The healthcare sector is facing a serious crisis in terms of nursing workforce due to the increasing prevalence of chronic diseases, extended life expectancy, and growing care needs. Traditional workforce management methods are insufficient in meeting the requirements of speed, predictive capacity, and scalability, especially in large and dynamic hospital systems. In this context, artificial intelligence technologies are emerging as a transformative tool that strengthens strategic and data-driven decision-making processes in nursing workforce management. Predictive analytics and machine learning algorithms offer high accuracy in personnel planning, scheduling, workload estimation, and early detection of burnout risk. Natural language processing techniques support performance evaluation and psychosocial status analysis, providing managers with objective and continuous data. AI-based optimization and dynamic assignment systems ensure continuity of care and patient safety by responding quickly to real-time clinical changes. In addition, AI-supported personalized training, career guidance, and psychosocial support mechanisms increase nurses' professional development and job satisfaction, reducing the risk of burnout. Artificial intelligence contributes to workforce sustainability by offering proactive strategies for candidate fit and talent management in recruitment and retention processes. In this context, artificial intelligence transforms nursing workforce management from merely an operational process into a strategic, fair, and evidence-based approach.

This review aims to examine the potential and areas of application of artificial intelligence technologies in nursing workforce management in light of the literature.