Leveraging Artificial Intelligence for Strategic Leadership and Institutional Capacity in Somalia: Lessons from Estonia and Rwanda

Abstract

Artificial intelligence is reshaping public administration worldwide, yet the scholarship on AI governance remains concentrated on advanced and rapidly emerging economies, leaving fragile, post-conflict states largely absent from the analytical record. This article addresses that gap by asking how Somalia can use AI to strengthen strategic leadership and institutional capacity, drawing comparative lessons from Estonia and Rwanda. Using a qualitative comparative design, the study analyses national AI strategies, institutional records, and government programs across the three cases through content analysis and structured, focused comparison. The findings show that Estonia, Rwanda, and Somalia converge on an ethicsoriented rather than rule-based regulatory posture, but diverge sharply in institutional maturity, the sequencing of governance investment, and the degree to which hybrid public-private arrangements generate accountability rather than an accountability vacuum. Somalia's nascent institutions, principally the Somali National AI Center and the Somalia Data Protection Authority, reveal functional indetermination as a structural condition rather than a deliberate governance choice. Strategic leadership, understood in this study as the demonstrated capacity of senior officials and institutions to formulate, prioritize, communicate, and sustain coherent long-term governance visions in the face of institutional constraints, is identified as the primary explanatory variable differentiating the three governance trajectories examined. The study concludes that Somalia's most urgent priority is not the drafting of a comprehensive national AI strategy but the formalization of clear mandates, sequencing logic, and accountability mechanisms, offering a context-sensitive contribution to the emerging literature on AI governance in fragile states.