The Labor Market Impact of Digital Technologies

Abstract

We investigate the impact of digital technology on employment patterns in Korea, where firms have rapidly adopted digital technologies such as artificial intelligence (AI), big data, and cloud computing. By exploiting regional variations in technology exposure, we find significant negative effects on female workers, particularly those in non-IT (information technology) services. This contrasts with previous technological disruptions, such as the IT revolution and robotization, which primarily affected male workers in manufacturing. The negative employment effect of AI did not differ across educational groups, but big data and cloud computing more negatively affected workers with less education. In IT services, although employment shares of professionals and technicians declined, vacancy postings for these positions increased, implying a shift in labor demand toward newer skill sets within the same occupations. These findings highlight both the labor displacement and the new opportunities generated by digital transformation.

Introduction

Technological advancements and their effects on labor markets have been a central focus of research for decades. Recently, the rise of generative artificial intelligence (AI) has sparked even greater interest in how new technologies will reshape employment patterns. While it is well established that the IT (information technology) revolution contributed to job polarization by replacing routine tasks (Autor, Levy, and Murnane, 2003; Autor and Dorn, 2013; Lee and Shin, 2017; Aum, Lee, and Shin, 2018), there is a growing need for empirical research to understand the effects of newer digital technologies, such as AI, big data analytics, and cloud computing. These digital technologies are anticipated to transform production processes and work practices, with some suggesting that their impacts could differ significantly from those seen during the IT revolution (Bharadwaj et al., 2013; Adner, Puranam, and Zhu, 2019). In particular, the potential of digital technologies to alter the demand for workers with different skill sets has become a crucial subject of investigation.

We examine how digital technology has influenced employment patterns in Korea, a country at the forefront of digital transformation. By leveraging regional variations in exposure to digital technology, we analyze the employment effects of AI, big data, and cloud computing across workers in different occupations and sectors, categorized by gender and education level. We find that the adoption of digital technologies may lead to outcomes distinct from those of previous technological shifts, such as the IT revolution or advances in industrial robotics.

The adoption of digital technologies in Korea appears to have a negative effect on employment. The negative effect is more pronounced for female workers. By educational groups, while AI does not show a significantly different effect, big data and cloud computing more negatively affect the employment of less educated workers.

Across industries, the negative effects of digital technology adoption on employment have been largest in non-IT services rather than in manufacturing. Women were especially negatively affected in non-IT services. Employment in IT services, on the other hand, was positively affected by big data and cloud computing, implying reallocation across sectors. The employment of men and less educated workers within IT services rose in response to the adoption of big data and cloud computing. Within each industry, the effect varied across occupations. In manufacturing, craft workers were the most negatively affected by big data and cloud computing, mirroring the pattern of job polarization caused by automation and robotization. In contrast, in IT services, professionals and technicians experienced the greatest reductions in employment shares. In non-IT services, elementary occupations—which have historically been less vulnerable to IT disruption—saw the steepest declines in employment shares. These findings by occupation and industry underscore the complexity of digital technology’s impact on labor markets.

The pronounced negative effect on female workers in non-IT services suggests that the nature of labor displacement caused by AI, big data, and cloud computing may differ from that of previous technological disruptions, which primarily affected male workers in manufacturing.

Finally, we find that the relationship between employment declines and job vacancies differed significantly across sectors and occupations. In manufacturing, craft jobs experienced reductions in both employment shares and vacancies, indicating diminished demand. In contrast, professional roles in IT services exhibited a paradoxical trend: While employment shares fell, vacancy postings for these positions increased, signaling a growing demand for professionals with new skill sets adapted to the new digital technologies. While digital technologies may reduce the number of traditional jobs, they are also creating new opportunities for workers who can meet the demands of evolving roles.