Empirical Analysis of the Impact of Ai on the Employment of Em-ployees in Service Enterprises
Year: 2025
Type: article
Abstract: With the development of artificial intelligence technology, its replacement impact on occupation has been one of the hot topics of discussion, especially the breakthrough development of generative AI, which has caused people's further concern about "machine replacing human". As the service industry absorbs the largest employment population, whether and what impact the development and application of artificial intelligence technology will have on the employment of the service industry is an urgent question to be answered. Based on the data of listed enterprises in the service industry from 2014-2022, this study uses the difference-difference method to study the impact of the application of artificial intelligence technology on the number of employees, the skill structure of employees and the income of employees in the service industry from the enterprise level. The main conclusions of this study are as follows: First, although the high-risk occupations replaced by artificial intelligence are still mainly concentrated in the manufacturing industry, the risk of service occupations being replaced by artificial intelligence is gradually becoming prominent; Second, the application of artificial intelligence technology in service enterprises will increase the total number of employees and absorb more employment. Third, despite the increase in the number of employees, this demand is mainly reflected in the demand for high-skilled employees, and the demand for medium-low skilled employees is reduced, showing a trend of "degree-position" polarization; Finally, in terms of employee income, the application of artificial intelligence technology in service enterprises has caused a certain downward trend in employee income, which is also one of the negative effects of de-skills, leading to the decline of employees' bargaining ability on salary, resulting in income inequality.
Authors: Shaoyun Lin, Dorj Tuvd, Ochgerel Buljinsuren
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6949509890
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