Executive Nurse Leader-Clinical Nurse Scientist Partnership for AI in Nursing Practice

OBJECTIVE: To develop a practice-oriented model for integrating artificial intelligence (AI) into nursing practice through executive nurse leader-nurse scientist dyad partnerships. BACKGROUND: AI integration in health systems is accelerating, with applications affecting nursing workflows, clinical decision making, and operational performance. However, health systems lack nursing-centered guidance for AI governance, implementation, and evaluation that aligns with clinical practice and organizational priorities. METHODS: A descriptive multiple-case study was conducted across 5 US health systems with varying organizational structures for AI. Data sources included organizational artifacts, initiative documentation, and leadership reflections. Cross-case thematic synthesis was used to identify shared leadership practices, organizational structures, and domains informing a nursing AI leadership dyad model. RESULTS: Across cases, executive nurse leaders and clinically based nurse scientists operated as complementary dyads. They jointly shaped AI strategy, implementation, evaluation, and governance. Early AI use cases focused on documentation efficiency, patient flow optimization, and clinical decision support. Within each domain, distinct but interdependent roles emerged, combining executive authority and operational alignment with scientific rigor, implementation science, and evaluation expertise. CONCLUSIONS: The proposed dyad-based leadership model provides a scalable, practice-grounded model for nursing engagement in AI. It offers health systems a structured approach to support responsible AI adoption, workforce trust, and value-driven technology investment.