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Benchmarking Türkiye’s AI Workforce Readiness : A Multidimensional Global Comparison Using LinkedIn Data

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  • Fatima, Freeha
  • Ozen, Efsan Nas
  • Raju, Dhushyanth

Abstract

Artificial intelligence (AI) is reshaping labor markets, with countries increasingly differentiated by the depth, breadth, and distribution of AI-related capabilities. This paper benchmarks Türkiye’s AI workforce readiness using LinkedIn skill and hiring data within a consistent cross-country comparison framework. The analysis examines eight dimensions of readiness: AI engineering depth, AI literacy, foundational and disruptive digital skills, sectoral specialization, employer demand, hiring momentum, exposure to generative AI, and international mobility of AI professionals. The evidence places Türkiye in an intermediate position in the cross-country distribution, generally below frontier economies and, in several dimensions, closer to the lower segment of the distribution. Foundational digital capability exceeds the global reference average, while AI literacy is expanding but remains below levels observed in higher-performing countries. The density of advanced AI engineering talent remains limited relative to frontier economies, and capability is unevenly embedded across sectors, with stronger presence in technology-oriented activities and higher disruption exposure in financial services. Employer demand is anchored in general competencies, hiring momentum is positive but below that observed in higher-performing countries, and net outward mobility of AI professionals persists. Exposure to generative AI is not unusually high in aggregate but varies substantially across sectors, with sectoral differences exceeding those across demographic groups. These findings describe an economy characterized by broad capability expansion without corresponding depth, specialization, or retention of advanced talent. AI readiness is inherently multidimensional and depends on the interaction of skill formation, labor demand, occupational structure, and international mobility. By documenting these patterns within a consistent comparative framework, the paper clarifies how middle-income economies can move from broad digital capability toward frontier specialization in the early stages of generative AI diffusion.

Suggested Citation

  • Fatima, Freeha & Ozen, Efsan Nas & Raju, Dhushyanth, 2026. "Benchmarking Türkiye’s AI Workforce Readiness : A Multidimensional Global Comparison Using LinkedIn Data," The Social Policy and Labor Discussion Paper Series 209922, The World Bank.
  • Handle: RePEc:wbk:hdnspu:209922
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    File URL: https://documents.worldbank.org/curated/en/099627204282614604/pdf/IDU-d9a4bac6-a0ac-44d9-91f0-3e19f23984b2.pdf
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