Intelligent technology is an important force in labor production and is conducive to improving employment quality. However, the existing literature on the impact of labor intelligence on employment quality and its mechanism is insufficient. This paper argues that labor intelligence can improve employment quality by improving workers’ non-cognitive ability, and it presents heterogeneity depending on workers’ age, gender, and skill level. This paper uses the China Labor Force Dynamics Survey (CLDS) data to conduct an empirical study, and the results show that (1) labor intelligence has a significant positive impact on employment quality. Labor intelligence improves the employment quality of workers, and the conclusion remains robust after endogenous processing and robustness tests; (2) labor intelligence has a heterogeneous effect on employment quality. Compared with female workers, labor intelligence has a more obvious effect on improving the employment quality of male workers. In different age groups, labor intelligence has a greater effect on the improvement of the employment quality of workers aged 35 and below. In different skill groups, labor intelligence plays a greater role in improving the employment quality of highly skilled workers; (3) further analysis of the moderating effect shows that non-cognitive ability plays a positive moderating role in the relationship between labor intelligence and employment quality, indicating that the improvement of non-cognitive ability strengthens the role of labor intelligence in improving employment quality. Compared with the existing literature, this paper discusses the influence of labor intelligence on employment quality, and provides empirical evidence for the mechanism and heterogeneity of labor intelligence in improving employment quality. The possible innovations of this paper are as follows: firstly, unlike existing literature, which mainly analyzes the impact of intelligence on employment and wages from the macro level, this paper uses CLDS individual questionnaire data to analyze the impact of labor intelligence on individual employment quality from the micro level. Secondly, unlike different pieces of literature which mostly explore the impact of intelligence on single indicators such as income, work environment, and work intensity, this paper intends to construct comprehensive indicators of employment quality from monetary income and working conditions to analyze the impact of labor intelligence on employment quality. Thirdly, it analyzes the moderating effect of non-cognitive ability on the relationship between labor intelligence and employment quality, and pays attention to the heterogeneous influence of labor intelligence on employment quality. This study shows that the development of labor intelligence is helpful to improve the employment quality of workers and improve the employment quality by improving the non-cognitive ability of workers. Therefore, it is important to encourage the development of new technologies such as artificial intelligence, increase policy support and financial investment in intelligent technologies, and continuously deepen technological reforms so that ordinary workers can enjoy the “technological dividend” brought by intelligent technologies. Moreover, it is necessary to develop targeted skills training services, encourage enterprises to increase pre-employment and transfer skills training, improve workers’ skills level and enhance skills-job matching. Finally, it is necessary to focus on the cultivation of workers’ non-cognitive abilities, improve their quality, and help them actively adapt to labor intelligence to achieve a steady improvement in employment quality.