The European Commission, with the Renovation Wave Strategy for Europe, has set its objective of doubling redevelopment interventions on existing assets within ten years. [16]. Some general goals have already been affirmed, despite rarely being placed so explicitly close to each other, such as the following: the recovery of the existing heritage and, at the same time, a reduction in greenhouse gas emissions, achieving climate neutrality for Europe and the improved quality of life of the people living in and using the buildings.

In line with these objectives, operational principles and indicators have been established that are capable of measuring the smart readiness of existing buildings, i.e., their ability to be included in the digital reconversion process of existing buildings. The Smart Readiness Indicator (SRI) evaluates the ability of buildings to answer the needs of users, modifying and adapting their functioning, and ultimately improving their energy efficiency and performance during the in-use phase. For effective application, the SRI makes explicit reference to the potential gains connected to the use of the digital model and DT of buildings. It considers the goals of greater energy saving, comparative analysis, and flexibility, as well as the functionality and ability to improve performance, thanks to the widespread use of interconnected and intelligent devices. It includes the assessment of the intelligence readiness of a building or unit based on key functionalities, the impact criteria, and pre-defined technical areas, also including additional information on building inclusiveness and connectivity, interoperability, cybersecurity, and data protection [132,133].

DT is an intelligent knowledge management system seeking its own counterpoint in the application of information technologies (ICT), welcoming innovative approaches leading to new ways of using sharing data between operators, as well as between operators and end users. These are issues that, although appropriately studied and theorized, have so far been almost never actually implemented in operational practices. Likewise, from the perspective of overall quality assurance in the lifecycle, when associating the terms “costs”, “efficiency,” and “sustainability” with the design, the need to overcome the lack of sharing and updating of information emerges, as well as the difficulty in control, the lack of communication, and interoperability.

In such a context, the cognitive and informational dimension acquires more and more centrality by bringing all of the management actions of the built environment into a unitary and interconnected process, achieving positive effects in terms of planning management activities, timing the implementation of interventions, and the control of the performance of components and equipment.

These are all aspects that are equally shared and explained in the founding characteristics of Digital Twin approaches, whose basic principle is information, which becomes information capital when it can be acquired and exchanged between buildings, digital models, operators, and users. This fuels the possibility of the effective transformations of the processes, enhancing the ability to govern the information for the current ecological and digital transition.

The widespread application of DT highlights a general goal to enhance the processing capacity of advanced technologies that are already available (BIM and IoT) but not yet widely implemented together.

The use of both BIM and IoT is increasingly diffused in the construction industry, but not in combination with each other. Their combined use has not yet been sufficiently explored, although it could contribute to achieving sustainability. In particular, the potential of their combined use could be expected to be exploited for simulations, monitoring processes, and the application of virtual and augmented reality.

There is a growing awareness that the future for Building Construction will enhance smart aspects connected to the whole functionality of buildings, combining both information systems and sensors. DT, devices, and sensors installed for monitoring and Building Automation Control Systems (BACS) create smart buildings and make the potential upgrade to cognitive buildings achievable. Physical/digital (phygital) constructions, smart grid nodes, and smart cities are capable of communicating with other buildings, mobility systems, and users [108,109].

DT, for the in-use and O&M phases, still appears critical, nevertheless, it represents the operational area in which the most relevant conditions exist for DT’s punctual future implementation.

Various studies quantify the consequences of the global emissions of climate-altering gases, energy consumption, land consumption, and waste production directly attributable to the building stock in operation.

There is an awareness that, when related to the conservation and transformation of the built environment, can be traced back with ever greater evidence to the O&M phase and the need for responsible and sustainable predictive maintenance actions. A phase to which, today, with equally growing awareness, extra costs are attributed, which are no longer and not only of an economic nature, but also of an environmental and social nature. The latter derives from the quantity of energy necessary to heat, cool, power, and manage buildings. As is known, a large amount of energy consumption relates to the lifecycle of buildings. Therefore, sustainable energy management and control represent urgent priorities and criticalities; however, they are not yet sufficient for achieving sustainable construction.

The Chartered Institution of Building Services Engineers (CIBSE) researchers had already expressed concern about these data. In a 2012 study, they argued that buildings normally consume double what was estimated at the design stage. This is a statement that, although not recent, continues to be in line with the energy consumption data of the building stock [134].

Therefore, with reference to the macro-objective of the decarbonization of the construction sector, the emergence of a priority critical area constituted by the O&M phase is clearly stated, as highlighted by the findings explored in the present literature review.

The report of the World Green Building Council (WGBC) affirms that the construction sector is responsible for 39% of global emissions of climate-changing gases, of which approximately one third (equal to 11% overall) is attributable to the construction phase. The remaining two thirds (equal to 28% overall) concern the operation phase [135].

Similarly, in 2016, the European Commission report attributed as much as 40% of European energy consumption to the existing building stock [136].

These data have undergone exponential growth over the last decade, with a rate of increase second only to that of the transport sector.

Between 2017 and 2018, there was a 2% increase in the energy needs of buildings, with a total increase in 2019 of approximately 8 Exajoules, equal to +7% compared to 2010 [137]. Equally significant is the data offered by the United Nation Environment Program (UNEP), which provide a snapshot of the state of buildings on a global scale. The Global Status Report found that total energy consumption and CO₂ emissions increased in 2021, even when compared to the pre-pandemic levels. This notwithstanding, there has been a substantial growth in investments and a consequential global reduction in buildings’ energy consumption. The same report documents how the energy demand of buildings has increased by around 4% since 2020, reaching 135 Exajoules, which is the highest value in the last 10 years. Moreover, CO₂ emissions from building have reached an all-time high of around 10 GtCO₂, an increase of 5% compared to 2020, and 2% compared to the previous peak in 2019 [138,139].

It seems clear that applying the Digital Twin approach to the O&M phase, as well as to the decarbonization processes of the sector, is a challenging area.

DT configures as a potential holistic tool for introducing innovative methods and opportunities supporting maintenance actions and, principally, the widespread use of predictive maintenance strategies.

According to these potentialities, it is necessary to adequately accompany the ongoing shift from hard (techniques) to soft (in-training, organization) techniques of study focus and operational aspects relating to a renewed maintenance approach. As a result, heterogeneous fields of interest are involved that presuppose multidisciplinary approaches and require an ever-increasing ability to manage structured data relating both to performance and operating values and behavioral and experiential aspects concerning the well-being of end users.