Emerging technologies in construction help manage work, risk
Emerging technologies in construction include AI and digital twins. Read how companies use advanced IT to improve risk analysis, forecasting, and more.
Construction companies haven't been known historically as emerging technology enthusiasts -- but some are embracing it now.
Financial and cultural issues have contributed to the slow uptake of IT in construction. According to a 2023 McKinsey & Company report, low margins and "limited capacity for investment" long hindered builders' spending on digitalization. A workforce accustomed to paper blueprints and other time-tested construction practices also constrained tech adoption.
However, the industry's demand for IT has increased over the years and is likely to intensify as builders deal with complex projects, resource constraints and recent developments such as the Trump administration's tariff policy. That includes a universal 10% tariff on imported goods, tariffs on steel and aluminum imports and the potential for future tariffs on lumber. Other countries have responded by instituting retaliatory tariffs.
"For construction contractors, such policies could lead to stockpiling of materials, reconsideration of contracts, and pricing and scheduling uncertainty," according to an online tariff resource center posted by the Associated General Contractors of America trade organization.
Against that backdrop, some construction companies now pursue a mix of emerging technologies, including AI, digital twins and robotics. Industry executives view tech adoption as critical for keeping construction projects on schedule and within budgets.
"Construction is beginning to get up to speed," said Ignacio Gastón, CEO of Ferrovial Construction, a subsidiary of global infrastructure company Ferrovial based in Madrid, Spain. Ferrovial's current U.S. construction projects include roles on New Terminal One at John F. Kennedy Airport in New York and highway projects in metro areas of Washington, D.C., and Dallas/Ft. Worth.
"We need certainty in delivery and cost," Gastón said. "That can be managed better with the use of technology."
Adopting AI for risk analysis, forecasting
While harnessing digital assets hasn't been a top industry priority, the potential for doing so is there. Construction projects generate immense amounts of data, Gastón noted. That's data Ferrovial and other construction companies now aim to exploit.
We need certainty in delivery and cost. That can be managed better with the use of technology.
Ignacio GastónCEO, Ferrovial Construction
For example, they're using AI to analyze contracts and identify key terms and patterns that could signal potential risk, Gastón said. This risk analysis use case can identify cost escalations or factors affecting project schedules.
In addition, predictive AI applications such as price forecasting are "especially critical in today's volatile market," he added.
DPR Construction, a general contractor and construction manager based in Redwood City, Calif., also uses AI. The company's construction work includes advanced manufacturing facilities, hospitals, life sciences laboratories and data centers. Clients include Applied Materials, GlaxoSmithKline and Meta.
CTO Atul Khanzode said DPR analyzes data from past projects, using its internally developed machine learning (ML) tool, to predict the resources an upcoming engagement requires.
"We have data on how many people we needed to complete a particular type of project, like a hospital or a data center," he said. "If there's a new project of a certain size that comes up, what would be the predicted resources needed for that project?"
The ML tool is designed to answer that question and also predict when resources will be required on a project. Forecasting capabilities are essential in an industry where skilled workers have been in short supply, Khanzode noted. He cited fewer people entering construction trades and immigration challenges as contributing to a tight labor market.
Khanzode said those labor factors could open more opportunities for industrialized construction, prefabrication or modular construction -- and spark additional AI use cases. Those methods involve manufacturing buildings in a factory and shipping them to the construction site for assembly, reducing the need for on-location labor. Here, AI can augment design automation tools, enabling construction companies to explore design options for prefabricating components.
AI can also be used to program construction robots that DPR uses to draw building layouts on the construction site, Khanzode said. Traditionally, builders manually measured and marked a structure's layout when transferring a design from blueprint to concrete slab.
AI use cases in construction include risk analysis and predictive maintenance.
Using digital twins for operations and maintenance
Some current technology rollouts build upon earlier phases of construction tech adoption, such as building information modeling (BIM). BIM, which emerged in the 2000s, creates digital representations of structures to assist with planning, design and construction.
Layout robots, for example, can use a BIM model to print a design on a construction site. Digital twins, virtual representations of physical structures, can also take advantage of BIM. A BIM model, traditionally used in a project's design and construction phases, can serve as the foundation for a digital twin, Gastón noted. Real-time data can be incorporated into the model to create the digital twin, linking the underlying model with the physical entity the model represents.
This approach lets the BIM model play a role in the operations and maintenance phase of a project's lifecycle. In that capacity, engineers can use a digital twin to explore how assets such as a bridge or a highway will perform in the future. Concrete, for example, can be poured and tested, with the resulting information uploaded to the digital twin.
Such asset behavior data helps Ferrovial, which both builds and manages infrastructure, identify the maintenance actions needed to keep an asset operating at optimal performance, Gastón said. "We are able to plan proactive maintenance strategies with much greater confidence."
DPR created a digital twin platform a few years ago, which it has spun out as a separate company called VueOps. Khanzode said customers use the platform for facility operations and maintenance.
VueOps' digital twins are built on top of BIM models, he noted. The VueOps platform incorporates data on systems within an asset -- air handling equipment, for example. The model, combined with historical maintenance data and maintenance manuals for constituent systems, helps building managers troubleshoot issues, according to VueOps.
Growing tech teams in construction
Amid increasing technology use, construction sites and project teams look much different than they did a decade ago.
"Now you have entire departments on a big project that focus on technology," Gastón said. "We will see more of that."
Khanzode has also witnessed the tech shift in construction. Twenty years ago, he was the first BIM engineer at DPR. Today, he estimates that the company has more than 300 BIM engineers and perhaps double that number of employees in different roles, such as project engineers, who can operate BIM systems.
BIM and virtual design tools have become technological mainstays, Khanzode said. "It is pretty much expected that if you are playing any kind of operational role on a project, you should be familiar with those technologies and be able to interact with them."
But the construction sector needs an influx of digitally knowledgeable workers, Gastón said. Ferrovial uses on-campus recruiting, startup partnerships and employee development to cultivate such workers, and Gastón hopes the growing role of AI and digital tools in the company's work will help draw younger professionals.
"As an industry, we need to attract more technically oriented talent," he said.
John Moore is a writer for Informa TechTarget covering the CIO role, economic trends and the IT services industry.
