In recent decades, technological advancements in areas such as the Internet of Things (IoT) and artificial intelligence have facilitated the digitalization of various resources, systems, and processes across various industrial sectors. Progress in virtual modeling and data acquisition technology has contributed to the emergence and development of the Digital Twin, a virtual representation of a physical asset that utilizes technologies such as sensors, IoT, communication networks, and 3D models to collect real-time data useful for monitoring its performance throughout its lifecycle. This work aims to emphasize the importance of applying Digital Twin technology in the construction sector, which helps understand the evolutionary behaviors and performance of a structure over time and space. It considers how the elements (materials, systems, etc.) composing the structure degrade based on various environmental conditions and user occupancy patterns. Simultaneously, through analysis and monitoring of physical assets using the digital twin, it becomes possible to determine the optimal time to intervene and replace worn-out components or systems, thus ensuring the continuous functionality of the structure to maintain performance at optimal levels. In the coming years, technology will enable the integration of artificial intelligence into the construction sector. This will allow the analysis of performance, both pre- and post-construction, to anticipate evolving needs with a high degree of probability. This will be facilitated by the collection of statistical data and the comparison of performance behaviors from buildings that are typologically and morphologically similar.