This paper examines how automation and robotization affect job displacement in Uzbekistan, moderated by skill adaptation. The study adds to the blank territory in terms of the nexus of Industry 4.0 forces and labor market outcomes in Central Asian transitional economies. A cross-sectional survey of 250 employees in manufacturing, services and agriculture industries in Uzbekistan was conducted quantitatively. The use of Structural Equation Modelling (SEM), multiple regression, and Pearson correlation analyses were used. Cronbach's alpha was used to assess reliability. Automation is a strong predictor of job displacement (= 0.54, p < 0.001). This relationship is moderated by skill adaptation and displacement among more digitally literate workers is buffered (R 2 = 0.61). Demographic analysis shows that younger, urban workers have a higher perception of automation threat. The cross-sectional nature does not allow causal inference. Results might not be generalizable to the Uzbekistan formal sector. It is suggested that future longitudinal studies should be developed. Employers and policymakers should invest in reskilling programs and digital literacy campaigns to reduce technological unemployment. The risk of unequal access to policy response in a transitioning economy of Uzbekistan is the growth of the inequality between digitally literate and non-literate employees. It is one of the first empirical quantitative studies that investigate the labor-market effects of automation in Uzbekistan through the use of SEM methodology.
Publication Date: 2026-06-21