How do PhD Students Use Generative AI? Reflections on Practice and Ethics

Generative AI (GenAI) has rapidly moved from novelty to ubiquity, reshaping how doctoral students approach learning, research, and career preparation. Yet while universities and the public often frame debates around undergraduate use, comparatively little attention has been given to PhD students despite their dual role as learners and future scholars. In this paper, we reflect on our experiences as PhD students using GenAI across coursework, qualifying exams, thesis research, teaching, and the job market. Drawing on these experiences, we highlight both the opportunities GenAI provides—for efficiency, conceptual clarity, and skill development—and the ethical challenges it raises, including concerns about academic integrity, cognitive outsourcing, disclosure, and employability beyond academia. Our reflections emphasize that GenAI use is not uniform: it varies with disciplinary context, institutional policies, and students’ levels of development. We argue that GenAI is no longer peripheral to doctoral education but central to its practice, and the challenge ahead is how it can be integrated responsibly to support learning, uphold integrity, and prepare graduates for an evolving academic and professional landscape.