Task augmentation, automation, and hybridization in nursing: A conceptual framework for artificial intelligence-integrated care delivery.

The integration of artificial intelligence (AI) in healthcare is rapidly reshaping nursing roles, functions, and tasks. However, there is no established framework to guide understanding of how AI interacts with nursing practice. To propose a conceptual framework, grounded in sociotechnical systems t...

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Publicado en:Nursing Outlook Vol. 73; no. 5
Autores principales: Barrett, Joshua J., Jones, Cheryl B.
Formato: Journal Article
Publicado: Elsevier B.V. Sep2025
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2025
      vid: 73
      iid: 5
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      pub: Elsevier B.V.
      place: New York, New York
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        189477555
        10.1016/j.outlook.2025.102524
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        atl: Task augmentation, automation, and hybridization in nursing: A conceptual framework for artificial intelligence-integrated care delivery.
      aug:
        au:
          Barrett, Joshua J.
          Jones, Cheryl B.
        affil: University of North Carolina at Chapel Hill, School of Nursing, Chapel Hill, NC
      sug:
        subj:
          Task Performance and Analysis
          Nursing Practice
          Automation
          Conceptual Framework
          Artificial Intelligence
          Health Care Delivery, Integrated
          Systems Theory
          Organizational Culture
          Workflow
          Ethics, Nursing
          Support, Psychosocial
          Curriculum Development
      ab: The integration of artificial intelligence (AI) in healthcare is rapidly reshaping nursing roles, functions, and tasks. However, there is no established framework to guide understanding of how AI interacts with nursing practice. To propose a conceptual framework, grounded in sociotechnical systems theory and task-technology fit, that illustrates the potential of AI to augment, automate, and hybridize nursing work. An exploratory review of literature across nursing, organizational theory, information systems, and management was conducted to identify patterns related to task characteristics, human–technology interaction, and organizational context. The framework links AI interaction types (augmentation, automation, and hybridization) with task categories (manual, cognitive, and routine) and organizational factors. It demonstrates that routine tasks are more amenable to automation, while complex tasks are better suited to augmentation or hybridization, depending on how governance structures shape AI adoption. This framework offers nurse leaders, educators, and clinicians a structured approach to anticipate AI's impact on nursing practice, align workflows, support ethical implementation, and inform curricula that prepare nurses for evolving AI–clinical care dynamics. • Categorizes nurse-AI interactions: augmentation, automation, hybridization. • Shows how task type (cognitive, manual, routine) influences AI applicability. • Emphasizes organizational governance role in AI implementation and delegation. • Provides practical tool for nurse leaders to align AI with care delivery goals.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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