Adaptation level of artificial intelligence (AI) in university curriculums: A case study on Mogadishu located universities

Abstract

This study examines the adaptation level of artificial intelligence (AI) within university curricula in Mogadishu, Somalia, a post-conflict context characterized by emerging technological momentum yet significant resource constraints. Utilizing a comparative descriptive research design, data were collected from 24 universities through a systematic analysis of curriculum documents and open-ended questionnaires administered to academic staff. The findings reveal that while AI integration is gaining traction, it remains structurally uneven and predominantly theoretical in nature. Quantitative results indicate that although all 24 sampled institutions have integrated at least one AI-related subject, such as Machine Learning, Data Science, or Neural Networks, into their computing departments, only 16 universities (66.7%) offer AI as a standalone subject. Furthermore, qualitative data underscores critical systemic barriers, including a profound absence of national and institutional policy frameworks, a shortage of specialized faculty, and a lack of dedicated AI laboratories for practical application. The study concludes that while there is positive institutional movement toward technological adoption, sustainable AI education requires strategic capacity building, the establishment of standardized academic frameworks, and increased investment in digital infrastructure to align graduate competencies with the demands of a technology-driven global labor market.

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