AfriDSAI

The African Institute for Data Science and Artificial Intelligence (AfriDSAI) is a transdisciplinary institute based at the University of Pretoria (UP) that brings together researchers, technologists, and communities to reimagine how data science and AI can work for Africa. By focusing on African challenges and contexts, the institute builds tools and knowledge that reflect the continent’s diversity and supports the people who will shape its digital future.

Initially led by Professor Vukosi Marivate, AfriDSAI addresses the underrepresentation of Africa in AI by strengthening the continental ecosystem that bridges academia, industry, and government. The Institute harnesses the untapped potential of AI and data science to improve the lives of African people through research in areas such as healthcare, agriculture, and climate resilience, while building capacity for emerging African researchers to become global leaders in the field.

The Need for an Africa-Centered AI Ecosystem

Artificial Intelligence holds transformative potential for Africa—but in its current global form, it often overlooks the continent’s languages, contexts, and challenges. Today, African perspectives remain underrepresented in the development and governance of AI, leaving many communities without the necessary tools, data, or research capacity to participate meaningfully in shaping these technologies.

At the same time, there is no coordinated, Africa-centric ecosystem to guide the development, application, or governance of AI and data science across the continent. Fragmented networks, limited access to infrastructure, and a lack of investment in African-led research mean that innovation too often happens elsewhere, for African markets, but not by African researchers.

AfriDSAI was established to address this gap directly. The Institute strengthens Africa’s AI ecosystem by bridging academia, industry, and government and ensuring that technological innovation aligns with the continent’s social priorities. Its research addresses Africa's underrepresentation in AI, particularly in language, vision, and application domains, while enhancing AI-enabled breakthroughs in healthcare, agriculture, education, and climate resilience.