Africa must move from fragmented national efforts to a more coordinated continental posture if it is to shape emerging rules on artificial intelligence (AI), according to the Secretary General of the Technology Information Confederation Africa (TICON Africa), Dr Jannie Zaaiman.
In a policy commentary, Zaaiman opines that AI regulation is evolving through a “polycentric governance landscape,” where multiple jurisdictions are simultaneously developing laws, standards, and institutional frameworks. This, he argues, creates both risk and opportunity for Africa, depending on how effectively it organises its response.
Major economies are already setting reference points. The European Union has advanced a comprehensive legal regime, while the United Kingdom and the United States are pursuing “strategy-led” and “fragmented federal-and-state” approaches, respectively. Meanwhile, international bodies are introducing binding instruments that could influence global compliance expectations.
In light of these developments, Africa’s challenge is less about participation and more about influence. The continent has taken steps, including the African Union’s Continental AI Strategy and several national frameworks, but these remain dispersed. The core issue, Zaaiman suggests, is “insufficient coordination” across jurisdictions.
He argues that without alignment, African countries risk becoming “passive adopters” of external standards, which could limit policy flexibility and constrain innovation ecosystems. Instead, he calls for a deliberate effort to build a “collective voice” that can engage global processes from a position of coherence.
Such coordination would require action at multiple levels. At the continental level, institutions must align strategy and representation. Regionally, blocs such as the Economic Community of West African States (ECOWAS) and the Southern African Development Community (SADC) should facilitate “regulatory learning” and shared experimentation. Nationally, governments must prioritise implementation through investments in skills, infrastructure, and institutional capacity.
Recent data reinforces the urgency. Global assessments show that many countries, including those in Sub-Saharan Africa, remain in early stages of AI readiness, highlighting gaps in “governance capacity” and technical infrastructure. This suggests that policy ambition must be matched by execution.
Zaaiman emphasizes that AI governance is still evolving and not yet settled. For Africa, this creates a strategic window to contribute priorities such as “developmental inclusion,” language diversity, and public-interest deployment into global frameworks.
What matters for Africa in AI governance is not the number of policies in place, but whether countries can actually coordinate and implement them in practice, where “implementation capacity” becomes the real measure of influence.
