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All Journal SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL
Hastini, Ria Yuli
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THE IMPACT OF ARTIFICIAL INTELLIGENCE–DRIVEN PERFORMANCE MANAGEMENT ON EMPLOYEE PRODUCTIVITY: THE MEDIATING ROLE OF JOB CRAFTING IN A MULTI-SECTOR STUDY ACROSS INDONESIA: DAMPAK MANAJEMEN KINERJA BERBASIS KECERDASAN BUATAN TERHADAP PRODUKTIVITAS KARYAWAN: PERAN MEDIASI JOB CRAFTING DALAM STUDI MULTI-SEKTOR DI SELURUH INDONESIA Komala, Evi; Widuri, Intan Lidiya; Mohammad Adrian; Hastini, Ria Yuli; Hartati, Sri
SOSIOEDUKASI Vol 14 No 4 (2025): SOSIOEDUKASI : JURNAL ILMIAH ILMU PENDIDIKAN DAN SOSIAL
Publisher : Fakultas Keguruan Dan Ilmu Pendidikan Universaitas PGRI Banyuwangi

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Abstract

The rapid adoption of artificial intelligence (AI) in performance management systems has transformed how organizations evaluate and enhance employee performance. However, empirical evidence on how AI-driven performance management improves employee productivity across diverse industrial sectors remains limited, particularly in emerging economies such as Indonesia. This study aims to examine the effect of AI-driven performance management on employee productivity, with job crafting serving as a mediating variable. Using a quantitative explanatory survey design, data were collected from 170 employees across multiple industries in Indonesia that have implemented AI-based performance management systems. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that AI-driven performance management has a positive and significant direct effect on employee productivity. Additionally, AI-driven performance management significantly enhances job crafting behaviors, which in turn positively influence employee productivity. Mediation analysis confirms that job crafting partially mediates the relationship between AI-driven performance management and employee productivity. These findings suggest that the productivity-enhancing potential of AI-based performance management is strengthened when employees are enabled to proactively redesign their work. This study contributes to the literature on technology-driven human resource management and provides practical insights for organizations seeking to integrate AI systems with employee-centered work practices.
Co-Authors Komala, Evi Mohammad Adrian Sri Hartati Widuri, Intan Lidiya