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How and for whom using generative AI affects creativity: A field experiment
Shuhua Sun1, Zhuyi Angelina Li2, Maw-Der Foo3
1A. B. Freeman School of Business, Tulane University.
Abstract:
We develop a theoretical perspective on how and for whom large language model (LLM) assistance influences creativity in the workplace. We propose that LLM assistance increases employees' creativity by providing cognitive job resources. Furthermore, we hypothesize that employees with high levels of metacognitive strategies-who actively monitor and regulate their thinking to achieve goals and solve problems-are more likely to leverage LLM assistance effectively to acquire cognitive job resources, thereby increasing creativity. Our hypotheses were supported by a field experiment, in which we randomly assigned employees in a technology consulting firm to either receive LLM assistance or not. The results are robust across both supervisor and external evaluator ratings of employee creativity. Our findings indicate that LLM assistance enhances employees' creativity by providing cognitive job resources, especially for employees with high (vs. low) levels of metacognitive strategies. Overall, our field experiment offers novel insights into the mediating and moderating mechanisms linking LLM assistance and employee creativity in the workplace. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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