AI Made in Africa: Voices from AI Businesses Across Africa on Briter (formerly Briter Bridges)

Artificial intelligence (AI) is a major driver of economic growth, social progress, and sustainable development across the African continent. Operating in close partnership with the African Union (AU) and in alignment with Agenda 2063: The Africa We Want, the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH, on behalf of the German Federal Ministry for Economic Cooperation and Development (BMZ), is implementing the AI Made in Africa project.

The AI Made in Africa project aims to strengthen the foundational prerequisites for AI-driven economic growth across AU member states. By focusing on private sector innovation, policy dialogues, and data accessibility, the project works to build a vibrant, sustainable, and self-reliant African AI ecosystem.

In light of this objective, AI Made in Africa project has undertaken a comprehensive, multi-phase study of the African AI business landscape with Briter to create a new evidence-based foundation for policy and ecosystem support. The study combined ecosystem mapping of African AI businesses and their activities in the last ten years, along with the first African AI Business Survey and several ecosystem engagements with AI businesses, policy experts, and investors. The report AI Made in Africa: Voices from AI businesses across Africa synthesises the collected data and qualitative inputs into a comprehensive report outlining the commercial and technical realities of African AI businesses.

Key takeaways from the report:

Across Africa, AI is moving from add-on to core: The mapping shows that many AI businesses are existing startups across sectors like agriculture, fintech, health, and logistics that adopted AI technologies to improve their products. But the survey revealed that many of the businesses that came out since the GenAI boom in 2022 are no longer adopting AI technology, but AI is central to their operating model.
The cost of AI is high, but the willingness to pay is uncertain. 65% of businesses cite cloud and compute as their highest cost, most of which are priced in dollars, while 56% sell their products for under $2,500 a year and 65% of businesses cite customer trust as the top barrier to scaling.
AI products are built with institutional consumers in mind. 88% sell to other businesses and 44% to government, and many of them use a subscription model rather than a one-time purchase. This reflects African AI businesses prioritising predictable, institutional revenue over individual consumer scale.
AI businesses in Africa train in-house in the face of a limited talent pool. AI businesses reported that finding senior-level AI tech talent is difficult in the face of global talent competition. As a result, many companies are building formal internal training pipelines to upskill junior talent.
Capital needs to be patient, not just bigger. Founders want investment vehicles that can work with the longer B2G sales cycles and structural currency risk, along with the higher cost to build their own datasets. The availability of capital is not the only problem, but the access to the right type of capital for the AI business ecosystem is a larger challenge in Africa.

Whether you're a founder, an investor, an ecosystem builder or a policymaker, the report sets out what needs to shift, from R&D and compute subsidies to cross-border data harmonisation and regulatory sandboxes, for African AI businesses to scale on their own terms.