Integrating Artificial Intelligence Technologies into Health Workforce Education: A Scoping Review of Digital Health Tools in Nursing Curricula - Dr S Kanaka Lakshmi (Qualitative and Quantitative Research Center, 2026)
The rapid expansion of digital health demands a transformation in health workforce education, yet the mapping of Artificial Intelligence (AI) modalities and their structural integration in nursing curricula remains fragmented. To address this gap, this scoping review aimed to systematically map global AI applications in nursing education from 2020 to 2026, offering a distinct contribution by synthesizing pedagogical innovations and structural implementation barriers to guide future curriculum design. Guided by the PRISMA-ScR framework, a systematic screening was conducted across Scopus, PubMed, and CINAHL databases. Results mapped five core AI technologies, including intelligent tutoring systems, virtual patient simulations, adaptive platforms, natural language processing, and predictive analytics, which significantly enhance students' clinical reasoning, critical thinking, and professional competence without compromising patient safety. However, global adoption is geographically skewed and heavily hindered by deficient technological infrastructure, high financial costs, ethical data privacy issues, and a pronounced gap in faculty digital readiness. This study concludes that successful AI integration must shift from ad-hoc usage toward structured, policy-driven curricular frameworks. Ultimately, this review provides a critical strategic benchmark for educational administrators and policy makers to standardize digital health competencies, mitigate regional educational disparities, and safely future-proof the next generation of the healthcare workforce.