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More flow and less objectification: Dual influence mechanisms of generative AI use on employees’ proactive behaviors

Sep 2026 · BMC Psychology · 0 citations

TL;DR

A dual-pathway model of value-creation is constructed to explore the underlying mechanisms and boundary conditions governing the impact of GAI use on employee proactive behavior and provide actionable practical guidance for corporate digital transformation and GAI deployment in modern enterprises.

Abstract

Technological innovations represented by generative artificial intelligence (GAI) are disrupting existing work modalities, leaving academia in urgent need of empirical research regarding how GAI usage shapes employee cognition and behavior. Grounded in Social Cognitive Theory (SCT), this study constructs a dual-pathway model of value-creation to explore the underlying mechanisms and boundary conditions governing the impact of GAI use on employee proactive behavior (PB). Utilizing a three-wave time-lagged survey with a sample of 380 full-time knowledge workers, we investigate the mediating roles of flow experience (FE) (representing the “empowering humans” pathway) and workplace objectification (WO) (representing the “liberating humans” pathway), as well as the moderating role of digital literacy (DL). Generative AI use is positively related to employee proactive behavior. Specifically, GAI use cultivates flow experiences and mitigates workplace objectification, both of which partially mediate the relationship between GAI use and proactive behavior. Furthermore, digital literacy exhibits an asymmetrical moderating effect: it strengthens the negative relationship between GAI use and workplace objectification, along with the corresponding indirect effect; however, its moderating effect on the relationship between GAI use and flow experience is not statistically significant. These conclusions offer critical theoretical implications for human-AI collaboration in organizations and provide actionable practical guidance for corporate digital transformation and GAI deployment in modern enterprises.

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