Digital twins have revolutionized various industries by enabling predictive modeling and simulation to optimize structural integrity and performance. Originally, DTs were developed for manufacturing and aerospace applications. They now integrate real-time operational data with virtual representations to enhance decision-making. This paradigm has now expanded to the architecture, engineering, and construction (AEC) industry, particularly for the preservation and restoration of historical artifacts. Unlike conventional applications, where DTs support product design, in cultural heritage, their primary function is to document, analyze, and maintain historical assets through continuous intervention and monitoring. This article presents an interdisciplinary approach to DTs, emphasizing data integration, AI-driven analysis, and real-time monitoring for cultural heritage. The study classifies the digital twin’s functionalities into five key domains: 3D reconstruction, sensor data acquisition, simulation technologies, multimodal interaction, and AI-enhanced collaboration. Leveraging these domains, the research proposes a systematic methodology to transform passive heritage artifacts into cyber-physical systems, fostering enhanced data-driven conservation strategies.