The transformative potential of AI and ML is immense, reshaping sectors from healthcare to finance. However, the pace of AI development and its benefits are not uniformly distributed, with under-resourced communities, particularly those historically disadvantaged, experiencing a lack of access to the rewards of AI. This disparity highlights the need for responsible, ethical, and community-centric approaches to AI development that prioritize local needs, cultures, and languages. This workshop aims to address these disparities by focusing on the human aspects of AI. It seeks to move beyond the technicalities of algorithms and computation to delve into the foundational elements of AI, the data itself. Doing so emphasizes the importance of data practices that are efficient, ethical, culturally aware, and inclusive. Participants will engage in discussions and practical sessions that explore data generation, annotation, legal frameworks, and sharing protocols. Special attention will be given to creating culturally contextual datasets that reflect African communities’ linguistic and societal nuisances. The workshop will also cover critical topics such as data governance, synthetic data implications, and cross-cultural data safety challenges and opportunities. The goal is to equip researchers, ML practitioners, and policymakers with the knowledge and skills necessary to implement AI projects that are ethical, inclusive, and impactful, thereby fostering an AI ecosystem that truly benefits all, especially those in marginalized communities. Through this endeavour, the workshop will contribute to shaping a future where AI development in Africa is driven by African voices and directly addresses the continent’s unique challenges and aspirations.