September 3, 2026
by Arnie Gess, President of Construction Links Network
Note: This practical guide is part of our ongoing Construction Technology Insights series, where Construction Links Network explores the technologies transforming the built environment and helps construction professionals understand the industry’s digital future.
For a deeper strategic look at this technology, read Digital Twins in Construction: Transforming Project Planning and Operations.
Readers interested in the broader digital transformation of construction can also explore our Construction Technology Insights collection.
Estimated reading time: 8 min read
As construction becomes increasingly data-driven, one technology is creating new possibilities for how buildings and infrastructure are planned, constructed, operated, and maintained: the digital twin.
But what is a digital twin in construction?
A digital twin is a dynamic digital representation of a physical asset, system, or process that uses data to reflect conditions and performance in the real world. Unlike a static 3D model, a digital twin can evolve as information about the physical asset changes.
In construction and the built environment, digital twins can represent anything from an individual building or piece of equipment to infrastructure networks, construction processes, and entire communities.
Sensors, Internet of Things (IoT) devices, Building Information Modeling (BIM), artificial intelligence, cloud platforms, and other data sources can contribute information to the digital twin, allowing project teams and asset owners to better understand what is happening—and potentially what could happen next.
A digital twin connects a physical asset with a digital environment.
At a basic level, the process involves several components:
1. Physical asset
A building, bridge, road, piece of equipment, construction site, or other real-world asset.
2. Digital representation
A virtual representation containing relevant information about the physical asset.
3. Data connection
Sensors, IoT devices, project platforms, building systems and other sources provide information about real-world conditions.
4. Analysis
Software, analytics and increasingly artificial intelligence can analyze the information.
5. Decision-making
Project teams, owners and facility managers use those insights to monitor performance, identify problems, simulate scenarios and make better-informed decisions.
The important distinction is the connection between the physical and digital environments. buildingSMART notes that digital twins can regularly exchange data with their physical counterparts, with technologies including AI, machine learning, sensors and IoT supporting dynamic data gathering.
This is one of the most important—and most commonly misunderstood—questions surrounding digital twins.
BIM and digital twins are related, but they are not the same thing.
Building Information Modeling provides structured digital information about the design, construction and characteristics of an asset. BIM is particularly valuable for design coordination, visualization, clash detection and information management.
A digital twin can build upon that information by connecting the digital representation to changing data from the physical asset.
Put simply:
BIM helps describe and manage information about an asset.
A digital twin can use connected data to reflect and analyze how that asset is actually performing.
Digital twins therefore have the potential to extend the value of digital information beyond design and construction and further into operations and asset management. buildingSMART has similarly described digital twins as an opportunity to extend BIM processes with operational and real-time information.
If you’re new to BIM, our practical guide What Is BIM in Construction? explains how Building Information Modeling creates and manages digital project information throughout the construction lifecycle.
Although digital twins are often associated with completed buildings and asset operations, they can also provide value during project delivery.
Project information can be compared with real-world site conditions to help teams understand whether construction is progressing as planned.
Reality-capture technologies such as drones, laser scanners and site cameras can also contribute information about current conditions.
Digital environments can bring information from multiple project disciplines together, improving visibility and helping teams identify potential coordination issues.
Digital twins can help teams understand relationships between project schedules and actual site conditions.
Connected data can provide additional visibility into site conditions, equipment activity and environmental factors.
IoT-connected equipment and sensors can feed operational information into digital environments, helping teams monitor location, utilization and performance.
Digital twins become significantly more powerful when combined with connected jobsite technologies.
Sensors can collect information about:
That information can then be associated with a digital representation of the project.
This connection between physical assets and real-time information is an important part of the evolution toward smart construction sites, where connected technologies provide greater visibility into jobsite operations.
One of the most compelling aspects of digital twin technology is that its usefulness does not necessarily end when construction is completed.
Teams can explore alternatives and simulate potential outcomes before physical work begins.
Digital information can help monitor progress, coordination, logistics and project conditions.
Asset information collected throughout construction can support the transition from project delivery to operations.
Owners can use connected information to understand asset condition and performance.
Historical and real-time data may help organizations identify patterns and anticipate maintenance requirements before failures occur.
A well-maintained digital representation can provide future project teams with valuable information about existing conditions.
This lifecycle dimension is particularly important. NIST identifies forecasting as a foundational capability across digital-twin functions including simulation, monitoring, optimization and decision support.
Potential benefits include:
The precise value depends on the quality of the underlying data and, importantly, whether the digital twin has been designed around a clear business objective.
A sophisticated visualization without useful data or a defined purpose is not necessarily a useful digital twin.
Artificial intelligence can substantially increase the value of digital twins.
A digital twin can provide organized information about an asset while AI can analyze large volumes of that information to identify patterns, anomalies and potential outcomes.
For example, AI could help analyze:
As these capabilities mature, AI in construction project management will increasingly complement digital twins by helping project teams turn complex datasets into actionable insights.
Digital twins should not be viewed as isolated technologies.
Their greatest potential comes from connecting multiple digital systems.
BIM can provide structured asset information.
IoT sensors can provide operational data.
AI can analyze information.
Cloud platforms can enable collaboration.
Robotics and automated equipment can interact with digital workflows.
Together, these technologies contribute to an increasingly integrated construction ecosystem.
This convergence is central to the future of connected construction, where people, equipment, assets and digital platforms increasingly exchange information across the project lifecycle.
Digital twins offer significant potential, but successful implementation isn’t simply a matter of purchasing software.
Organizations must consider:
Interoperability is particularly important because construction projects typically involve multiple organizations and technology platforms.
A digital twin becomes far less valuable when critical information remains trapped in disconnected systems.
Open standards can help information move between the different platforms and stakeholders involved throughout an asset’s lifecycle.
This is particularly relevant as BIM, geographic information systems (GIS), IoT platforms and asset-management systems increasingly converge.
Organizations including buildingSMART International are working to advance open standards for digital twins and improve interoperability across the built-asset ecosystem.
As buildings and infrastructure become more connected, cybersecurity becomes increasingly important.
Digital twins can combine information from sensors, operational systems, cloud platforms and other connected technologies. Organizations therefore need to consider how that information is protected, accessed and governed.
Organizations developing digital-twin strategies should also consider security and trust for digital twin technology as part of their broader approach to data governance and cybersecurity.
Digital twin technology is likely to become increasingly important as construction organizations generate greater volumes of connected data.
Future digital twins may combine:
Rather than looking at these technologies individually, the industry is gradually moving toward connected digital ecosystems capable of supporting decision-making throughout the entire asset lifecycle.
For contractors, owners, engineers and facility managers, the opportunity is not simply to create digital representations of physical assets.
It is to create useful, trusted and continuously evolving information environments that support better decisions.
A digital twin in construction is a dynamic digital representation of a physical asset, system or process that uses data to reflect real-world conditions and support monitoring, analysis and decision-making.
No. BIM and digital twins are closely related, but they serve different purposes. BIM focuses on creating and managing structured information about an asset, while digital twins can connect digital representations with changing real-world data.
Not every implementation uses the same technology stack, but sensors and IoT devices are common sources of real-world information used by dynamic digital twins.
Applications include project monitoring, coordination, equipment tracking, scenario simulation, asset management, predictive maintenance and building operations.
Yes. Long-term operations and asset management are among the most important potential applications of digital twin technology.
AI can analyze information associated with a digital twin to identify patterns, detect anomalies, forecast potential outcomes and support better decisions.
