Introduction:
Water management in agriculture is a critical factor in national development. Although the Earth's water reserves are sufficient, uneven distribution—worsened by climate change and conflicts—limits agricultural productivity in many underdeveloped countries. Ensuring equitable access and sovereign rights to water is both a developmental priority and a matter of sovereignty. In today’s AI-driven era, agricultural water management is a key driver of economic development and sustainability.

Methods:
This study will use customized AI models trained on historical and recent data from water resource authorities and surveys. Economic models linking water management to financial stability will be integrated into these algorithms. Extensive surveys and field interviews will collect data on local water challenges and community practices. This mixed-method approach aims to develop adaptable, sustainable water management solutions for underdeveloped regions.

Expected Results:
Implementation of the proposed system is expected to reduce water wastage by up to 40% and increase crop yields by 25–35%. Improved water governance will enhance the economic conditions of farming communities, stabilizing livelihoods and enabling better household investment in education. These social improvements may lead to healthier populations and more informed citizens, contributing to national GDP and GNI growth.

Conclusions:
This research demonstrates that intelligent design and participatory management of agricultural water can drive economic transformation in underdeveloped nations. Harnessing AI and civil engineering innovations can accelerate sustainable development, making agricultural water management a cornerstone of future economic progress.