A Senegalese startup recently launched an artificial intelligence model capable of conversing in Wolof, a West African language. However, this development highlights a broader challenge: the limited availability of data for most African languages hinders the advancement of AI technologies across the continent. Current AI models are largely trained on widely-spoken languages like English and Mandarin, leaving many African languages underrepresented. This disparity creates a significant barrier to equitable access and development of AI solutions tailored to local needs. Experts emphasize the need for increased investment in data collection and linguistic resources for African languages. Overcoming this linguistic obstacle is crucial for ensuring AI benefits all populations, not just those who speak dominant global languages. The launch of the Wolof AI represents a positive step, but widespread progress requires further focused effort.