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All Journal MIX : Jurnal Ilmiah Manajemen Jurnal BISNIS & KEWIRAUSAHAAN YUME : Journal of Management International Journal of Accounting & Finance in Asia Pasific Journal of Economics and Management Scienties Jurnal Pendidikan Dasar dan Keguruan J-CEKI Jurnal Ekonomi, Manajemen, Akuntansi Joong-Ki
Basalamah, Indira
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Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Environmental Science Health Professions Library & Information Science Social Sciences

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Journal : Journal of Economics and Management Scienties

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AI-Driven Performance Management: Enhancing Objectivity and Efficiency Basalamah, Indira; P, Muhammad Carda
Journal of Economics and Management Scienties Volume 7 No. 3, June 2025
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/jems.v7i3.134

Abstract

Traditional performance management systems are frequently criticized for subjectivity, inconsistency, and delayed feedback. To address these limitations, organizations are increasingly adopting Artificial Intelligence (AI) to enable real-time, data-driven employee evaluations. While AI enhances objectivity and operational efficiency, its deployment introduces several critical challenges. These include algorithmic bias rooted in historical data, opacity in decision-making logic, employee concerns about digital surveillance, and organizational resistance to automated appraisal systems. This article presents a systematic review of scholarly literature and enterprise case studies published between 2020 and 2024 to examine how AI is reshaping performance management practices. Four core themes are identified: bias mitigation, feedback automation, ethical risks, and large-scale implementation. The analysis reveals that AI can improve evaluation accuracy and responsiveness—particularly in hybrid and digital-first environments—when accompanied by transparency, ethical oversight, and human interpretability. Rather than replacing managerial judgment, AI should serve as an augmentation tool within a human-centered performance ecosystem.
Co-Authors Abdul Haris Akmal Abdullah Albar, Muhammad Andi Agung Hariawan Patempoi Andi Haerani, Muhammad Carda P, Aswin Aswin Eka Ariaty Arfah, Eka Ariaty Haerani, Andi Halim, Hasyim Haslinda Haslinda, Haslinda Herlina Herlina Mardiana, Sri Murniati, Sitti Nuraini Nuraini Nurmilawati, Nurmilawati P, Muhammad Carda Patu, Masriadi Ramli, H. Mansyur Rina Rina Roslina Alam Sinring, H. Bahar Sumarni S, Sumarni Surianto, Rahmat Yassir Yassir