African-language AI developers cannot access sufficient training data to build competitive language models

AI researchers and companies building African-language AI models face a critical bottleneck: there simply isn't enough digitized text data in African languages to train high-quality models. This creates a vicious cycle where African languages remain underrepresented in global AI systems, and companies struggle to justify investment in tools that serve these markets. Existing data collection solutions are either too expensive, too slow, or don't exist for lower-resourced languages.