Sustainable Mentorship Practices: Designing Frameworks That Blend AI Efficiencies with Human Intuition

Abstract

The integration of Artificial Intelligence (AI) into academic mentoring has the potential to transform conventional approaches by increasing efficiency, availability, and accuracy. However, the challenge lies in ensuring that such advances do not supplant the essential human factors of empathy, intuition, and contextual understanding. This chapter aims to design a sustainable framework that combines AI-driven effectiveness with human-centred mentorship practices, thereby achieving an optimal equilibrium between technological advancement and personalised guidance. To this end, a qualitative methodological approach was employed, with data collected through semi-structured interviews with ten academic mentors and fifteen postgraduate mentees from a range of multidisciplinary fields of study. Thematic data analysis was utilised to examine the data. The findings reveal that while AI significantly enhances routine tasks such as feedback, scheduling, and resource allocation, mentees consistently value human interaction for emotional support, nuanced advice, and contextual adaptability. The proposed framework underscores the integration of AI tools and human guidance, highlighting areas where AI excels and domains where human insight remains irreplaceable. This chapter emphasises the importance of promoting synergy between AI and human mentors, which ultimately aims to improve the quality, accessibility, and inclusiveness of mentorship in academia. Furthermore, the chapter serves as a foundation for further research on sustainable, AI-enhanced mentorship paradigms.