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In the pursuit of organizational goals, addressing the fundamental needs of employees, such as ensuring the availability of drinking water, plays a pivotal role in fostering a productive, healthy, and value-aligned work environment. This imperative necessitates the implementation of intelligent service management solutions that are both efficient and intelligent. In this research, we propose a visionary architectural transformation that seamlessly integrates intelligent agent-based smart systems within the domain of Smart Organizations. Our novel architectural approach draws inspiration from Activity Theory, strategically orchestrating interactions between employees, company objectives, and tools. Additionally, we employ a meticulously crafted 4-layer organizational system structure to delineate roles, establish rules, foster communities, and optimize task allocation. This forward- looking architecture is further fortified through the integration of cutting-edge technologies, encompassing the Internet of Things (IoT) with precision dispensing scales for real-time predictive capabilities, human-computer interaction (HCI) mobile applications and web services to enhance user-system engagement, and pervasive artificial intelligence (AI) implementations across every layer of the system. The architectural framework is consolidated within a robust Big Data platform, enabling the collection and comprehensive analysis of data on a grand scale. This multifaceted approach seeks to usher in profound and all-encompassing changes in the management of drinking water supply services, encompassing organizational paradigms, technological advancements, and methodological enhancements to enhance efficiency and effectiveness. The focus of this transformation is primarily directed toward companies involved in supply activities, with particular emphasis on drinking water provisioning. Through the development of predictive system prototypes and meticulous performance analysis, our study conclusively demonstrates that the Smart System-based prediction architecture significantly enhances operational performance and elevates the quality of drinking water supply services.