Artificial Intelligence in Nursing Care:
Opportunities, Challenges, and Future Directions
Abstract
Artificial Intelligence (AI) is emerging as a transformative force in nursing care, offering innovative solutions to enhance patient safety, improve care quality, and alleviate the growing workload of nursing professionals. This presentation shows a comprehensive overview of current advancements, challenges, and future pathways for AI integration in nursing practice. Drawing on a bibliometric analysis of 490 nursing-related AI studies (1995–2025), we observe a maturing research field, shifting from exploratory technological assessments toward practical, evidence-based implementation strategies, with the United States leading in global collaboration and publication output. Key applications highlighted include AI-supported fall prevention systems such as SAVE & SAFE, which combines sensor-based monitoring, automated fall detection, and coordinated care models in acute geriatric settings, demonstrating potential to reduce both patient risk and nurse workload. Furthermore, longitudinal field studies using privacy-preserving depth sensors in nursing homes reveal the feasibility of AI-driven activity recognition—such as mobility tracking and fall risk prediction—based on over 58,000 hours of unobtrusive data, enabling personalized, preventive care. Despite these promising developments, significant barriers remain, including poor data quality, inadequate digital infrastructure, insufficient nurse involvement in design, and ethical concerns around transparency and privacy. To address these challenges, the AI Nursing Care Readiness Assessment (AINCRA) tool was developed, offering a structured, multidimensional framework across regulatory, technical, processual, social-ethical, and community-building dimensions to guide interdisciplinary teams through the AI lifecycle. The symposium underscores that sustainable AI integration in nursing requires participatory design, workforce upskilling, robust real-world validation, and a steadfast commitment to equity and person-centered care. Together, these contributions chart a path toward.
Short Biography
Prof., Dr. Karin Wolf-Ostermann is Professor of Health Care Research at the University of Bremen and Head of the Health Care Research Department at the Institute for Public Health and Nursing Research (IPP). Her academic background is in statistics and theoretical medicine, and she received her doctoral degree in applied statistics from TU Dortmund. Her research focuses on health services and nursing research, evidence-based nursing, quality of care, care for people with dementia, digitalisation and artificial intelligence in nursing care, as well as quantitative and mixed-methods research. Before joining the University of Bremen in 2014, she was Professor of Social and Nursing Research at Alice Salomon University of Applied Sciences in Berlin.
