Artificial Intelligence and Heterogeneous Unemployment Risk Across Regions: Scenario-Based Projections of Alternative Policy Responses in Taiwan

Objective: – To evaluate the impact of artificial intelligence (AI) on employment in Taiwan by quantifying exposure and projecting unemployment risks across industries, occupations, and regions. Methods: – National workplace survey data (N = 4, 009) were analyzed using AI Industry Exposure (AIIE) and Occupation Exposure (AIOE) indices to construct a composite AIECI. Six scenarios (α = 0.075 or 0.15; RA = 0, 0.5, 1) modeled unemployment projections for 2025–2035. Results: – Taipei, Hsinchu, and Taichung showed the highest exposure. Under high-impact scenarios, urban unemployment may rose sharply, while retraining interventions reduced projected risks. Rural regions remained less affected. Conclusions: – AI exposure is unevenly distributed, concentrating risk in technology-intensive regions and occupations. Targeted workforce adaptation policies are needed to mitigate unemployment and regional disparities.