Reimagining nursing education: Leveraging competency-based education, artificial intelligence, and simulation for a diverse and practice-ready workforce

Abstract

BACKGROUND: Nurses represent the largest share of the U.S. health-care workforce and are central to improving population health. Transforming nursing education into a responsive, adaptive, competency-based system is essential to prepare a diverse, practice-ready workforce. PURPOSE: This concept paper presents a vision for integrating artificial intelligence (AI), competency-based education (CBE), and simulation to personalize learning, enhance skill acquisition, and foster cultural respect in nursing education. METHODS: We propose shifting from rigid, time-bound curricula to flexible, competency-driven pathways that allow learners to progress at their own pace. Hypothetical student and faculty scenarios illustrate how these innovations can accommodate diverse life circumstances and learning styles. DISCUSSION: This approach expands access for underrepresented groups-including adult learners and those with caregiving responsibilities-while cultivating a workforce equipped to deliver community-oriented care and address social determinants of health such as housing, education, and nutrition. CONCLUSIONS: By embracing AI, CBE, and simulation, nursing education can be reimagined to build a diverse, inclusive, and practice-ready workforce positioned to advance health equity and improve population health outcomes across the United States.

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