Integrating Deep Learning and Artificial Intelligence in the National Learning Ecosystem - Santyasa, I Wayan; Ghazali, Ihwan; Amiri, Mohammad Soleimani (Buletin Edukasi Indonesia, 2025)
The integration of Artificial Intelligence (AI) and Deep Learning (DL) in education has gained significant global attention as countries adapt to the demands of Industry 4.0 and Society 5.0. In Indonesia, where the education system serves over 60 million students, the potential of these technologies is both promising and underutilized. A fundamental challenge lies in the dual interpretation of the term “deep learning”: globally, it is defined as an AI technique using neural networks, whereas in Indonesian educational policy, it refers to pedagogical strategies fostering higher-order thinking skills. This semantic dissonance risks miscommunication and fragmented implementation. Through a combined literature review and policy-oriented analysis, this paper critically examines Indonesia’s current position in adopting AI and DL within its education system. The study highlights conceptual inconsistencies, infrastructural limitations, and equity concerns, especially in underserved regions. It calls for a standardized terminology framework, investment in inclusive AI infrastructure, teacher training on ethical AI use, and the development of a national AI-in-education roadmap. By addressing these issues, Indonesia can align its educational transformation with global standards while preserving its local pedagogical values.