This chapter aims to equip African Union’s member states with the tools to efficiently design policies that foster jobs and sustainable human development (SHD) for the youth. The African Union (AU) adopted the Data Policy Framework (DPF) in February 2022, before OpenAI’s chatbot ChatGPT ushered in the Artificial Intelligence (AI) Revolution in November that same year. This timing suggests—and this chapter shows—that the DPF hardly addresses the risks and scope presented by AI, particularly in terms of employment and SHD. Striving to overcome the challenges outlined by Sustainable Development Goal No. 8, which urges states to open employment opportunities, this chapter delves into the complexities introduced by AI’s ability to perform high-order cognitive tasks, such as evaluating and creating. This reality poses an unprecedented threat, especially to the youth in the Global South, escalating the risks of unemployment and complicating governments’ legislative responses. Young third-world countries are disproportionately affected by joblessness and more vulnerable to the disruptive effects of AI and generative pre-trained transformers (GPTs) on the job market, as they typically lack the experience, skills, and resources to adapt to the rapidly changing employment landscape. This original research enquires into how AU members should redefine their data policies to combat AI-induced unemployment while leveraging AI to generate jobs and advance SHD for the youth. A carefully reformed DPF, that focuses on decolonizing AI, can delicately balance between mitigating unemployment risks and harnessing AI for economic growth. The chapter argues that decolonizing AI in Africa calls for three key shifts within the DPF: prioritizing indigenous knowledge, favouring data sovereignty, and—most importantly—building local capacity. A doctrinal (i.e., legal) analysis of the DPF and what it implies for employment, as well as a survey of the literature on AI’s effects on employment and the DPF form the methodology of this study. The added value of this research lies in its utility in guiding AU policymakers towards data policies that not only respond to the rapid breakthroughs in AI but also protect and economically empower the youth demographic in this digital era.