Background: Generative artificial intelligence (GenAI) offers new forms of academic support but also complicates judgments about authorship, learning authenticity, fairness, and professional formation in nursing education. This study explored the ethical dilemmas experienced by nursing faculty when responding to students’ use of GenAI for academic requirements.
Methods: A descriptive phenomenological study was conducted with 15 nursing faculty purposively recruited from four higher education institutions in Lanao del Sur, Philippines. Semi-structured interviews were completed from March to May 2025 and analyzed using Colaizzi’s seven-step method. Two researchers independently coded all transcripts, reconciled interpretations by consensus, and used NVivo 14 to organize the analytic record. Credibility, dependability, confirmability, and transferability were addressed through saturation, field notes, selected-participant member checking, independent coding, expert review and pilot testing of the guide, an auditable coding structure, and contextual description.
Results: Four themes and nine subcategories were identified: integrity versus innovation (AI as a learning scaffold and a threat to critical engagement; authenticity as evidence of learning); ambiguity of ethical boundaries (absence of shared institutional standards; ambiguous classification and procedural fairness); professional accountability and role modelling (academic integrity as preparation for professional practice; faculty responses as ethical role modelling); and the call for ethical literacy and institutional support (faculty preparedness and shared interpretation; institutional governance and common standards; ethical literacy for responsible integration).
Conclusion: Faculty did not describe GenAI as inherently acceptable or unacceptable; rather, ethical judgment depended on whether its use supported learning, was transparently disclosed, and was evaluated under fair institutional rules. Nursing programs should establish explicit, assessment-specific GenAI guidance, due-process procedures, and continuing ethical-AI education for faculty and students.