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Artificial Intelligence (AI) is increasingly positioned as a transformative force in global education, yet its role in low-resource contexts remains underexplored. This study investigates the extent to which AI can shape the future of higher education in Uganda, focusing on a case study of Makerere University, the country’s leading public institution. Drawing on academic literature, national policy documents, and Makerere’s digital transformation initiatives, the research examines how AI is being conceptualized and implemented within the institution through four specific objectives: examining global and African AI integration patterns, assessing Makerere’s adoption levels, identifying implementation gaps, and proposing contextualized recommendations. The study adopted a qualitative document analysis to interpret and extract meaning from written, visual, or physical documents. It involved a systematic review of materials and identified themes and patterns and concepts that did not need direct participant interaction. Findings reveal a complex landscape. While Makerere has initiated AI-related efforts such as establishing research hubs and integrating machine learning into selected academic programs, progress remains uneven and constrained by infrastructural limitations, inconsistent internet access, and the absence of a coordinated institutional strategy. Information got from primary data reveals that less than 10% of Ugandan higher education institutions have piloted AI initiatives, with Makerere showing only 25% implementation compared to 85% in developed nations. The study argues that AI is not an inevitable future, but a conditional opportunity. Its integration and impact will depend heavily on policy coherence, institutional capacity, and inclusive technological planning. Rather than replacing traditional systems, AI is more likely to play a complementary role. The paper concludes with objective-based recommendations aimed at strengthening Uganda’s readiness for AI in higher education, proposing a pathway to move from fragmented experimentation to sustainable innovation.