nursing science, considering AI both as a topic of study and as a methodological tool, while addressing its opportunities and concerns. Drawing on these insights, we recommend several future directions of nursing science. Key priorities include integrating AI literacy as core components of graduate nursing education, expanding nursing scientists' participation in interdisciplinary AI working groups, applying rigorous implementation science frameworks to optimize AI deployment, and advocating for the interests of patients and families within this evolving landscape. We also discuss the importance of sustained collaboration with industry partners. Nurse scientists contribute expertise in the clinical and relational aspects of care, while AI designers and engineers bring essential technical insight. 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. • The application of artificial intelligence (AI) to nursing science call for changes in nursing education especially given the rapid adoption of AI in the practice setting. • The introduction of AI in Nursing Science calls for integrating AI literacy into graduate nursing education, applying rigorous implementation science frameworks to optimize AI deployment. • Reciprocal partnerships between nurse scientists and other disciplines as well as industry will be essential to support the iterative AI innovation cycle that requires ongoing validation and trust.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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