Wardiansyah Wardiansyah
Universitas Insan Pembangunan Indonesia

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SYSTEMATIC REVIEW OF ARTIFICIAL INTELLIGENCE IMPLEMENTATION FOR CONTINUOUS LEARNING: BENEFITS, IMPACTS, AND CHALLENGES Winanti Winanti; Yoga Prihastomo; Yulius Denny Prabowo; Achmad Sidik; Penny Hendriyati; Muhamad Luthfian; Rizky Setiawan; Wardiansyah Wardiansyah; Zaki Ma'rufan Chandra
JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) Vol. 11 No. 3 (2026): JITK Issue February 2026
Publisher : LPPM Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33480/jitk.v11i3.7583

Abstract

Artificial Intelligence (AI) is believed to be a crucial driver and force for realizing sustainable learning, so there is an urgent need to consolidate existing research to provide a clear and structured understanding of its tangible benefits, broader impacts, and ongoing challenges. This systematic literature review (SLR) aims to fill this gap by offering a concise overview of the role of AI in supporting sustainable learning in terms of benefits, impacts, and challenges in the era of society. Through a periodic review (SLR) of studies published between 2023 to 2025, this paper summarizes evidence on how AI enhances student learning engagement. This synthesis outlines the challenges, impacts, and pitfalls of using AI. The findings reveal that AI-driven tools—including intelligent tutoring systems, chatbots, emotion recognition systems, and adaptive learning platforms—significantly enhance personalized learning experiences and student motivation. This review synthesizes the technological landscape, outlining its benefits, impacts, and persistent challenges. Despite its potential, ethical, technical, and pedagogical hurdles remain. Consequently, this study lays the groundwork for future research and development in AI-based continuous learning. This study has several limitations. The literature review does not cover the specific designs and methodologies for measuring student engagement with AI. It also focuses on explicit outcomes like engagement and motivation, potentially overlooking unintended consequences or long-term impacts of AI integration. Furthermore, the analysis is constrained by the varying methodological quality and reporting transparency of the primary studies included.