Avoiding a Generative‐ AI Divide: Global Interdependencies and Governance Challenges for Labor Markets in Developing Countries

Generative artificial intelligence (GenAI) is diffusing globally at unprecedented speed, reshaping labor markets through channels rooted in global interdependencies that no single country can govern alone. Standard “automation” framings are incomplete for developing countries: GenAI reconfigures services trade and platform‐mediated work across jurisdictions while also changing task content and skill returns within countries. These channels operate through structural constraints especially salient in developing contexts—high informality, persistent skill deficits, and gaps in digital and physical infrastructure. Drawing on emerging empirical evidence, we identify a dual risk. First, slow and uneven adoption may prevent firms, schools, and public agencies from capturing productivity gains, widening cross‐country gaps with the technological frontier. Second, developing countries may integrate into global AI value chains primarily through weakly regulated data work and platform labor, with limited protections and progression opportunities. These risks are fundamentally collective‐action problems: they arise from regulatory asymmetries, governance gaps, and the deeply interdependent nature of global digital labor markets that no single country can govern unilaterally. We analyze five domains where international coordination is both necessary and feasible: AI‐relevant skills; digital and physical infrastructure; regulation of platform and data work; developing‐country participation in global AI governance; and a Global South research agenda.