Exploring the Accountability and Perception on Artificial Intelligence Among Nurses in Selected Hospitals in Bulacan

The rapid integration of Artificial Intelligence (AI) in healthcare necessitates an examination of how nurses navigate accountability and perception toward these technologies. This qualitative-phenomenological study explored the lived experiences of nine (9) staff nurses from selected hospitals in Bulacan, Philippines, regarding AI accountability and perception. Semi-structured interviews were conducted and analyzed through thematic analysis. Findings revealed two overarching dimensions: (1) Accountability, encompassing ethics, potential incorrect judgments, man-over-machine autonomy, effects on public dignity, public confidence, and inherent biases in testing; and (2) Perceptions, including perceived usefulness, perceived ease of use, social influence, facilitating conditions, and self-efficacy. Results indicated that nurses affirmed human primacy in clinical decision-making, expressed heightened concern for data privacy and patient dignity, and recognized AI's potential to enhance efficiency while cautioning against overdependence. Accountability gaps, particularly the inability to hold AI responsible for errors, were consistently highlighted. Institutional support, structured training, and robust data governance emerged as critical facilitating factors for responsible AI adoption. Anchored in Rogers' Diffusion of Innovations Theory, this study underscores the need for an integrated approach balancing technological advancement with ethical governance and human-centered nursing care in the Philippine healthcare context.