The Impact of Generative AI Development on Unemployment in the Financial Industry in China and the United States

Abstract

The rapid development of generative artificial intelligence is triggering far-reaching structural changes in the labor market in the global financial industry. This paper aims to study the differentiated impact of generative AI on the unemployment rate in the financial industry in China and the United States and its response strategies. Generative AI, with its creative content generation, complex decision simulations, and unstructured data processing capabilities, is reshaping the employment landscape in the knowledge-intensive industry of finance. China and the United States have shown completely different influence paths due to different financial structures, technological foundations, and policy orientations: China's bank-led financial system is facing a large number of low- and middle-skilled job transformation pressures, but through strong government intervention and "stable employment" policies, the impact is buffered; The United States is market-led, with prominent risk of replacing mid-range analytical positions and relying on market regulation mechanisms to cope with technological shocks. This study not only reveals the alternative mechanism and creative effect of generative AI on financial employment, but also proposes a differentiated strategic response framework for the two countries, providing an important reference for the global financial industry to achieve a smooth transformation in technological change.