THE FUTURE OF THE LABOR MARKET IN THE CONTEXT OF AUTOMATION
Abstract
Objective: This study aims to assess the impact of automation on employment structures, identify emerging job categories, analyze social risks, and propose strategic responses to workforce challenges in the digital age. Method: The research applies predictive modeling and systemic-structural analysis to contextualize labor market shifts within Uzbekistan, offering localized insights alongside global trends. Results: The findings reveal declining demand for routine labor, growth in IT and service-related jobs, and the expansion of gig economy models; automation contributes to regional employment disparities and, while improving efficiency, intensifies risks of structural unemployment and social inequality. Novelty: Despite growing research on digital transformation, this study addresses a gap by linking labor market restructuring with socio-economic stability in transitional economies, emphasizing the urgent need for coordinated efforts among policymakers, industry, and education to ensure equitable labor market participation.