ARTIFICIAL INTELLIGENCE, AUTOMATION, AND LABOR MARKET TRANSFORMATION: EVIDENCE ON EMPLOYMENT, SKILLS, AND WAGE DYNAMICS

Abstract

Artificial intelligence (AI) and automation transformed global labor markets by reshaping employment structures, skill requirements, and wage dynamics. This study examined the impact of AI adoption on employment patterns, skill transformation, and wage outcomes using a quantitative research design. Data were collected from a sample of 320 employees across IT, banking, manufacturing, education, and service sectors. The analysis applied descriptive statistics and structural equation modeling to evaluate relationships among variables. Results indicated that AI adoption significantly influenced employment patterns (β = 0.63, p < 0.001), skill transformation (β = 0.67, p < 0.001), and wage dynamics (β = 0.61, p < 0.001). Skill transformation also significantly affected employment patterns (β = 0.58, p < 0.001) and wage dynamics (β = 0.55, p < 0.001). Mediation analysis confirmed that skill transformation played a significant role in linking AI adoption with both employment outcomes and wage distribution. The model explained 52% variance in employment patterns, 45% in skill transformation, and 49% in wage dynamics. Findings demonstrated that AI created both opportunities and challenges by increasing demand for high-skilled labor while reducing routine-based employment. Wage inequality increased due to differential skill adaptation across workers. The study highlighted the importance of reskilling and education reforms to ensure inclusive labor market outcomes in the era of AI-driven transformation.