DAMPAK AI DISRUPTION THREAT TERHADAP INNOVATIVE WORK BEHAVIOUR MELALUI TECHNOLOGY INSECURITY PADA KARYAWAN GENERASI MILENIAL DI ERA TRANSFORMASI DIGITAL

Fadhila Damayanti Prayitno; Yeni  Absah; Romi Fadillah  Rahmat

doi:10.34127/jrlab.v14i3.1886

Authors

Fadhila Damayanti Prayitno Universitas Sumatera Utara
Yeni Absah Universitas Sumatera Utara
Romi Fadillah Rahmat Universitas Sumatera Utara

DOI:

https://doi.org/10.34127/jrlab.v14i3.1886

Keywords:

AI Disruption Threat, Technology Insecurity, Innovative Work Behaviour, JD-R Theory, Social Exchange Theory, Karyawan Milenial

Abstract

This study aims to analyze the influence of AI Disruption Threat on Innovative Work Behavior, with Technology Insecurity as a mediating variable on millennial employees in Medan City, Indonesia. This study uses a quantitative approach with Partial Least Squares–Structural Equation Modeling (PLS-SEM) analysis techniques through SmartPLS 4 software. A total of 92 respondents who are millennial employees aged 25–40 years and working in digital-based organizations participated in this study. The results of model testing indicate that all constructs meet the criteria for reliability and convergent and discriminant validity. Empirically, AI Disruption Threat has a significant positive effect on Innovative Work Behavior (β = 0.331; p < 0.05) and a strong positive effect on Technology Insecurity (β = 0.611; p < 0.001). In contrast, Technology Insecurity had a significant negative effect on Innovative Work Behavior (β = –0.437; p < 0.001). Mediation analysis showed that Technology Insecurity partially mediated the relationship between AI Disruption Threat and Innovative Work Behavior. This research model explained 66.9% of the variance in Technology Insecurity and 60.5% in Innovative Work Behavior, indicating moderate to high explanatory power. These findings confirm that AI disruption has a dual effect—as a catalyst for innovation and a source of technological anxiety—that can increase or decrease innovative behavior depending on organizational support and employee psychological well-being. This research extends the Job Demands–Resources (JD-R) and Social Exchange Theory (SET) frameworks by revealing that employees' innovative responses to AI are highly dependent on the balance between technological demands and available organizational resources. Practically, organizations need to balance digital advancement with psychological empowerment through training, transparent communication, and supportive leadership so that AI-based transformation truly drives innovation, rather than the other way around.

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