As African governments work to shape their own artificial intelligence (AI) governance frameworks, a growing body of policy experience from Asia, Latin America, and the Gulf is providing an alternative reference point beyond the European and American models that have traditionally dominated the conversation.
Dr Jannie Zaaiman, Secretary General of the Technology Information Confederation Africa (TICON Africa), argues that the global AI policy environment has become genuinely distributed, with countries at varying levels of development now producing governance approaches that reflect their own economic priorities rather than simply mirroring the frameworks of wealthier nations.
In Asia, that has produced a range of distinctive models. Singapore has extended practical governance tools to cover newer AI applications, while Japan and South Korea have anchored their national legislation around trustworthy AI principles. China has pursued a more targeted path, regulating specific high-risk use cases such as generative AI and deep-synthesis content rather than building a single cross-sector legal instrument. Collectively, these approaches illustrate that regulatory frameworks can be designed to evolve in step with technology rather than play catch-up.
In Latin America, Brazil has committed to a multi-year national AI investment plan, while Chile had already implemented roughly 78 percent of its AI Action Plan initiatives by April 2025. Smaller Caribbean economies, coordinating through regional bodies, have focused primarily on building institutional readiness and collaboration capacity.
Gulf economies offer another reference point. The United Arab Emirates and Saudi Arabia have embedded AI strategy within long-term national development plans, treating technology governance not as a standalone regulatory exercise but as a component of broader economic transformation.
For African policymakers, the significance of these examples lies in what they share with the continent’s own constraints. Countries such as Brazil, Chile, and several Gulf states have navigated questions around compute access, skills gaps, and the gap between policy ambition and implementation capacity challenges that are not unique to Africa but particularly acute across much of the continent.
Zaaiman’s analysis suggests that the real differentiator between regions is not the sophistication of the policies themselves but the speed at which governments can build the institutional infrastructure digital systems, trained human resources, and regulatory capacity needed to turn written frameworks into practice. On that measure, African economies face a genuine but not insurmountable gap.
The broader implication is that AI governance is still being written globally, and peer economies outside Europe and North America are actively shaping it. For Africa, the window to draw on that diversity of experience, while investing in the domestic capacity to act on it, remains open.
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