Exploring Supervisors’ Readiness to Integrate AI Tools in Postgraduate Supervision in Higher Education

Abstract

The integration of artificial intelligence (AI) tools in postgraduate supervision has the potential to transform research processes by enhancing the quality of feedback, improving the efficiency of supervision, and addressing persistent challenges such as time constraints and student engagement within higher education. Despite this promise, the readiness of supervisors to adopt AI remains uneven, necessitating an exploration of their preparedness to integrate such tools. This study employs a constructivist paradigm and a qualitative research approach, guided by a generic qualitative research design. It draws on semi-structured interviews with 15 postgraduate supervisors from diverse disciplines to examine their perspectives on the integration of AI tools in postgraduate supervision. Through thematic analysis, four central themes emerged: technological literacy, institutional support, perceptions of AI, and ethical considerations, revealing the complex interplay between individual competence and institutional context. Supervisors with prior experience in digital technologies or from technology-intensive fields demonstrated higher readiness, while those from non-technical backgrounds encountered challenges due to limited digital exposure and perceived complexity. Institutional factors such as digital infrastructure, supportive policies, and professional development opportunities further influenced readiness levels. However, concerns surrounding academic rigour, ethical accountability, and workload pressures continue to constrain adoption. The chapter concludes by recommending targeted capacity-building programmes, institutional policy reforms, interdisciplinary collaboration, and enhanced supervisor–student partnerships to ensure ethical and effective AI use. Ultimately, while AI tools hold significant potential to enhance supervision efficiency and personalised support, their successful implementation requires tailored strategies responsive to diverse supervisory contexts, offering valuable insights for higher education institutions seeking to promote responsible AI integration in postgraduate supervision.