ARTIFICIAL INTELLIGENCE AND THE TRANSFORMATION OF LABOR MARKETS: AN EMPIRICAL ANALYSIS OF EMERGING SKILLS DEMAND

Abstract

The rapid diffusion of artificial intelligence (AI), and generative AI in particular, is reshaping the composition of labor demand across the global economy. This paper synthesizes recent cross-country statistical evidence from the International Labour Organization (ILO), the Organisation for Economic Co-operation and Development (OECD), the World Bank, and the World Economic Forum (WEF) to examine how AI exposure is redistributing skill requirements within occupations rather than uniformly eliminating jobs. Using a comparative, secondary-data approach, the study finds that roughly one-quarter of global employment is exposed to generative AI, with exposure concentrated in high-income economies and in occupations dominated by women. Rather than displacing workers outright, AI exposure is associated with rising demand for managerial, business, cognitive, and digital skills, alongside a projected net gain of tens of millions of jobs worldwide by 2030 accompanied by a substantial reskilling burden. The findings suggest that the central labor-market risk of AI is skill obsolescence and uneven adaptation capacity rather than mass unemployment, with particular implications for developing economies such as Uzbekistan, where AI usage remains concentrated in a narrow set of occupations. The paper concludes with policy implications for education systems, vocational training, and labor-market institutions.