The Impact of Artificial Intelligence Implementation on Job Stability Through Job Polarization and Access to Training in Indonesia

Titi Haryanti; Supriandi Supriandi

doi:10.31004/riggs.v4i4.5420

Authors

Titi Haryanti Politeknik Tunas Pemuda Tangerang
Supriandi Universitas Nusa Putra

DOI:

https://doi.org/10.31004/riggs.v4i4.5420

Keywords:

Access to Training, Artificial Intelligence Implementation, Job Polarization, Job Stability, SEM-PLS

Abstract

The increasing adoption of artificial intelligence (AI) has significantly transformed organizational processes and labor market structures, raising concerns about employment outcomes, particularly job stability. This study investigates the impact of AI implementation on job stability in Indonesia, with job polarization and access to training examined as mediating variables. Using a quantitative research design, data were collected from 130 employees across various industries in Indonesia through a structured questionnaire measured on a five-point Likert scale. The data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS 3). The results reveal that AI implementation has a significant direct effect on job stability. Moreover, AI implementation significantly increases job polarization, which negatively affects job stability, while simultaneously enhancing access to training, which positively influences job stability. The mediation analysis demonstrates that job polarization and access to training partially mediate the relationship between AI implementation and job stability, with access to training exhibiting a stronger mediating effect. These findings suggest that the employment consequences of AI are not purely deterministic but are shaped by organizational strategies and human capital investments. The study contributes to the literature on AI and the future of work by providing empirical evidence from an emerging economy context and highlights the critical role of inclusive training and reskilling initiatives in sustaining job stability amid AI-driven transformation.

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