AI Governance Capacity in Developing Countries: Gaps, Innovations and Implementation

This study evaluates AI governance across 74 developing countries, examining institutional, technical, and financial barriers. Over 50 peer-reviewed studies (2019-2026) were analyzed. Developing countries are building governance frameworks suited to local conditions. The analysis identifies 10 evidence-based practices from Kenya, India, Indonesia, Nepal, and Tanzania. Key findings: (1) 70% of developing countries have regulatory fragmentation across multiple agencies; (2) 34 governance gaps exist across institutional, technical, financial, human capital, and policy areas; (3) governance-before-technology approaches reduce implementation problems by 42%; (4) ethics integration improves operational efficiency; (5) long-term institutional commitment sustains governance systems. The study presents three governance tiers (Foundational, Emerging, Advanced) matched to institutional capacity and describes South-South learning mechanisms. This research documents governance work in developing countries and provides guidance for AI governance aligned with national objectives and the Sustainable Development Goals.