Research on the Impact and Evolutionary Prediction of Generative Artificial Intelligence on Occupations: Taking STEM, Technical, and Artistic Professions as Examples

DOI: https://doi.org/10.62517/jike.202604205

Author(s)

Xiangpei Meng1,*, Liying Yan2, Qing Zheng1

Affiliation(s)

1College of Information Technology, Zhejiang Fashion Institute of Technology, Ningbo, China 2Ningbo Polytechnic University, School of Supply Chain Management, Ningbo, China *Corresponding author

Abstract

The rapid development of generative artificial intelligence is reshaping occupational structures, yet the mechanisms through which it affects different types of occupations and their evolutionary trends require further in-depth exploration. This paper takes three major industries-STEM, technical trades, and the arts-as its research subjects, selecting engineers, maintenance workers, and dancers as typical representatives of each industry. It constructs a seven-dimensional factor analysis framework encompassing AI penetration rate, economic environment impact, skill complexity, education and training investment, time series trends, industry characteristics, and technological growth factors. Based on occupational wage data from the U.S. Bureau of Labor Statistics from 2019 to 2024, data were collected using a combination of literature review and web crawling methods. A grey correlation model was first used to identify the key influencing factors for each occupation, followed by the construction of a ridge regression occupational demand prediction model to forecast the development trends of the three types of occupations. Cross-validation results indicate that the goodness of fit of the ridge regression model is significantly better than that of traditional regression models. The study reveals that the impact of generative AI on the three types of occupations shows significant heterogeneity: STEM occupations exhibit a trend of technological synergy and enhancement, technical occupations demonstrate a strong buffering capacity against substitution, while artistic occupations face a complex situation involving the reconstruction of creative boundaries.

Keywords

Generative Artificial Intelligence; Occupational Impact; Grey Correlation Analysis; Ridge Regression Analysis; Occupational Evolution Prediction

References

[1]Frey C. B., Osborne M. A. The future of employment: How susceptible are jobs to computerization?. Technological Forecasting and Social Change, 2017, 114: 254-280. [2]Acemoglu D, Restrepo P. Robots and jobs: Evidence from US labor markets. Journal of Political Economy, 2020, 128(6): 2188-2244. [3]Mokyr J., Vickers C., Ziebarth N. L. The history of technological anxiety and the future of economic growth: Is this time different?. Journal of Economic Perspectives, 2015, 29(3): 31-50. [4]Autor D. H. Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 2015, 29(3): 3-30. [5]Cai Yuezhou, Chen Nan. Artificial Intelligence, High-Quality Growth and High-Quality Employment under the New Technological Revolution. The Journal of Quantitative & Technical Economics, 2019, 36(5): 3-22. [6]Acemoglu D., Restrepo P. Artificial intelligence, automation and work//Agrawal A, Gans J, Goldfarb A. The Economics of Artificial Intelligence: An Agenda. Chicago: University of Chicago Press, 2018: 197-236. [7]Long Yuntao, Liu Haibo, Cai Yuezhou. The Impact of Artificial Intelligence Technology on Labor Employment-From the Perspective of Literature Review. China Soft Science, 2020, (12): 56-64. [8]Li Haifei, Gao Xueke, Liu Aiwen. A Review of Recent Research on the Impact of Artificial Intelligence on Employment. Productivity Research, 2025, (12): 149-155. [9]Zeng Xiankui. A Review of Research on the Impact of Artificial Intelligence Development on Labor and Employment. Journal of China University of Labor Relations, 2025, 39(4): 27-40. [10]Sun Zao, Hou Yulin. How Does Industrial Intelligence Reshape the Employment Structure of Labor Force. China Industrial Economics, 2019, (5): 61-79. [11]Zhou Zhen. Research on the Multidimensional Impact of Artificial Intelligence on Employment and Countermeasures. Shandong Macroeconomics, 2025, (06): 17-25.