Water resources management is one of the fundamental challenges in today's world, which has become increasingly complex due to climate change, population growth, and the expansion of industrial activities. Given the limited availability of freshwater resources (only 50 percent is available) and the intensification of water stress (720 million people live in critical areas), this research attempts to examine the dual role of artificial intelligence in water resources management and environmental sustainability, with an emphasis on arid and semi-arid regions such as West Asia; because artificial intelligence has become a useful tool in various fields, including environmental sciences. Therefore, artificial intelligence acts as a two-way technology. On the one hand, by providing smart solutions in water quality monitoring, drought prediction, irrigation optimization (30 percent reduction in agricultural water consumption), and leakage detection (prevention of 95 percent of urban waste), it plays a key role in achieving sustainable development goals such as clean water and climate action. On the other hand, the development of AI infrastructure, especially data centers, is exacerbating the resource crisis, consuming millions of liters of water for cooling annually and accounting for 1.5% of global electricity. Training large models such as Chat.