The article addresses the issue of ensuring technological sovereignty in sub-Saharan Africa. Using Nigeria, Kenya and Ghana as case studies, the author demonstrates that national programmes and strategies dedicated to developing advanced information technologies have been implemented in a sub-Saharan Africa, as well as professional research groups and scientific and educational research centers that are aimed at developing artificial intelligence (AI) applications. IT parks are also under construction in some countries. The key area of research is natural language processing, as a wide range of AI applications that can understand different African languages is needed to create a well-developed AI-ecosystem in Africa that addresses the needs of local citizens. Both general scientific methods (such as analysis, synthesis and analogy) and special methods (such as critical discourse and comparative analyses) were used in the research. It has been revealed that several language models for Kiswahili, Yoruba, Twi and Luganda as well as a special Python library for solving speech recognition tasks for the most common languages in Ghana have already been developed by certain African research groups. This represents a significant breakthrough for African countries in the field of high-tech technologies. However, these successes are local in nature across the entire continent, as their further development depends on a problem that affects most African countries: lack of funding. As a result, many research groups in Africa exist on a voluntary basis, and the research itself is frequently funded by sponsorship from Western corporations and foundations. This poses a serious threat to the technological sovereignty of sub-Saharan African countries, which, despite ongoing efforts, continue to depend on imported technologies and foreign investments. In order to reduce this dependence, African governments need to consider mechanisms for attracting African investors to relevant research and development. Only in this case it would be possible to organize an effective search for optimal solutions in order to meet specific local and regional demands.