Journal of nursing management · 2026
Value Co-Creation Between Nurses and Generative Artificial Intelligence: A Grounded Theory Study.
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Jia Yingying, Zhu Wei, Cai Yan, Jiang Yan
Аннотация
BACKGROUND: The role of generative artificial intelligence (GenAI) in nursing is increasingly shifting from a support tool toward a collaborative partner. However, the mechanisms underlying nurse-GenAI value co-creation (N-GAIVC) remain undertheorized.
AIM: To develop a theoretical framework for N-GAIVC.
METHODS: This study used a Straussian grounded theory approach. Between January and April 2026, 27 clinical nurses and nurse managers from hospitals across China were recruited using purposive, snowball, and theoretical sampling. Semistructured in-depth interviews and online textual data from Chinese social media platforms were analyzed. Data analysis followed the constant comparative method, with iterative open, axial, and selective coding conducted to generate and refine categories. Theoretical saturation was assessed through supplementary interviews and considered achieved when no new categories or relationships emerged.
RESULTS: A theoretical framework of nurse-GenAI value co-creation was developed, comprising three integrative domains. Situated engagement conditions included engagement drivers, appraising GenAI fit, and safe-use scaffolding. Professional orchestration in practice involved selective delegation, prompting, verification, contextualization, feedback, peer diffusion, and implementation embedding. Conditional value outcomes encompassed both co-creation and destruction and recursively shaped subsequent engagement, safeguards, and nurse-GenAI co-evolution.
CONCLUSIONS: Nurse-GenAI value co-creation is a situated, professionally orchestrated, and adaptive process. Value arises not from GenAI use alone, but from nurses' appraisal of task fit and risk, active orchestration of GenAI contributions, and alignment with nursing expertise, human-centered care, and organizational safeguards.
IMPLICATIONS FOR NURSING MANAGEMENT: The framework provides a practical roadmap for responsible GenAI integration in nursing practice. Nurse managers should assess task suitability and risk; strengthen nurses' GenAI literacy and critical evaluation; establish training, governance, accountability, and validation mechanisms; and support nurse-led feedback and workflow embedding. These measures can enhance value while mitigating overreliance, added workload, and erosion of relational and professional capabilities.
AIM: To develop a theoretical framework for N-GAIVC.
METHODS: This study used a Straussian grounded theory approach. Between January and April 2026, 27 clinical nurses and nurse managers from hospitals across China were recruited using purposive, snowball, and theoretical sampling. Semistructured in-depth interviews and online textual data from Chinese social media platforms were analyzed. Data analysis followed the constant comparative method, with iterative open, axial, and selective coding conducted to generate and refine categories. Theoretical saturation was assessed through supplementary interviews and considered achieved when no new categories or relationships emerged.
RESULTS: A theoretical framework of nurse-GenAI value co-creation was developed, comprising three integrative domains. Situated engagement conditions included engagement drivers, appraising GenAI fit, and safe-use scaffolding. Professional orchestration in practice involved selective delegation, prompting, verification, contextualization, feedback, peer diffusion, and implementation embedding. Conditional value outcomes encompassed both co-creation and destruction and recursively shaped subsequent engagement, safeguards, and nurse-GenAI co-evolution.
CONCLUSIONS: Nurse-GenAI value co-creation is a situated, professionally orchestrated, and adaptive process. Value arises not from GenAI use alone, but from nurses' appraisal of task fit and risk, active orchestration of GenAI contributions, and alignment with nursing expertise, human-centered care, and organizational safeguards.
IMPLICATIONS FOR NURSING MANAGEMENT: The framework provides a practical roadmap for responsible GenAI integration in nursing practice. Nurse managers should assess task suitability and risk; strengthen nurses' GenAI literacy and critical evaluation; establish training, governance, accountability, and validation mechanisms; and support nurse-led feedback and workflow embedding. These measures can enhance value while mitigating overreliance, added workload, and erosion of relational and professional capabilities.