Artificial Intelligence and Labor Market Adjustment in Türkiye: Evidence from LinkedIn Data

Freeha Fatima, Efsan Nas Ozen and Dhushyanth Raju

No 209921, The Social Policy and Labor Discussion Paper Series from The World Bank

Abstract: This paper examines how artificial intelligence (AI) is reshaping Türkiye’s labor market by documenting patterns in skill supply, employer demand, and labor market adjustment using high-frequency digital labor market indicators from LinkedIn. The analysis focuses on the mechanisms through which AI-related change is associated with shifts in skills, hiring, occupational mobility, exposure to generative AI, and international migration. The evidence shows a relatively broad presence of foundational digital and AI literacy skills across sectors and demographic groups, alongside a persistent and increasing concentration of advanced AI engineering talent within a narrow set of occupations and industries. Measured skill penetration follows non-monotonic patterns over time, while frontier AI talent accumulates steadily, indicating a divergence between the breadth and depth of AI capability. Entry into AI roles often follows strongly path-dependent pathways, and employer demand signals for technical and AI-adjacent capabilities are only partially reflected in realized hiring, with no sustained positive divergence in AI-related hiring relative to overall labor demand. Potential exposure to generative AI varies systematically across sectors and demographic groups, with the balance between task augmentation and disruption differing across sectors rather than uniformly favoring one over the other. International migration emerges as a salient adjustment margin for highly specialized AI talent, operating alongside domestic reallocation mechanisms and influencing the availability of frontier skills within the domestic labor market. These patterns indicate that the central challenge associated with AI in Türkiye’s labor market lies not in whether AI-related capabilities will spread, but in how reallocation unfolds across skills, occupations, and workers over time. The findings highlight the role of skill formation systems, hiring and credentialing practices, occupational structures, and cross-border mobility in shaping the trajectory of labor market adjustment. The analysis also illustrates how digital labor market data can complement traditional sources by providing timely evidence on emerging skills, evolving demand, and early adjustment dynamics in middle-income economies navigating the AI transition.

Date: 2026-04-01
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