Changes in demand and optimization of cultivation paths of smart financial talents for corporate carbon reduction and pollution reduction under the risk constraints of artificial intelligence application: a mixed research approach

Abstract

Environmental pollution and climate change are major challenges on the road to sustainable development for human society. In this regard, based on the risk constraints of the application of artificial intelligence, this paper takes 2712 A-share listed manufacturing enterprises from 2012 to 2024 as research objects, and utilizes the mixed research method of qualitative combined with quantitative analysis to examine the impact of artificial intelligence on the reduction of pollution and carbon dioxide of enterprises, as well as the impact of carbon dioxide reduction and pollution reduction of enterprises on the demand for intelligent financial talents. The study shows that the application of artificial intelligence can effectively reduce the sulfur dioxide and carbon dioxide emissions of enterprises, and play the effect of pollution reduction and carbon reduction. The regression coefficients of the degree of demand for intelligent financial talents in enterprise pollution reduction and carbon reduction are 0.273 and 0.234 respectively, indicating that for every unit increase in pollution reduction and carbon reduction, the demand for intelligent financial talents in enterprises will increase by 0.273 and 0.234 units respectively. At present, the market demand for intelligent financial talents has formed a large gap, the traditional financial education training path, and can not meet the current economic and social demand for talents, there is an urgent need to explore the new path of high-quality training of intelligent financial talents.