The algorithmic turn of society in the second decade of the 21st century has been marked by the ubiquity of artificial intelligence (AI) in many aspects of human life, including healthcare. Evidence indicates the increasing use of diverse configurations of AI systems—such as machine learning algorithms, natural language processing, neural networks and generative AI—for applications ranging from biomedical imaging and predictive analysis to virtual assistants, robotics, telehealth and drug discovery (Bekbolatova et al., 2024; Olawade et al., 2024). In nursing specifically, AI has been used for functions such as health assessment, nursing care planning, intelligent tutoring, telehealth services and electronic health record management (Ruksakulpiwat et al., 2024; Choi et al., 2023; Hwang et al., 2022). The widespread integration of AI in healthcare systems globally shows no signs of slowing down; hence, nurses must expand their skillsets to include AI-specific competencies. Likewise, nurse education institutions are tasked to train nursing students and professionals for these emerging demands and contribute to research that ensures the profession remains responsive to the dynamic landscape of AI-enabled healthcare.

While these AI-driven advancements hold significant promise for healthcare delivery and education, scholars and practitioners have raised critical concerns about the potential risks associated with these technologies. Beyond safety issues, such as the generation of unreliable or fictitious results, cybersecurity threats, provider unpreparedness and the erosion of human-centered care (Wubineh et al., 2024, Moulaei et al., 2024, Mennella et al., 2024), other significant challenges include data biases and technological inequalities that may exacerbate existing health disparities (Ueda et al., 2023). Mainstream AI systems and practices risk undermining the health-related human rights of marginalized individuals and groups by introducing additional barriers to accessing empowering, equitable and scientifically sound healthcare (Business for Social Responsibility, 2023). Professionals and educators across health disciplines, including nursing, are therefore called on to advocate for the responsible deployment of AI in practice, ensuring it upholds clients’ human rights to health.

Following the Human Rights-Based Approach (HRBA), governance actors have a duty to establish structures and processes that respect, uphold and protect citizens' rights to health, safety and autonomy in an increasingly AI-driven world (Türk, 2023; Business for Social Responsibility, 2023). As designated advocates for the right to health, nurses play a critical role in shaping healthcare AI governance to hold AI health innovators and providers accountable while empowering clients to make informed decisions and access effective, equitable care (International Council of Nurses, 2011; American Nurses Association, 2022). While most nursing scholarship focuses on nurses' professional responsibilities in ensuring the ethical implementation of AI in healthcare (Badawy et al., 2024, Ronquillo et al., 2021), little attention has been given to the role of nursing academic institutions as AI governance actors—institutions that not only train future nursing professionals but also engage in research, advocacy and policymaking in healthcare. Addressing this gap, this discussion paper unfolds in four parts. First, it explains the philosophical approaches used to develop the normative framework for stakeholdership. Second, it describes the interconnected layers of the healthcare AI governance ecosystem. Third, it conceptualizes the domains and modalities of AI governance stakeholdership in the context of nursing academia. Finally, it applies an HRBA to propose an integrated framework for nursing academia’s stakeholdership to orient AI governance ecosystems toward a fuller realization of the right to health.