The impact of GenAI on the demand for entry-level jobs

Abstract

The paper investigates the impact of generative artificial intelligence (GenAI) on labor demand across entry-level and senior-level positions in Belgium between 2021 and 2024. Focusing on the task-based model of technological change and implementing a Difference-in-Differences (DiD) framework, the study analyzes VDAB job vacancy data across high and low GenAI-impact sectors. Results has shown the slight decline in job vacancies after GenAI introduction, the impact varied across sectors and experience levels. Entry-level roles were more vulnerable in highly automatable sectors, whereas senior roles remained stable but did not experience a statistically significant rise. The findings suggest a future trasformation of job structures rather than displacement, offering practical implications for policymakers and enterpreneurs.This study contributes to the growing empirical literarure on GenAI and labor by fulfilling a existing research gap with sectoral and longitunal data from the Belgian labor market.