Artificial intelligence governance and regulatory frameworks in emerging economies: Accountability mechanisms, institutional capacity, and ethical oversight in Nigeria, Kenya, and South Africa

Background: Artificial intelligence systems are being deployed across governance, healthcare, financial services, and social infrastructure in emerging economies at a pace that has substantially outrun the development of regulatory frameworks capable of ensuring accountability, fairness, and ethical oversight. In Nigeria, Kenya, and South Africa, rapid AI adoption by both public sector institutions and private corporations has generated significant governance gaps, particularly regarding algorithmic transparency, data protection, and redress mechanisms for AI-driven harms.

Aim: This study examined the current state of AI governance and regulatory frameworks in Nigeria, Kenya, and South Africa, assessing institutional capacity for ethical AI oversight and identifying gaps between regulatory ambition and implementation capability.

Methodology: The study employed a qualitative comparative policy analysis methodology drawing on regulatory document analysis, semi-structured interviews with 39 AI governance stakeholders across the three countries, and assessment of institutional capacity indicators. Data were collected between January and October 2025 and analysed using thematic analysis guided by the responsible AI governance framework.

Findings: All three countries have articulated AI policy ambitions, but implementation capacity lags significantly behind regulatory rhetoric. South Africa's AI policy framework, operationalised through the Presidential Commission on the Fourth Industrial Revolution, exhibits the most institutionally developed oversight architecture, though enforcement mechanisms remain nascent. Nigeria's emerging AI strategy is constrained by inadequate technical expertise within regulatory bodies. Kenya shows the most dynamic civil society engagement with AI accountability, complementing weaker formal regulatory structures.

Contributions: The study contributes to AI governance and public policy literature by providing comparative empirical evidence of regulatory capacity in three leading African economies, identifying transferable institutional innovations and structural constraints that shape AI governance trajectories in emerging market contexts.