Worker Repositioning and Technological Change: Evidence from an Online Labor Market

Published Online:https://doi.org/10.1287/orsc.2025.20566

Technological change reshapes labor markets not only by changing labor demand but also by altering labor supply, as workers reallocate effort across tasks and opportunities in response to technological advances. Yet research has focused more on demand-side effects than on how workers themselves adapt. In this research, we examine worker repositioning on a large online labor market following the launch of ChatGPT in November 2022. We argue that the launch of ChatGPT reduced expected returns to labor in exposed skill domains and develop and test a series of hypotheses regarding how this shock is associated with participation, horizontal positioning, and vertical positioning among workers on the platform. Using proprietary data on incumbent freelancers and a difference-in-differences design that leverages cross-sectional variation in pre-period AI exposure and skill-level, we show that freelancers more exposed to AI shift away from prior domains and reorient bidding toward higher-value contracts. In contrast, high skill-level freelancers, who face greater adjustment costs, are less likely to reduce participation on the platform, reposition across domains, and move upmarket. These findings highlight how technological shocks reshape labor markets through supply-side adaptation and how domain-specific human capital constrains worker responses.

INFORMS site uses cookies to store information on your computer. Some are essential to make our site work; Others help us improve the user experience. By using this site, you consent to the placement of these cookies. Please read our Privacy Statement to learn more.