INVESTIGATING THE IMPACT OF ARTIFICIAL INTELLIGENCE ON JOB AUTOMATION AND EMPLOYMENT IN THE GLOBAL WORKFORCE

Abstract

The rapid diffusion of artificial intelligence has intensified global debate regarding its implications for employment, job displacement, and workforce transformation. This study investigates the multifaceted relationship between AI adoption and labour-market outcomes using a mixed-methods experimental approach that integrates quantitative econometric analysis with qualitative thematic assessment. Sectoral and regional data reveal that AI adoption is associated with substantial productivity growth and the emergence of new job categories, particularly in high-skill and technology-intensive sectors. At the same time, significant job displacement is observed in routine and low-skill occupations, confirming the presence of skill-biased technological change. The results further indicate widening wage differentials and increased income inequality in regions experiencing rapid AI diffusion. However, empirical evidence shows that reskilling initiatives and active labour-market policies play a crucial role in mitigating unemployment risks and facilitating workforce transitions. Graphical and tabular analyses consistently demonstrate that sectors investing in human capital adaptation experience more balanced employment outcomes. Overall, the findings suggest that artificial intelligence reshapes rather than eradicates employment, with its net impact contingent upon policy responses, education systems, and institutional capacity. The study contributes to ongoing discourse by providing empirical evidence that supports a nuanced understanding of AI as both a disruptive and enabling force in the modern labour market, underscoring the importance of inclusive and adaptive strategies for sustainable economic development.