Indonesia faces significant waste management challenges due to the high volume of unmanaged waste, inefficient sorting, and continued reliance on conventional disposal practices. This study aims to examine the role and implementation of Artificial Intelligence (AI) in waste sorting and management and its potential application in Indonesia. A Narrative Literature Review (NLR) was conducted by analyzing relevant studies obtained through Google Scholar using keywords related to AI, waste management, computer vision, and waste classification. The findings indicate that AI has been applied to automated waste identification, classification, real-time detection, monitoring, and robotic sorting. Applications of computer vision, deep learning, object detection, and robotic systems demonstrate potential to improve sorting accuracy, processing speed, operational efficiency, and recycling. Comparative evidence from Bangladesh, Vietnam, India, Russia, and the United Kingdom shows diverse approaches to AI-based waste management. For Indonesia, AI adoption should be adapted to local waste characteristics, infrastructure, datasets, and human resource capacity. A gradual integration of AI with digital infrastructure and automated systems can support more efficient and sustainable waste management.
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