The Effects of AI Assistance on Self-Promotion

Alexander Koch (), Jenny Kragl (), Sijuan Ming () and Julia Nafziger ()
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Alexander Koch: Aarhus University
Jenny Kragl: EBS Business School
Sijuan Ming: Aarhus University
Julia Nafziger: Aarhus University

No 18441, IZA Discussion Papers from IZA Network @ LISER

Abstract: Persistent gender gaps in self-promotion contribute to unequal labor market outcomes. In this study, we investigate how AI-assisted writing tools shape self-promotion, and, as a secondary outcome, confidence and how these effects interact with gender. For this purpose, we conducted an online experiment in China in which participants wrote self-promotion texts, provided a numerical self-promotion score and stated their confidence about how they will perform in an upcoming math and logic test. We find suggestive evidence that AI assistance reduces numerical self-evaluations. Neither gender nor the interaction between gender and AI assistance is significantly related to self-promotion or confidence. We conduct a text analysis to investigate the mechanisms behind these results.

Keywords: self-promotion; confidence; AI assistance; gender gaps (search for similar items in EconPapers)
JEL-codes: C90 D03 D83 J16 M12 (search for similar items in EconPapers)
Date: 2026-03
New Economics Papers: this item is included in nep-ain and nep-exp
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