Lanfrica Insights
We exist to change how African AI is understood, and how our story gets told.
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June 22, 2026 · 15 min read
The Shape of Large African-Language Datasets
For more than a decade, African-language datasets have been described through scarcity: low-resource languages, limited training data, not enough samples. That description still captures much of the field, but it no longer captures its ceil
“Until the lions have their own historians, the history of the hunt will always glorify the hunter.”
— Chinua Achebe
Reshaping how we think about African AI
African AI is extraordinarily diverse: linguistically, regionally, and institutionally. Yet the evidence needed to understand it remains deeply fragmented. Datasets, research, tools, and records of the people behind them are scattered across repositories, institutions, disciplines, and the African diaspora. Any single repository or partial map therefore reveals only part of the field.
That partial view also shapes what gets counted. African AI is not built by popular startups, model-makers, and dataset providers alone. It is seeded by the field linguist who wrote a language's first grammar, the team behind its first dictionary or keyboard, and the student who mapped its tones: quiet, distributed work across decades and disciplines that makes later language technology possible.
Too often, accounts of the "state of AI in Africa" rely on anecdotes, expert opinion, and press releases rather than systematic evidence. Where evidence is used, it is often drawn from a single repository, dataset, or survey, offering only a partial view of the field. The result is an incomplete account of the trends, drivers, and trajectory of the ecosystem.
Lanfrica Insights exists to change how African AI is understood, and how the story of our own work gets told. Our analyses draw on multiple sources of evidence, including the African AI Atlas, our living, connected map of the field, and apply rigorous empirical methods to questions that have too often been answered from fragments.
This allows us to uncover overlooked contributions, examine the real drivers of African AI's progress, make its impact more visible, and develop a clearer account of what is possible for Africa.
Our mission is to improve public understanding of the drivers, progress, and impact of AI across Africa through empirical, evidence-based analysis.
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