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

Evi Komala; Intan Lidiya Widuri; Mohammad Adrian; Ria Yuli Hastini; Sri Hartati

Authors

Evi Komala Universitas Lampung
Intan Lidiya Widuri Universitas Lampung
Mohammad Adrian Universitas Lampung
Ria Yuli Hastini Universitas Lampung
Sri Hartati Universitas Lampung

Keywords:

Artificial Intelligence, performance management, job crafting, employee productivity

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.

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