Artificial intelligence is beginning to redefine the U.S. construction industry — not just in how contractors run projects, but also in how future demand is forecast. A new report from Merlo America, developed with predictive intelligence firm BiltData.ai, projects where construction growth will concentrate by 2030. At the same time, industry advisors say contractors are already deploying AI in design, bidding, and jobsite operations, though challenges around data quality remain.
Together, the two perspectives suggest a future in which predictive AI identifies opportunities, while operational AI enables firms to capture them.
BiltData’s predictive modeling platform merged public data, industry outlooks, and geospatial analysis to project market demand from 2025 through 2030. Applying a 4% annual growth rate, the system distributed activity across metro areas based on demographics, economic performance, and past construction patterns.
By 2030, U.S. construction spending is expected to rise from $1.553 trillion in 2025 to $1.889 trillion, with residential remaining the largest segment at $755.8 billion, followed by commercial ($567.2 billion), industrial ($377.4 billion), and infrastructure ($188.5 billion).
Just five states — California, Texas, Florida, New York, and New Jersey — are forecast to account for 42% of spending. Thirty-five metropolitan regions will capture nearly two-thirds of all construction, with the New York–Newark–Jersey City area leading at $162.2 billion by 2030.
“New York’s construction spending alone could rival the economy of a small country,” the report notes.
A major driver of industrial growth will be the data center sector, fueled by cloud computing, artificial intelligence, and 5G. Washington, D.C. is projected to lead with 3,000MW of capacity by 2030, followed by Dallas–Fort Worth at 1,500MW.
“Data centres are emerging as a powerful driver of construction and industrial activity,” the report said. “These tech-heavy hubs are ripe for investment in equipment and skilled services.”
If the forecast points to where demand will rise, contractors must determine how to capture that growth. Brian Kassalen, principal at Baker Tilly, says AI adoption is already expanding across the construction lifecycle.
“We’re seeing significant investment across all stages of the construction lifecycle, but especially in design, bidding and on-site operations,” he said.
Design firms are using AI to iterate CAD layouts and test different structural scenarios. Procurement teams apply AI to analyze markets and select cost-effective vendors. On jobsites, drones, cameras, and robotics integrated with AI are streamlining monitoring and progress tracking.
“On the job site, AI is being combined with technologies like drones, cameras, and robotics to streamline progress tracking, identify deviations from plans and improve real-time decision-making,” Kassalen said.
The clearest value so far is in estimating and bidding:
“By analysing historical costs, market trends, and labour data, AI helps contractors generate more accurate bids and avoid underpricing, a common cause of project losses.”
Many contractors begin their AI journey with safety applications, Kassalen explained.
“One of the easiest areas for contractors to start experimenting with AI is safety,” he noted. “For example, firms can use drones to fly over a job site and apply algorithms or heat-sensing software to identify potential hazards. If someone asks me what a good first step might be, safety is probably at the top of the list.”
Despite AI’s potential, Kassalen cautioned that data quality is the largest barrier.
“AI is only as strong as the data it can access and learn from,” Kassalen said. “Without good data to feed into the models, even the best AI tools won’t provide useful insights. So, the biggest gap isn’t in the technology. It’s in how firms collect, manage and leverage their data.”
This divide is especially sharp between larger contractors, who are more likely to invest in AI pilots, and midsize firms that often prefer familiar methods. Within companies, IT leaders often push for wider adoption while finance departments weigh ROI carefully.
The Merlo/BiltData forecast envisions a $1.889 trillion industry by 2030, concentrated in a handful of states and metros, with data centers at the core of industrial expansion. Kassalen’s contractor view underscores that realizing this growth will depend not only on where demand rises, but also on which firms can use AI to improve bidding, safety, and project delivery.
In short, the next decade of U.S. construction may be defined as much by AI-driven execution as by the scale of projected demand.
Originally reported by Mitchell Keller in Construction Briefing.
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