article · Open Books and Proceedings
The integration of AI (artificial intelligence) into postgraduate supervision has transformative potential for improving efficiency, communication, and research outcomes. This study explores both the opportunities and challenges associated with AI-based tools in postgraduate supervision. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, it systematically reviews peer-reviewed journal articles, conference papers, and reports to identify trends, benefits, and barriers to AI adoption. Thirty-seven studies were selected for final synthesis due to their direct relevance to the study’s research questions. The findings indicate that AI offers significant opportunities, such as personalised learning paths, automated feedback cycles, enhanced research, increased visibility, and support for supervisor-student collaboration. Nonetheless, several major obstacles to widespread AI adoption remain. These include ethical implications, data privacy concerns, technical restrictions, and limitations in user digital literacy. Resistance from supervisors and students, driven by fears of AI supplanting human interaction, is also a notable barrier. The study proposes the development of regional and national guidelines for the phased implementation of AI tools in postgraduate supervision, starting with non-intrusive applications such as administrative support and progress tracking. Concurrently, training programmes for supervisors and students should be introduced to enhance digital literacy and cultivate a favourable attitude towards AI tools. Additionally, institutions must develop policies to address ethical issues and create a framework for human-AI collaboration that complements traditional supervision practices. This study advances scholarly understanding of AI’s evolving role in postgraduate student supervision and provides actionable insights for institutions seeking to utilise AI effectively.
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DOI: 10.38140/obp4-2026-13
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