Artificial Intelligence as a Gender issue in Educational Management. A case of State Universities in Zimbabwe

Admire Chafa & Anna Moyo
Department of Educational Policy Studies and Leadership
Midlands State University, Zimbabwe
Email: chafaa@staff.msu.ac.zw/ moyon@staff.msu.ac.zw

Abstract: This study investigates the gendered dynamics of Artificial Intelligence (AI) integration in educational management at state universities in Zimbabwe. With AI playing an increasingly pivotal role in enhancing administrative and academic functions, it is essential to examine how gender disparities influence the adoption and utilization of AI technologies. The research aims to explore the extent of gender disparities in AI roles, analyze how AI applications either perpetuate or mitigate gender biases, and identify barriers faced by women in accessing AI-driven educational tools. Additionally, it proposes strategies to promote gender equity in AI implementation within higher education management. Using a mixed-methods approach, the study combines quantitative surveys and qualitative interviews to gather data from two hundred participants, including university staff and administrators. The findings reveal significant gender disparities, with women being underrepresented in AI-related roles and facing various barriers, including limited access to training, societal norms, and gender biases in AI applications. Approximately 55% of female respondents reported experiencing gender bias in AI-driven educational tools, highlighting the need for inclusive AI design. The study also identifies critical strategies to bridge these gender gaps, including the implementation of gender-sensitive policies, capacity-building programs, mentorship initiatives, and regular audits of AI systems to ensure fairness. Furthermore, fostering inclusive work environments that support women, particularly in technical fields, emerged as a key factor in enhancing gender equity. In conclusion, while AI offers transformative potential in educational management, its successful integration requires addressing systemic gender imbalances. The study’s recommendations aim to provide actionable insights for universities, policymakers, and researchers striving to create more equitable, inclusive environments for women in AI-driven educational settings. The findings contribute to the broader discourse on technology, gender, and educational management, emphasizing the importance of equity in the evolving digital landscape.