Navigating Ethical, Legal, and Social Implications of Artificial Intelligence in Advanced Practice Nursing

Background: The rapid integration of artificial intelligence (AI) into health care systems offers new opportunities for advanced practice registered nurses (APRNs). However, this innovation also introduces a variety of concerns regarding ethical and responsible use and implications for patient care, privacy, data integrity, clinical systems, and professional practice. Ethical implications associated with the integration of AI in health care require critical examination by APRNs. Objective: This article examines ethical, legal, and social implications of integrating AI in advanced practice nursing. Grounded in the American Nurses Association Code of Ethics and the American Association of Colleges of Nursing Essentials, it provides practical strategies for APRNs to engage with AI technologies in ways that uphold core values such as patient autonomy, equity, trust, and human connection. Methods: A narrative review of the literature was conducted, supplemented by an analysis of current AI tools and illustrative case studies, to identify ethical considerations and educational strategies for implementing AI in advanced practice nursing. Real-world examples, including clinical decision support systems, predictive analytics, and AI-assisted documentation, were examined to highlight the potential benefits and risks of AI integration. Results: AI tools can enhance diagnostic accuracy, streamline documentation, and improve patient care. However, ethical risks include biased algorithms, privacy breaches, and depersonalized care. Case examples from inpatient emergency care, outpatient primary care, and academic settings illustrate how APRNs can mitigate these risks through transparent communication, interdisciplinary collaboration, and targeted technology training. Key themes that emerged from the literature highlight the potential of AI to enhance diagnostic accuracy, streamline clinical documentation, and improve patient education. However, significant ethical concerns were also identified, including algorithmic bias, data privacy risks, and the potential for depersonalized care. Conclusions: APRNs will play a critical role in ensuring that AI is used ethically, responsibly, and effectively. By actively engaging in implementation efforts, they help balance technological innovation with preserving human interaction and clinical judgment. Implications for Nursing: APRNs must take the lead in driving the ethical integration of artificial intelligence by shaping policies, advancing education, and implementing clinical strategies that protect patient safety, promote equity, and uphold professional values. To lead effectively in this rapidly changing landscape, they must actively develop AI competencies, engage in interdisciplinary collaboration, and advocate for responsible, patient-centered innovation in practice.