Water management in vulnerable territories faces structural challenges associated with deep information gaps, institutional weaknesses, and technological limitations that hinder evidence-based decision-making. On a global scale, organizations such as UNESCO and the World Bank have warned that the lack of reliable and timely hydrological data disproportionately affects rural and peri-urban communities and regions exposed to water stress and extreme weather events. In this context, artificial intelligence (AI) emerges as a set of tools with high potential to transform water management by analyzing large volumes of data, predicting future scenarios, and optimizing monitoring and distribution processes. This article analyzes, from a critical and up-to-date perspective, the information gaps that condition water management in vulnerable territories and examines the main contributions of AI to reduce these gaps. Based on a systematic review of recent scientific literature and institutional reports, concrete applications of AI in hydrological prediction, loss detection, water quality monitoring, and support for water governance are identified. The results show that, although AI offers significant improvements in efficiency and predictive capacity, its impact depends on the availability and quality of data, as well as inclusive institutional frameworks. It is concluded that the responsible integration of AI can contribute substantively to a more equitable and sustainable water management in vulnerable territories.