The Impact of Artificial Intelligence on Employment and Wage Inequality

Abstract

Introduction: Artificial Intelligence (AI) is playing an increasingly prominent role in technological progress, impacting not only the structure of jobs but also wages and the labor market across the globe. Despite its promise for increased productivity, efficiency, and innovation, there are concerns about the implications of AI on job security and income inequality. The purpose of this study was to assess the employment implications and wage gaps across various industries and skill sets following the adoption of AI. It also explored how AI use relates to job insecurity, salary increases, and upskilling. While AI is increasingly being incorporated into business operations, there is a lack of evidence on the concurrent effects of AI on employment and wage inequality, especially across occupational groups. Methods: The cross-sectional survey was carried out with 350 respondents across a number of industries, such as Information Technology, Manufacturing, Healthcare, Finance, Education, and Customer Service. Data were gathered from the structured questionnaire and analyzed using descriptive statistics, Chi-square testing, one-way analysis of variance (ANOVA), and multiple linear regression techniques. Results: The findings showed that 72.6% of the respondents stated that their companies were currently using AI. Almost half of those who answered (48.9%) believed that AI would create new job prospects, while 24.6% were worried about job loss. There were substantial differences between skill categories in terms of wage growth (high-skilled workers had higher wage growth than low-skilled workers, p < 0.001, 8.7% vs. 2.8%). There was a statistically significant relationship between the adoption of AI and concerns about job displacement (χ² = 12.84, p = 0.002). In addition, there were significant correlations between wage growth and the adoption level of AI (β = 0.38, p < 0.001) and worker skill level (β = 0.42, p < 0.001), as well as participation in AI-related training programs (β = 0.21, p = 0.008). Conclusion: The results indicate that AI is significantly shaping today's job market, generating new job opportunities and also playing a significant role in the emergence of skill-based wage gaps. While the economic value of AI integration seems to be larger for more skilled workers, AI workforce training and reskilling programs could be key to mitigating negative labor market effects on vulnerable populations. The results underscore the importance of employment policies and capacity development initiatives based on evidence to drive inclusive and sustainable labor market development in the era of growing AI adoption.