AI in Universities: The Good, the Bot, and the Ugly Truths

Artificial intelligence (AI) is reshaping higher education, offering opportunities for personalized learning, enhanced efficiency, and improved campus management. However, its adoption also presents challenges such as ethical concerns, disparities in access, and over-reliance on technology. This study explores the benefits and challenges of AI integration in two Ugandan universities, focusing on its impact on teaching, learning, and institutional administration. Using a mixed-methods approach, data were collected through surveys from both students (123) and faculty members (43) across some Ugandan universities, complemented by interviews. Quantitative data were analyzed using ANOVA to assess differences in perceptions of AI adoption, while qualitative data provided deeper insights into concerns surrounding data privacy, infrastructure limitations, and faculty readiness. The findings revealed significant disparities in AI adoption, with institutions possessing better resources and access to AI tools reporting more positive perceptions of its effectiveness. The study also highlighted concerns over unequal access to AI-driven educational tools, emphasizing the need for targeted policy interventions. Tabular presentations illustrated variations in AI adoption levels, showcasing both the potential and challenges faced by different institutions. Qualitative insights underscored fears of reliance on AI at the expense of human interaction, as well as the necessity for data protection measures. The study concluded that while AI adoption in Ugandan universities is still at a nascent stage, there is a strong shared recognition among students, faculty, and administrators of its potential to enhance teaching, learning, and administrative efficiency, yet significant barriers such as limited infrastructure, unequal access to AI tools, and insufficient training hinder its widespread implementation. The study recommends the strategic investments in digital infrastructure to ensure equitable AI access, the development of policies that prioritize inclusivity, and regular training programs for faculty and administrators to enhance AI literacy. Universities must balance AI adoption with ethical considerations, ensuring that technological advancements do not exacerbate educational inequalities.