[Care Transformation: The AI- and Data-Driven Shift From Reactive to Proactive and Predictive Care].

With global population aging and the increasing prevalence of chronic diseases, the traditional reactive medical model, which focuses on post-illness management, is increasingly inadequate for addressing the structural challenges currently facing healthcare systems. With Taiwan now an aging society, the long-term care needs arising from disability, dementia, and multiple comorbidities further underscore the urgent need to transform existing models of care. This article begins by examining the necessity of care transformation driven by artificial intelligence (AI) and data, and then examines the emergence of "proactive care" and "predictive care" and related trends and empirical research. This article also examines how the nursing profession may evolve away from its reactive role and into a key participant in risk identification, health management, and predictive decision-making to strengthen person-centered continuity of care. Finally, the authors propose that a goal of future nursing education and system design should be to enhance data literacy, ethical governance, and interdisciplinary collaboration concurrently to promote the sustainable development of predictive care within Taiwan's healthcare system.