Integrative Systematic Review on the Impact of AI-Based Training Programs on Motivation and Performance of Non-Academic Educational Staff


  • Husni Mubarrak Sekolah Tinggi Ilmu Manajemen Sukma, Medan, Indonesia
  • Vina Winda Sari * Mail Universitas Medan Area, Medan, Indonesia
  • Nurhayati Nurhayati Sekolah Tinggi Ilmu Manajemen Sukma, Medan, Indonesia
  • Wardayani Wardayani Sekolah Tinggi Ilmu Manajemen Sukma, Medan, Indonesia
  • Suginam Suginam Universitas Harapan Medan, Medan, Indonesia
  • Mesran Mesran Sekolah Tinggi Ilmu Manajemen Sukma, Medan, Indonesia
  • (*) Corresponding Author
Keywords: AI Training; Work Motivation; Non-Academic Staff; Digital Literacy; Higher Education

Abstract

This study aims to systematically review how artificial intelligence (AI)-based training affects the motivation and performance of non-academic educational staff in educational institutions. The review employed a Systematic Literature Review (SLR) approach, analyzing 20 selected articles from SCOPUS, Web of Science, and SINTA databases. Findings reveal that AI-based training contributes to improved work efficiency, employee engagement, and adaptive skills. However, its impact on work motivation is highly dependent on digital literacy, training design, and managerial support. The study also highlights a lack of integrative models that link AI training, motivation, and performance in a cohesive framework. The findings offer theoretical contributions to the development of digital HRM in education and practical insights for designing inclusive and adaptive AI-based training. This study’s limitations include the scarcity of longitudinal data, dominance of research from developed countries, and limited contextual insights from Southeast Asia. Future research is encouraged to apply empirical and longitudinal approaches to strengthen causal understanding and contextual applicability

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