Artificial intelligence in advanced practice nursing education: Opportunities and challenges

Abstract

ABSTRACT Artificial intelligence (AI) is transforming health care delivery and education, offering both opportunities and challenges. Because AI tools become more integrated into clinical practice, educators are exploring their potential to enhance learning, improve decision making, and prepare future providers for technology-rich environments. However, the use of AI in health care education raises concerns about academic integrity, overreliance, and the risk of AI-generated misinformation, known as “hallucinations.” These inaccuracies pose significant challenges for students building foundational knowledge. Additionally, practical issues such as implementation costs, Health Insurance Portability and Accountability Act compliance, data privacy, and inherent biases in AI systems must be addressed. This article discusses the integration of AI into advanced practice nursing education using the Technological Pedagogical Content Knowledge (TPACK) framework. This framework emphasizes the interconnectedness of technology, pedagogy, and content knowledge, guiding educators in designing assignments that promote critical thinking and prepare students for real-world clinical practice. The evolution of an AI-based assignment for advanced practice nursing students is detailed, highlighting ethical considerations, interdisciplinary collaboration, and the development of clinical reasoning skills. By integrating AI into nursing education, we can ensure that advanced practice registered nurses (APRNs) are well-prepared to meet the demands of modern health care environments. This integration supports essential competencies, aligns with the 2021 American Association of Colleges of Nursing Essentials, and addresses the increasing complexity of patient care. Moreover, it equips APRNs with the skills needed to leverage AI effectively, fostering a culture of continuous learning and adaptation.