A One-Year Longitudinal Study Examining the Direct and Indirect Effects of AI Dependence on Work Engagement and Gender Differences

As artificial intelligence (AI) products become increasingly integrated into daily life, AI dependence has gained significant public and scholarly attention. While existing research has primarily examined its impact on students, few studies have investigated its association with employee career development, particularly work engagement. Our one-year longitudinal study involving 1108 employees aged 21-60 examined the long-term effect of AI dependence on work engagement, incorporating work self-efficacy as a mediator and gender as a moderator. Using three-wave survey data, we found that AI dependence at Time 1 (T1) directly predicted work engagement at Time 3 (T3), and also exerted a significant indirect effect through work self-efficacy at Time 2 (T2). While the mediating effect of T2 work self-efficacy showed no gender differences, the direct effect of T1 AI dependence on T3 work engagement was significantly stronger among male employees. These findings systematically address questions regarding the long-term, mediated, and gender-differentiated effects of AI dependence. They provide important warnings regarding AI dependence prevention and deliver practical implications for maintaining and enhancing employee self-efficacy and engagement in the AI era.

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Publication Details

Journal
Behavioral Sciences
Published
2025-12-24
DOI
https://doi.org/10.3390/bs16010044
Primary Topic
Technostress in Professional Settings
Type
article
Field-Weighted Citation Impact
0.00

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article

A One-Year Longitudinal Study Examining the Direct and Indirect Effects of AI Dependence on Work Engagement and Gender Differences

Qingqi Liu, Jiani Wen, Yuju Lei
Behavioral Sciences
Technostress in Professional Settings
article

A One-Year Longitudinal Study Examining the Direct and Indirect Effects of AI Dependence on Work Engagement and Gender Differences

Qingqi Liu, Jiani Wen, Yuju Lei
article en

Abstract

As artificial intelligence (AI) products become increasingly integrated into daily life, AI dependence has gained significant public and scholarly attention. While existing research has primarily examined its impact on students, few studies have investigated its association with employee career development, particularly work engagement. Our one-year longitudinal study involving 1108 employees aged 21-60 examined the long-term effect of AI dependence on work engagement, incorporating work self-efficacy as a mediator and gender as a moderator. Using three-wave survey data, we found that AI dependence at Time 1 (T1) directly predicted work engagement at Time 3 (T3), and also exerted a significant indirect effect through work self-efficacy at Time 2 (T2). While the mediating effect of T2 work self-efficacy showed no gender differences, the direct effect of T1 AI dependence on T3 work engagement was significantly stronger among male employees. These findings systematically address questions regarding the long-term, mediated, and gender-differentiated effects of AI dependence. They provide important warnings regarding AI dependence prevention and deliver practical implications for maintaining and enhancing employee self-efficacy and engagement in the AI era.

Behavioral SciencesVol. 16(1)
Beijing Normal University (CN), Hubei University of Arts and Science (CN)
Beijing Normal University, Jilin Office of Philosophy and Social Science, National Office for Philosophy and Social Sciences
Gender equality
Openalex Percentile: Top 29%
Technostress in Professional Settings
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A One-Year Longitudinal Study Examining the Direct and Indirect Effects of AI Dependence on Work Engagement and Gender Differences — Qingqi Liu, Jiani Wen, et al. · Behavioral Sciences (2025) | TGRS Research Map | TGRS