Nurse Leadership and Artificial Intelligence Integration in Nursing Workforce Management: A Scoping Review.

Journal: Journal of advanced nursing
Published Date:

Abstract

AIM: To systematically map evidence on the application of AI systems in nursing workforce management, with a targeted focus on the role of nurse leaders. DESIGN: A scoping review. DATA SOURCES: A comprehensive literature search was conducted across six databases: CINAHL, IEEE Xplore, MEDLINE/PubMed, PsycINFO, Scopus, and Web of Science. Studies published in English between January 2015 and December 2024 were included. REVIEW METHODS: Studies that focused on AI in the context of nursing leadership or workforce management were included, while those examining AI in healthcare but without a specific focus on nursing leadership/management were excluded. RESULTS: A total of 1014 articles were retrieved, and 12 were included in this review. Eleven articles were published between 2022 and 2024. The findings show that AI systems in nursing management have been applied in several domains, including workforce planning, nursing safety, and staff prediction models. Although studies highlight the positive optimising potential of AI systems, others underscore the ethical implications of AI with respect to nursing leadership and management, particularly regarding discriminatory stereotypes in AI-generated nurse imagery and the critical role of nurse leaders in ethical AI integration in care. Only one study identified important barriers to AI integration, underlining the need for enhanced AI training for nurse managers. CONCLUSIONS: Findings suggests that the application of AI systems in nursing leadership/management is in its early phases, with limited engagement of nurses in innovating and implementing AI-enabled systems. A substantial problem related to AI adoption remains-AI integration hinges on addressing the readiness and engagement levels of nurse leaders early on in the process of AI systems' innovation. To promote AI integration, AI competency, trust, and optimisation in healthcare, developing a basic working understanding of AI together with a culture of multidisciplinary AI development teams that include nurses are potentially proactive strategies. REPORTING METHOD: This study adhered to the PRISMA-ScR guideline. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Authors

  • Frank Kiwanuka
    Department of Nursing Science, Faculty of Health Sciences, University of Eastern Finland, Kuopio.
  • Simone Stevanin
    Department of Nursing Science, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.
  • Younas Ahtisham
    Faculty of Nursing, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada.
  • Brenda Owusu
    University of Miami School of Nursing & Health Studies, Coral Gables, Florida, USA.
  • Anu Nurmeksela
    Department of Nursing Science, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.
  • Tarja Kvist
    Department of Nursing Science, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.

Keywords

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