The Importance of Artificial Intelligence in Enhancing Sustainable and Climate-Resilient Agriculture in Cambodia: A Narrative Review

AbstractCambodia’s agriculture—dominated by smallholder rice systems alongside rapidly growing horticulture—is increasingly challenged by climate variability, recurrent droughts, floods, and changing hydrological regimes in the Lower Mekong Basin. Evidence from ScienceDirect-indexed literature shows that artificial intelligence (AI)—including machine learning (ML), deep learning (DL), and geospatial AI (Geo-AI)—can strengthen climate resilience and sustainability by improving (1) crop monitoring and rice mapping from satellite data, (2) seasonal and in-season yield forecasting, (3) drought and flood risk early warning, (4) pest/disease surveillance and integrated pest management (IPM), (5) water and nutrient-use efficiency, and (6) supply-chain intelligence to reduce losses and stabilize markets. Cambodia-specific studies published in ScienceDirect demonstrate promising performance of satellite-derived planting dates for yield estimation in rainfed paddy fields and show measurable links between drought indices and rice productivity across Cambodia, while agronomy and social-science work highlights pesticide reliance, extension gaps, and adoption constraints that AI tools must address to be effective and equitable. This narrative review synthesizes ScienceDirect evidence across technical and socio-institutional dimensions, identifies enabling conditions (data infrastructure, ground-truthing networks, digital extension capacity, governance), and proposes a Cambodia-focused research and implementation agenda emphasizing locally validated Geo-AI services, farmer-centered advisory systems, and climate-risk decision support integrated with sustainable intensification strategies.