With the rise of digital technologies in recent years, to maintain global competitiveness, organizations strive to reduce asset’s cost, improve its performance, and service quality during its Lifecycle. Digital twin as one of the key technologies of industry 4.0 revolves around the idea of replicating the characteristics and behaviors of real-world objects to provide accurate representations in virtual environments. The concept of digital twin has gained substantial attention in both academic and industrial circles in recent years due to its potential for improving various systems performances and contributing to Industry 4.0. Lifecycle. In the field of building assets management, there are still some challenges in the digital twin framework, such as difficulties in achieving real-time communication and closed-loop control. This paper investigates existing challenges and opportunities in the application of digital twin as an enabler for building asset management by critically reviewing the existing applications. The proposed framework offers architecture for orchestrating specific industry 4.0 technologies that are most applicable to asset management, such as hybrid modelling which combines both physics based and machine learning approaches, where the former one is used when the data about the asset is known while the alter one can be mostly used at the operation stage when the real-time data with sensing devices are sent to digital twin for analysis. This paper proposes a roadmap for building asset management based on the existing works and their limitations.