The rapid evolution of new technologies, particularly artificial intelligence (AI), has sparked questions about whether these emerging frontier technologies might increasingly substitute employees performing complex tasks. In contrast to such fears, a new IZA discussion paper by Melanie Arntz, Sabrina Genz, Terry Gregory, Florian Lehmer and Ulrich Zierahn-Weilage finds evidence of a deepening de-routinization along with an increase in between-firm inequality.
To examine how the diffusion of new technologies at the firm level contributes to aggregate occupational changes, the authors collect novel firm-level data on the actual adoption of frontier technologies and link this to administrative data records from the German Federal Employment Agency. A key advantage of the data: it allows distinguishing between non-adopters, digital adopters, and frontier adopters.
Strong de-routinization of the German workforce between 2011 and 2016
The study starts by documenting a substantial decline in routine cognitive and manual jobs by about 2.4 percentage points among the German workforce from 2011 to 2016. The data further shows that the share of routine occupations fell the most in firms adopting frontier technologies, followed by those adopting digital technologies.
Based on a decomposition approach, the authors are able to show how the inequality between firms within the group of frontier adopters explains their contribution to overall de-routinization. The key insight: the adoption of frontier technology does not lead to a widespread replacement of routine jobs within firms. Rather, only a subset of larger firms is responsible for the de-routinization among frontier adopters.
Adoption in frontier technologies in larger firms boosts de-routinization
Delving deeper into the mechanisms behind the findings, the authors reveal that the aggregate decline in the routine employment share among workers employed at frontier adopters occurs because initially larger frontier adopters reduce their routine employment share in contrast to smaller frontier adopters (the authors call this the “scale effect”). The mechanisms are explained with differences in how firms adopt frontier technologies, reflected in changing skill demands and training needs.
Frontier adopters with larger non-routine cognitive shares grow faster
As an additional reason, the authors demonstrate that initially less routine-intensive firms experience stronger employment growth (“composition effect”). In other words, firms that already have a higher share of non-routine cognitive workers are better positioned to gain benefits from technology adoption and thus grow faster. Altogether, the study indicates that the routine-replacing effect of frontier technologies hinges on having the right skills – either from the start or by investing in upskilling the workforce.