Neonatal nurses’ experiences with generative AI in clinical decision-making: a qualitative exploration in high-risk nicus

Background Neonatal nurses in high-risk Neonatal Intensive Care Units (NICUs) navigate complex, time-sensitive
clinical decisions where accuracy and judgment are critical. Generative artificial intelligence (AI) has emerged as
a supportive tool, yet its integration raises concerns about its impact on nurses’ decision-making, professional
autonomy, and organizational workflows.
Aim This study explored how neonatal nurses experience and integrate generative AI in clinical decision-making,
examining its influence on nursing practice, organizational dynamics, and cultural adaptation in Saudi Arabian NICUs.
Methods An interpretive phenomenological approach, guided by Complexity Science, Normalization Process
Theory, and Tanner’s Clinical Judgment Model, was employed. A purposive sample of 33 neonatal nurses participated
in semi-structured interviews and focus groups. Thematic analysis was used to code and interpret data, supported
by an inter-rater reliability of 0.88. Simple frequency counts were included to illustrate the prevalence of themes but
were not used as quantitative measures. Trustworthiness was ensured through reflexive journaling, peer debriefing,
and member checking.
Results Five themes emerged: (1) Clinical Decision-Making, where 93.9% of nurses reported that AI-enhanced
judgment but required human validation; (2) Professional Practice Transformation, with 84.8% noting evolving role
boundaries and workflow changes; (3) Organizational Factors, as 97.0% emphasized the necessity of infrastructure,
training, and policy integration; (4) Cultural Influences, with 87.9% highlighting AI’s alignment with family-centered
care; and (5) Implementation Challenges, where 90.9% identified technical barriers and adaptation strategies.
Conclusions Generative AI can support neonatal nurses in clinical decision-making, but its effectiveness depends on
structured training, reliable infrastructure, and culturally sensitive implementation. These findings provide evidencebased
insights for policymakers and healthcare leaders to ensure AI integration enhances nursing expertise while
maintaining safe, patient-centered care.