Automation, AI, and the Intergenerational Transmission of Knowledge

Enrique Ide

No 20940, CEPR Discussion Papers from Centre for Economic Policy Research

Abstract: Recent advances in Artificial Intelligence (AI) have sparked expectations of unprecedented economic growth. Yet, by enabling senior workers to accomplish more tasks independently, AI may reduce entry-level opportunities, raising concerns about how future generations will acquire expertise. This paper develops a model to examine how automation and AI affect the intergenerational transmission of tacit knowledge — practical, hard-to-codify skills critical to workplace success. I show that the competitive equilibrium features socially excessive automation of early-career tasks, and that improvements in such automation generate an intergenerational trade-off: they raise short-run productivity but weaken the skills of future generations, slowing long-run growth — sometimes enough to reduce welfare. Back-of-the-envelope calculations suggest that AI-driven entry-level automation could reduce the long-run annual growth rate of U.S. per-capita output by 0.05 to 0.35 percentage points, depending on its scale. I further show that AI co-pilots can partially offset lost learning by assisting individuals who fail to acquire skills early in their careers. However, they may also weaken juniors’ incentives to develop such skills. These findings highlight the importance of preserving and expanding early-career learning opportunities to fully realize AI’s potential.

Keywords: Artificial intelligence; Automation; Long-run economic growth; Tacit knowledge (search for similar items in EconPapers)
JEL-codes: J24 O33 O40 (search for similar items in EconPapers)
Date: 2025-12
References: Add references at CitEc
Citations:

Downloads: (external link)
https://cepr.org/publications/DP20940 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cpr:ceprdp:20940

Ordering information: This working paper can be ordered from
https://cepr.org/publications/DP20940

Access Statistics for this paper

More papers in CEPR Discussion Papers from Centre for Economic Policy Research 33 Great Sutton Street, London EC1V 0DX, UK.
Bibliographic data for series maintained by CEPR ().