Artificial intelligence, hiring and employment: Job postings evidence from Sweden - Erik Engberg; Mark Hellsten; Farrukh Javed; Magnus Lodefalk; Radka Sabolová; Sarah Schroeder; Aili Tang (Örebro University School of Business, 2024)
This paper investigates the impact of artificial intelligence (AI) on hiring and employment, using the universe of job postings published by the Swedish Public Employment Service from 2014-2022 and universal register data for Sweden. We construct a detailed measure of AI exposure according to occupational content and find that establishments exposed to AI are more likely to hire AI workers. Survey data further indicate that AI exposure aligns with greater use of AI services. Importantly, rather than displacing non-AI workers, AI exposure is positively associated with increased hiring for both AI and non-AI roles. In the absence of substantial productivity gains that might account for this increase, we interpret the positive link between AI exposure and non-AI hiring as evidence that establishments are using AI to augment existing roles and expand task capabilities, rather than to replace non-AI workers.
Keywords: D22; J23; J24; O33; 330; Artificial Intelligence; Technological Change; Automation; Labour Demand