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AI has become one of the most prominent fields of global attention.
Today, it is applied not only in everyday life but also across diverse professional sectors, driving countries worldwide to invest heavily in its development.
As AI emerges as a key driver of the future international order, competition among nations is intensifying.
Yet the development of AI requires skilled human resources, vast datasets, and reliable infrastructure, areas where significant disparities have already emerged.
Consequently, nations that hold global power are consolidating their dominance in AI as well.
The United States and China, for example, are currently locked in fierce competition for AI leadership.
But what does it mean to be excluded from this race?
AI is, at its core, a product of learning. However, the learning process rarely reflects a truly balanced view of the world.
Which information is accepted as truth, and which perspectives are emphasized, depends on the data and the designers who train the system.
Even with objective data, outcomes differ depending on who builds and trains the AI.
This is why many countries are actively developing AI models that reflect their own perspectives.
The 2025 AI Index Report illustrates this imbalance.
The vast majority of leading AI models have been developed in the United States and China, while Africa lags significantly behind in both pace and scale.
Although Africa and Latin America have made progress in computer science (CS) education, many African countries still lack stable access to basic infrastructure such as electricity.
As of 2023, only 34% of primary schools in Sub-Saharan Africa had electricity, showing the severity of this barrier.
Without these foundations, computer literacy and AI education remain limited.
The gap extends to research and development as well.
From 2013 to 2023, Africa recorded strikingly low numbers of AI-related publications, patents, and legislative initiatives.
Between 2003 and 2024, Africa produced virtually no major AI models.
Even in the Korea Software Policy & Research Institute’s global report on large-scale AI models, African countries were absent, underscoring the widening development gap.
This issue is not just technical. It is fundamentally about representation.
Without AI models developed from African perspectives, global AI will continue to reflect primarily U.S. and Chinese viewpoints.
This risks erasing Africa’s unique and diverse perspectives from the global AI ecosystem.
Africa’s 54 countries represent rich cultural and social diversity, and if this is excluded, Africa’s influence in international discourse will inevitably diminish.
Signs of exclusion are already evident.
In global surveys on AI services conducted between 2022 and 2024, only South Africa was included, compared to nine Asian countries, twelve European countries, three North American countries, five South American countries, and two Oceanian countries.
This illustrates how Africa is being sidelined as an opinion leader in shaping the future of AI.
If this trend continues, Africa risks becoming further marginalized in the global AI landscape.
For these reasons, the development of major AI models in Africa is not optional but essential.
To achieve a more balanced global perspective, representation across continents must be ensured.
Expanding participation from currently marginalized regions such as Africa and Latin America will strengthen solidarity and cooperation within the Global South.
At the same time, AI-leading nations can help build a fairer and more sustainable global AI ecosystem through collaboration.
AI models developed by Africa would be more than technological milestones.
They would serve as a foundation for balance, fairness, and diversity in the international community.
If support for Africa’s AI industry is delayed, the future global AI order will become increasingly shaped by the perspectives of only a few powerful nations.
For genuine balanced development, we call for active support and global solidarity in fostering Africa’s AI industry and advancing the development of major AI models.
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