Transboundary water conflicts are multifaceted issues characterized by competition over finite resources, environmental considerations, historical complexities, and global repercussions. The imperative of effective management of shared water resources cannot be overstated. Such management not only addresses water scarcity but also promotes cooperation, sustains development, and provides conflict resolution mechanisms, contributing to regional stability, international relations, and overall well-being. AI and ML technologies offer transformative capabilities in this context. They enable predictive modeling, efficient resource allocation, data-driven decision support, and diplomacy among nations. AI and ML play a critical role in achieving sustainable and equitable water resource management by providing early warnings, optimizing resource allocation, and mitigating potential sources of conflict. Furthermore, they foster transparency, data-informed decision-making, and impartiality, fostering trust among stakeholders and enhancing collaboration. This chapter delves into the utilization of Artificial Intelligence (AI) and Machine Learning (ML) techniques in the domain of water resource management, particularly concerning transboundary conflict resolution. It explores the algorithmic and data-driven approaches that underpin the application of AI and ML, resulting in more sustainable and equitable practices for managing water resources. Through illustrative case studies, it showcases the potential of these technologies to predict water scarcity, optimize resource allocation, and foster collaboration among neighboring nations. It underscores the urgency of harnessing AI and ML in resolving the intricate challenges of transboundary water management. By leveraging these technologies, the global community can progress toward a more water-secure and peaceful world where shared water resources become instruments of cooperation and peace, rather than sources of contention and conflict.