• Address many of the gaps in AI and gender in Sub-Saharan Africa. There is little to no disaggregated data on gender in general, and this gap is even more glaring in sub-Saharan Africa. There is a gap between data on gender and Artificial Intelligence. This results in a biased assessment of society?s needs.
• Addressing the low representation of women in the Artificial Intelligence professions. They remain a minority because they are not pushed towards this professional field. Correct the biases and the reproduction of social inequalities, at the level of algorithms. Some algorithms are borderline sexists. In fact, it is the designers who create implicit biases in the algorithmic systems. This leads us to think that sometimes Artificial Intelligence can generate problems in gender issues instead of providing solutions.
• Contribute to the construction of frameworks for responsible use of Artificial Intelligence and better consideration of AI and gender in governance.
• Promote the consideration of African contexts. Promote inclusion in Africa in relation to our issues. For example, there is limited literature on the harms of technology in our contexts. Work towards a pan-African collaboration on AI and gender inclusion. Today there is a lack of joint work between Francophone and Anglophone Africa. And there is no organized group in Africa to galvanize inclusion and gender in Artificial Intelligence.
• Encourage multidisciplinary collaboration. Artificial Intelligence is a cross-border issue. There is a need to work together between gender and AI actors. The questions are transversal for these two fields. We also need multidisciplinary research to be tested in the African environment.

Gender is, a cross-cutting issue that challenges us.