AI-Enabled Enterprise Applications and Workforce Transformation in a Resource-Constrained University: The Case of Nalut University, Libya

Abstract

This paper presents a documentary and comparative case analysis of the implications of AI-enabled enterprise applications for Nalut University, a small, geographically dispersed public university in the Nafusa Mountains region of western Libya. Drawing on Gartner’s Predicts 2026: AI’s Impact on Enterprise Applications and a rigorous analysis of five official Arabic institutional documents of Nalut University (the Second Strategic Plan 2025–2030, the Executive Plan 2025–2026, the 2020 Leadership Selection Guide, the 2019 Administrative Procedures Manual, and the current organisational structure chart), and the systematic assessment of nine formal cooperation agreements signed by the university between 2019 and 2023,  the study investigates how intelligent applications, agentic AI, and composable architectures may extend institutional capacity while transforming the roles of academic, administrative, technical, and support staff. Deep comparative case studies are drawn from universities across the Arab world (University of Benghazi and Sebha University in Libya; Houari Boumediene University of Science and Technology in Algeria; selected Tunisian and Moroccan initiatives), the Gulf (leading universities in the United Arab Emirates and Saudi Arabia), Sub-Saharan Africa (University of Calabar in Nigeria; Bindura University of Science Education in Zimbabwe; selected South African institutions), Asia (Singapore’s higher-education AI ecosystem), and broader global practice. Both successful implementations and analytically examined failure cases are included so that Nalut University can adopt proven practices and systematically avoid documented pitfalls. The historical partnership analysis reveals a consistent pattern of general, largely non-binding  academic memoranda of understanding  focused on staff exchange, joint research and traditional scholarly activities, with almost no provisions addressing digital transformation, artificial intelligence or enterprise-system modernization.  Findings indicate that Nalut University possesses explicit strategic intent under Strategic Goal 7 but operates from a largely paper-based administrative baseline characterised by multi-step hierarchical procedures, limited inter-campus connectivity, shortages of specialised academic expertise, and dependence on state budgets. A five-layer AI Transformation Framework tailored to resource-constrained, multi-campus universities is proposed, together with three future scenarios (Limited Adoption, Augmented University, and Fully Enabled Digital University). Based on the documentary evidence and comparative cases examined, augmentation of existing staff roles rather than large-scale replacement appears to be the most plausible near- to medium-term trajectory under disciplined implementation, provided that data foundations, continuous staff capability-building, ethical governance, outcome-based implementation, and a deliberate redesign of future partnership instruments are prioritised. Detailed practical recommendations, limitations, and a forward research agenda are presented. The study contributes to the still underdeveloped literature on AI in small universities of the Global South and offers transferable lessons for similar institutions across the Arab region and beyond.