A scoping review of emerging benefits and challenges of generative artificial intelligence in postgraduate research supervision

The integration of generative artificial intelligence (GenAI) tools is rapidly transforming higher education. While these technologies offer promising opportunities to enhance research practices, they also raise essential challenges and ethical concerns. This scoping review systematically mapped the current literature on the emerging benefits and challenges of GenAI in postgraduate research supervision. Using the five-stage framework proposed by Arksey and O’Malley, we searched key databases, including Scopus, Web of Science, EBSCO, and Google Scholar, as well as grey literature sources. Searches were limited to publications from January 2018 to May 2025 (inclusive); the final search was completed on 05 May 2025. Studies and reports addressing the use, benefits, challenges, and ethical concerns of GenAI in postgraduate supervision were included. Data were extracted, charted, and thematically analysed to synthesise insights across contexts. Seventeen studies that met the inclusion criteria, published from 2018 to 2025, were included. The findings revealed that GenAI reduces supervisor workload by performing time-consuming administrative and editorial tasks, such as basic proofreading, grammar correction, and formatting, thereby allowing supervisors to focus on higher-level intellectual guidance. However, challenges include supervisors’ limited experience with GenAI, unclear institutional policies and guidelines, and ethical concerns, including academic integrity, transparency, bias, and data privacy, which are exacerbated when students over-rely on AI or fail to disclose its use. While GenAI holds significant potential to complement postgraduate supervision, it cannot replace the relational, disciplinary, and interpretive expertise of human supervisors. Effective integration of GenAI in postgraduate research supervision requires institutional policy frameworks, supervisor capacity-building, and strengthened ethical governance to ensure responsible, equitable, and high-quality postgraduate research.

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Publication Details

Journal
Discover Artificial Intelligence
Published
2026-05-29
DOI
https://doi.org/10.1007/s44163-026-01476-w
Primary Topic
Doctoral Education Challenges and Solutions
Type
article
Field-Weighted Citation Impact
0.00
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article

A scoping review of emerging benefits and challenges of generative artificial intelligence in postgraduate research supervision

D. Gumede, P. R. Gumede
Discover Artificial Intelligence
Doctoral Education Challenges and Solutions
article

A scoping review of emerging benefits and challenges of generative artificial intelligence in postgraduate research supervision

D. Gumede, P. R. Gumede
article en

Abstract

The integration of generative artificial intelligence (GenAI) tools is rapidly transforming higher education. While these technologies offer promising opportunities to enhance research practices, they also raise essential challenges and ethical concerns. This scoping review systematically mapped the current literature on the emerging benefits and challenges of GenAI in postgraduate research supervision. Using the five-stage framework proposed by Arksey and O’Malley, we searched key databases, including Scopus, Web of Science, EBSCO, and Google Scholar, as well as grey literature sources. Searches were limited to publications from January 2018 to May 2025 (inclusive); the final search was completed on 05 May 2025. Studies and reports addressing the use, benefits, challenges, and ethical concerns of GenAI in postgraduate supervision were included. Data were extracted, charted, and thematically analysed to synthesise insights across contexts. Seventeen studies that met the inclusion criteria, published from 2018 to 2025, were included. The findings revealed that GenAI reduces supervisor workload by performing time-consuming administrative and editorial tasks, such as basic proofreading, grammar correction, and formatting, thereby allowing supervisors to focus on higher-level intellectual guidance. However, challenges include supervisors’ limited experience with GenAI, unclear institutional policies and guidelines, and ethical concerns, including academic integrity, transparency, bias, and data privacy, which are exacerbated when students over-rely on AI or fail to disclose its use. While GenAI holds significant potential to complement postgraduate supervision, it cannot replace the relational, disciplinary, and interpretive expertise of human supervisors. Effective integration of GenAI in postgraduate research supervision requires institutional policy frameworks, supervisor capacity-building, and strengthened ethical governance to ensure responsible, equitable, and high-quality postgraduate research.

Discover Artificial Intelligence
Mangosuthu University of Technology (ZA), Durban University of Technology (ZA)
Quality Education
Openalex Percentile: Top 4%
Doctoral Education Challenges and Solutions
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