This presentation explores the asymmetries on distribution and circulation of knowledge and know-how on big data and AI in Latin America. It reveals infrastructure gaps, limited skills, and divergent understandings among experts, policymakers, technicians, and citizens. Technoscientific promises outpace actual knowledge and technical proficiency, widening the digital divide between the Global North and the Global South. Dependency on digital transnationals for 'turnkey' solutions exacerbates the problem. We aim to identify and characterize skill-building processes in the region by analyzing expert activities. Despite increased data availability, the number of skilled individuals remains limited. Universities and training centers are expanding, but access to infrastructure and data is asymmetrical compared to the North. Many countries lack the infrastructure and skills to collect and store large amounts of data, or struggle to compete with the digital transnationals. This creates a new form of dependency on offshore cloud services beyond local control or regulation. Moreover, there is a constant transfer of professionals trained by public institutions to private companies. This process hinders effective utilization and increases misuse. The lack of knowledge circulation within the region inhibits collaboration and duplication of efforts. Key questions include skill development, the role of formal and informal education, knowledge circulation, access strategies, new dependencies, but also new forms of resistance. This presentation sheds light on the knowledge divide and its implications, emphasizing the need for equitable knowledge exchange, infrastructure improvement, and skill retention to bridge the gap in big data and AI expertise between the North and the South.