AI Integration in Indonesian Education: Trends, Outcomes, and Challenges - A Comprehensive Review

Background Global education trends show the rapid growth of Artificial Intelligence (AI) as one of the leading technologies worldwide, a shift increasingly reflected in Indonesian education. This study aims to provide a Systematic Literature Review (SLR) by mapping the research landscape, its representation in practice and policy, its impact on learning quality, and the barriers to AI integration in Indonesian education. Method Using the PRISMA protocol, 34 peer-reviewed articles indexed in the Scopus and Google Schoolar databases (2020–2026) were systematically selected and thematically analyzed across four main themes. Results The findings indicate a rapid increase in publication productivity, particularly following the worldwide expansion of generative AI technologies after 2022. However, this growth remains unevenly distributed, concentrated in higher education institutions and urban centers on the island of Java, with a marked absence in primary and secondary education levels and in regions outside Java. The majority of AI-driven implementations consist of generative chatbots, adaptive learning platforms, and intelligent tutoring systems, alongside emerging applications such as learning analytics and AI-powered instructional media. Several studies included in this review reported that AI has contributed to measurable improvements in student outcomes including learning achievement, motivation, engagement, and teaching efficiency with studies reporting relative performance gains of 20–35% in well-implemented AI environments. Nonetheless, its adoption also poses significant risks, including a decline in students’ critical thinking skills, threats to academic integrity, and the absence of comprehensive data privacy policies and ethical standards governing AI use in education. Conclusion These findings underscore the urgent need for a responsible AI implementation framework in Indonesia one that incorporates standardized AI literacy competencies for teachers, locally contextualized ethical policies, and a functional national roadmap for AI-enabled educational transformation.