Code, Capacity, and Control: AI, Algorithmic Governance, and Political Accountability in African States examines the dual use of digital systems as instruments of developmental administration and as infrastructures for surveillance, exclusion, and political control. Centering South Sudan without treating it as exceptional, the study situates the case within broader debates in digital governance, AI ethics, ICT4D, and authoritarian technology diffusion. It develops the concept of algorithmic developmental authoritarianism to explain how formal norms, institutional design, and struggles over authority become fused in the deployment of digital systems. Drawing on comparative analysis of AI adoption in Rwanda, Kenya, Ghana, and South Africa; legal analysis of data protection and AI governance frameworks; technical audit approaches to algorithmic accountability; and interviews with government e-governance officials, civil society digital rights advocates, and AI practitioners, the study advances three linked propositions. First, algorithmic governance combines administrative promise with significant political risk. Second, imported digital infrastructures carry embedded accountability models that shape domestic governance outcomes. Third, effective public oversight of AI deployment remains uneven and politically contested. The analysis addresses the central question of how African governments deploy AI and machine learning across sectors such as taxation, land administration, policing, and border management, and under what governance conditions, accountability mechanisms, and evidence of effectiveness. It shows that institutions, narratives, and policy frameworks function as political instruments rather than neutral technical arrangements. The study concludes that reform eff