Reshaping the doctoral journey in the AI era
TL;DR
The findings suggest that AI is intertwined with doctoral education not only as a tool for efficiency but also as part of a broader socio-technical and identity-forming process.
Abstract
This article systematically reviews how artificial intelligence (AI) systems, particularly generative AI (GenAI), are reshaping the doctoral journey. Unlike existing reviews that examine AI in higher education broadly, this review positions doctoral candidates as emerging scholars whose AI use intersects with learning, research, academic writing, authorship, and early knowledge production. Drawing on Web of Science Core Collection records from 1998 to 2026, the study followed preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines and retained 28 studies from an initial pool of 185 records. VOSviewer-based co-occurrence and co-citation analyses were integrated with full-text reading to identify five synthesized themes: AI as academic infrastructure, AI-mediated restructuring of doctoral practices, technology acceptance and negotiation, ethical risks and academic integrity, and wellbeing, adaptation, and support. The findings suggest that AI is intertwined with doctoral education not only as a tool for efficiency but also as part of a broader socio-technical and identity-forming process. The review contributes a doctoral identity-centered synthesis of how AI intersects with research practices, authorship, academic voice, supervision, academic integrity, wellbeing, and doctoral support.
