For too long, the African AI ecosystem has been plagued by a major problem - one more insidious than the perceived lack of AI training datasets and computing infrastructure on the continent: the growing African AI ecosystem is unmapped. This creates two major problems that bottleneck AI innovation on the African continent, for African people, and for African problems.

For AI developers, researchers, and beyond, this creates a problem of discoverability. It is a long and painful experience looking for African datasets because many creation efforts are siloed, fragmented, and dispersed in obscure locations.

For policymakers, government officials, and decision-makers, this lack of mapping creates a fundamental lack of clarity about:

• Critical gaps in AI development: what vital tools, datasets, applications are available and missing in different sectors?
• The actual impact of AI on African communities: are AI solutions addressing Africa's most pressing challenges in healthcare, agriculture, education, and governance?
• Emerging risks and challenges unique to African contexts: what African-centric risks of AI exist on the continent?

Without a cohesive mapping, efforts are fragmented & obscure, innovation is siloed, often duplicated, stakeholders lack the whole picture, and African voices continue to be marginalized in global AI development.