Challenges and Opportunities for Implementing Artificial Intelligence in Education in Indonesia

Lucas Lima; Tiago Costa; Thabo Mokoena; Mpho Nkosi

Authors

Lucas Lima Universidade São Paulo Author
Tiago Costa Universidade Federal Rio Janeiro Author
Thabo Mokoena University Cape Town Author
Mpho Nkosi University Pretoria Author

Keywords:

Artificial Intelligence, Digital Transformation, Education

Abstract

Artificial Intelligence (AI) is rapidly reshaping education systems worldwide by enabling adaptive learning, automated assessment, and personalized instruction. Indonesia—with its large and diverse student population, burgeoning edtech sector, and recent national AI and digital-skills initiatives—faces a unique set of opportunities and constraints when implementing AI in education. This paper synthesizes contemporary literature and Indonesian policy developments to identify infrastructural, pedagogical, ethical, and governance challenges, while also highlighting potential pathways for scaling evidence-based AI interventions that support equity and teacher capacity. Using a mixed-methods synthesis of policy documents, reports, and recent empirical literature (2020–2025), we propose an integrated framework for responsible, pedagogically-driven AI adoption in Indonesian schools and higher education. Practical recommendations are presented for policymakers, educators, and edtech developers to align AI deployment with curricular goals, digital inclusion, and data governance

References

Boncillo, J. J., & Reyes, M. (2025). AI in education: A systematic review of applications, benefits and ethical challenges. Journal of Educational Computing Research, 63(5), 1012–1038.

Bond, M. (2024). Review of reviews: The landscape of artificial intelligence in higher education research. International Journal of Educational Research Open, 5, 100123.

Bond, M., & Bedenlier, S. (2024). A meta-systematic review of artificial intelligence in higher education: Scope, themes and future directions. International Journal of Educational Technology in Higher Education, 21(1), 1–24.

Dinar, Y., & Hidayat, F. (2024). Local edtech ecosystems and AI innovation in Indonesia: University–industry partnerships. Journal of Technology Transfer in Education, 12(1), 23–41.

Garzón, J., & Acevedo, R. (2025). Systematic review of artificial intelligence in education: Applications, challenges, and future research directions. Multimodal Technologies and Interaction, 9(8), 84.

Haetami, H. (2025). AI-driven educational transformation in Indonesia: Opportunities, pilots and governance issues. Journal of Indonesian Educational Studies, 7(2), 112–133.

Kurniawan, B., & Hartono, A. (2022). Data protection compliance in Indonesian schools after PDP Law: Early observations and guidance. Computer Law & Security Review, 44, 105709.

Létourneau, A., Bouchard, K., & Tremblay, F. (2025). A systematic review of AI-driven intelligent tutoring systems and their effects on K–12 learning outcomes. Frontiers in Education, 10, Article 12078640.

Letourneau, A., & Nguyen, P. (2024). Intelligent tutoring systems for mathematics: A synthesis of randomized controlled trials. Educational Researcher, 53(4), 221–234.

Liao, Q., & Wang, H. (2022). Adaptive learning systems and student outcomes: Meta-analysis of experimental studies. British Journal of Educational Technology, 53(6), 1504–1523.

Lim, T., & Abdullah, N. (2023). Generative AI in education: Opportunities, risks, and classroom practices. Computers & Education Open, 4, 100089.

Mathew, A., & Suresh, K. (2022). Machine learning models for predicting student performance: Trends and challenges. Journal of Learning Analytics, 9(2), 1–19

Matos, T., & Silva, P. (2025). Applications of artificial intelligence in education: Effectiveness, ethical concerns, and implementation challenges — a systematic review. Computers & Education: Artificial Intelligence, 6, 100027.

Nurhayati, S., & Rahmawati, L. (2025). Parental readiness for AI-driven learning in Indonesian child education: Implications for policy and practice. Education and Information Technologies, 30(3), 3457–3476.

OECD. (2021). AI and the future of education: Policy perspectives and practical considerations. OECD Publishing.

Prasetyo, R., & Lestari, S. (2021). Equity implications of digital learning: The digital divide in Indonesian basic education. International Review of Education, 67(3), 363–384.

Purnama, M. R., & Santoso, D. (2025). Teacher readiness toward artificial intelligence in Indonesian classrooms: A mixed-methods study. Journal of Educational Technology & Society, 28(1), 55–70.

Santos, R., & Putri, A. (2023). Learning analytics in Indonesian schools: Current status and prospects for AI integration. Asia Pacific Journal of Education, 43(1), 89–105.

Sari, D. K., Putri, Y., & Prasetyo, H. (2025). Measuring artificial intelligence literacy among Indonesian higher education students: Development and validation of an AI literacy instrument. International Journal of Educational Research, 124, 102200.

Tech4Good Institute. (2023). Implementation challenges of data protection and AI in education: Lessons for Indonesian schools. Tech Policy Review, 2(3), 45–68.

UNESCO. (2021). Pedagogical and policy guidance on artificial intelligence in education (Policy Brief). UNESCO Publishing.

UNESCO. (2024). Recommendation on the Ethics of Artificial Intelligence. UNESCO.

U.S. Department of Education. (2023). Artificial Intelligence in Education: Challenges and Opportunities — Policy Brief. U.S. Department of Education.

Wang, S., Li, J., & Chen, Y. (2024). Artificial intelligence in education: Trends from a decade of research. Computers & Education, 180, 104558.

Zhu, H., & Park, S. (2025). Identifying and mitigating ethical risks in AI for education: A systematic review. Humanities and Social Sciences Communications, 12, Article 52.