Applications of Artificial Intelligence in Environmental Management in Vietnam: A Mini Review

Vietnam faced serious environmental challenges, including air pollution, waste management issues, natural disasters, climate change, and biodiversity loss. This paper provided a mini-review of artificial intelligence (AI) applications in the environmental sector in Vietnam, based on studies published between 2020 and 2025. AI was effectively applied in various domains, such as high-accuracy air quality forecasting using models such as LightGBM and CatBoost; optimization of solid waste management through Random Forest and integrated IoT systems; flood and landslide prediction using XGBoost and LSTM; climate change impact assessment based on stacked LSTM architectures; and natural resource monitoring employing convolutional neural networks combined with geographic information systems. These studies demonstrated that AI outperformed traditional methods in terms of accuracy and efficiency, thereby supporting data-driven decision-making. However, major challenges remained, including limitations in data availability, human resources, and technical infrastructure. The paper further proposed development directions such as establishing open databases, strengthening human capacity building, and promoting international collaboration to accelerate AI adoption in alignment with Vietnam’s National AI Strategy toward 2030. Overall, AI was expected to become a key enabling tool for sustainable environmental management in Vietnam.