This session introduces a new World Bank Group modelling framework that treats AI not as a simple productivity shock, but as a structural transformation of the production process. By embedding the hardware–software production paradigm into the Bank's dynamic CGE model (MANAGE), we simulate how AI adoption reshapes sectors, occupations, prices, under budget constraints over time.
Are we missing the true economic impact of AI? How can we equip policymakers with better tools? Investments in generative AI are accelerating rapidly, yet our understanding of its economy-wide impact remains limited. While firm-level studies and task-based evidence are expanding, macroeconomic projections still range from modest productivity gains to transformative growth effects. For policymakers, this uncertainty makes effective decision-making difficult This session introduces a new World Bank Group modelling framework that treats AI not as a simple productivity shock, but as a structural transformation of the production process. By embedding the hardware–software production paradigm into the Bank's dynamic CGE model (MANAGE), we simulate how AI adoption reshapes sectors, occupations, prices, under budget constraints over time. The framework integrates detailed task-level occupational data, based on the ILO-NASK Index of GenAI Exposure, which allows substitution patterns to vary across sectors, and models AI as a dual-capital bundle combining data, software, and intangible capital. It enables policymakers to assess alternative adoption scenarios and their implications for growth, structural change, and equity.
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