Who Wins the AI Revolution in Europe?

Executive Summary

AI is redrawing Europe’s economic geography. In “Diverging Paths: AI Exposure and Employment Across European Regions,” we map how artificial intelligence interacts with Europe’s regional structures — from sectoral specialisation and R&D intensity to skills and productivity. The findings show that AI will not reshape Europe evenly: innovation hubs are best placed to benefit, while peripheral regions risk falling further behind.

Europe’s AI economy divides into four clusters. A cluster analysis identifies high-tech service and capital centres, an advanced manufacturing core, and southern and eastern peripheries. These groups differ systematically in innovation capacity, workforce skills, and industrial mix — implying distinct trajectories for AI adoption and employment outcomes.

Employment effects depend on local structures. In capital-intensive manufacturing systems, AI may reduce employment; in advanced industrial cores, it tends to enhance process innovation instead. In labour-intensive eastern economies, automation could cause displacement unless complemented by active policy.

Without intervention, divergence will deepen. Regional disparities in innovation and training risk reinforcing a two-speed Europe — one that captures AI’s gains and one that bears its costs.

Policy recommendations

1. Invest in regional capabilities and skills. Strengthen R&D, workforce training, and industrial upgrading in southern and eastern peripheries to ensure that AI supports convergence rather than fragmentation.