Academic Identity in the Age of Generative AI: A Qualitative Pilot Study of Doctoral and Higher-Degree Researchers

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Authors: Aliz Ovlachi
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Abstract

Doctoral training is not merely the production of a thesis; it is a developmental process through which candidates come to experience themselves as independent researchers. Central to this process is the internalisation of authorship, epistemic ownership, and confidence that one’s ideas, syntheses, and conceptual insights are genuinely one’s own. The rapid integration of generative artificial intelligence (AI) tools into academic work has introduced a novel tension into this identity-formation process. While AI tools may function as cognitive supports - assisting with executive load, structure, and synthesis - they may simultaneously evoke unease, imposter feelings, or concerns about authenticity and academic legitimacy. Anecdotal reports from doctoral students suggest that AI-assisted work may become a new “breeding ground” for imposter feelings, particularly when internal distinctions between assistance and authorship feel blurred. Conversely, some students experience AI as a benign or even empowering scaffold that enables deeper thinking rather than replacing it. Importantly, responses to AI use may vary not only by academic stage, but also by intentional avoidance of AI and by generational cohort, with younger academics potentially holding different normative assumptions about digital assistance than their senior peers. Despite the rapid uptake of generative AI in higher education, there is currently limited empirical research examining how AI use - or deliberate non-use - shapes academic identity, authorship experience, and feelings of legitimacy among higher-degree researchers. This exploratory study aims to address this gap through a small-scale qualitative pilot inquiry. Project Status: implementation (ethics approved; transition from conceptual design to active recruitment/data collection).

Fields of Study & Subjects

Doctoral Education Challenges and Solutions Academic integrity and plagiarism Artificial Intelligence in Education

Publication details

Publication date
1 January 2026
Document type
Preprint