The Dual Effects of Artificial Intelligence on Employment Structure: An Empirical Study Based on Regression and Clustering Models

With the rapid development and widespread application of artificial intelligence technologies, the global employment landscape is undergoing profound changes. The demand for low-skilled jobs is decreasing, while the demand for high-skilled jobs is increasing. This study selects labour market data for major economies from 2015 to 2024, and applies regression and cluster analysis to explore the intrinsic link between the degree of technology penetration and labour restructuring. The study finds that AI technologies have replaced around a quarter of low-skilled jobs in manufacturing, while at the same time high-skilled jobs such as data science and AI development have grown rapidly, further widening the skills gap. Moreover, the impact has varied significantly across countries and industries. Developed countries have experienced a massive loss of low-skill jobs and a dramatic increase in high-skill jobs, while developing countries have experienced similar trends, but with relatively smaller changes. Based on the above findings, the study makes a series of targeted policy recommendations, including strengthening vocational training, promoting industrial upgrading, improving the social security system, and enhancing the adaptability of the labour force, with the aim of mitigating the impact of AI on the employment structure and promoting the smooth development of the labour market.