Emerging Technology Confronts Traditional Techniques
A quiet, virtually unseen revolution is unfolding across America’s construction sites as contractors increasingly deploy autonomous machines to deliver services. In part, this is being done to embrace the future, but the real reason is to survive the present.
For instance, in Texas, a major interstate expansion facing sudden crew reductions turned to autonomous graders and compactors. That pivot mirrored one implement by Atlas Energy Solutions, which has been using self-driving sand-hauler trucks in the state’s Permian Basin. In both of these instances, the purpose was not to test technology. It was to respond to the crisis of workforce shortages that threatened project timelines and the fulfillment of contractual obligations.
Even before recent shifts in immigration policy, the U.S. construction industry needed 439,000 additional workers to meet demand according to a labor demand model maintained by Associated Builders and Contractors. The construction unemployment rate hit a record low of 3.2% in August 2024, the lowest in 25 years of data tracking. Associated General Contractors’ 2024 workforce survey found that 94% of construction firms report difficulty finding workers to hire, with 85% having open positions they cannot fill.
Presently, much emerging equipment renders existing workers more efficient rather than simply replacing them. According to Trimble research, experienced operators run 41% faster with 75% more accuracy when using automated assistance systems. New operators are 28% faster with accuracy rates doubling when such systems are utilized.
At the heart of the move toward autonomous equipment is a global shortage of heavy equipment operators at most construction companies. That shortfall limits demand for equipment that requires operators, which in turn limits manufacturers’ sales. To address that, more manufacturers are ramping up investment in machinery that can produce and deliver autonomous units.
In many instances, such equipment has been in operation for years. For example, Komatsu’s FrontRunner Autonomous Haulage System has moved more than three billion metric tons of material since 2008. According to a recent Autonomous Construction Equipment Global Market Report, other major players in the autonomous construction equipment market are Caterpillar, Hitachi Construction Machinery, Volvo Construction Equipment, Built Robotics, Cyngn, Royal Truck & Equipment, Case Construction Equipment, and Deere and Company among others.
The global market for autonomous construction equipment is forecast to expand from $15.3 billion in 2024 to $16.7 billion in 2025, translating into an annual growth rate exceeding 9%. Much of this growth is attributed to emerging markets, increasing infrastructure build-out, a desire for safer construction jobsites, and a general rise in global industrialization. By 2029, this market is expected to expand to $24.5 billion with a compound annual growth rate exceeding 10%.
Highway construction faces the most acute shortages, particularly among skilled heavy equipment operators. Fifty-four percent of contractors report project delays specifically due to workforce shortages, more than supply chain disruptions or material costs. With Infrastructure Investment and Jobs Act deadlines looming and state Department of Transportation contracts carrying steep delay penalties, the industry confronts a dilemma: how to complete massive projects with shrinking crews. Shifting immigration policies do not help along this dimension, with immigration raids routinely transpiring at construction jobsites (e.g., Tallahassee) or at Home Depot parking lots across the nation.
Technology to the Rescue
As labor shortages intensify, construction companies are rapidly deploying autonomous and AI-powered solutions that were experimental just a few years ago. Results are dramatic. For instance, Caterpillar’s MineStar Command for hauling system has enabled hundreds of autonomous trucks to move more than 8.6 billion tons of material across dozens of sites, demonstrating just how far the technology has progressed over a short period. These advances are now migrating from mining to highway construction, where autonomous bulldozers and graders reduce operator requirements by 30 to 40%.
No article regarding emerging technology can ignore AI, and this article is no different. AI project management systems are revolutionizing how contractors schedule and optimize resources. Think Power Solutions reports that AI-driven dynamic scheduling can generate hundreds of viable project timelines in hours, automatically adjusting for weather delays, material shortages, and crew availability. These systems use machine learning to predict potential delays before they occur, enabling real-time schedule adjustments that minimize downtime and keep projects on track despite workforce constraints.
Prefabricated Bridge Elements and Systems (PBES) represent another technological leap. The Federal Highway Administration’s accelerated bridge construction program demonstrates how components built off-site dramatically reduce field assembly time and labor requirements. Bridge decks, concrete barriers, and drainage systems manufactured in controlled factory environments arrive job-ready, requiring minimal on-site crews for installation.
Digital monitoring systems are replacing traditional inspection teams with unprecedented efficiency. Drones now conduct bridge inspections 75% faster than manual crews at just 5% of the cost, according to data from the American Association of State Highway and Transportation Officials (AASHTO). Meanwhile, Internet of Things (IoT) sensors embedded in pavement continuously track compaction quality and material performance, providing real-time feedback that was impossible with human monitoring operating in isolation.
A Virginia highway project illustrates the magnitude of these gains and practical implications. Despite losing 25% of its crew mid-construction, the project finished on schedule by deploying autonomous grading equipment and AI-optimized scheduling systems, demonstrating how technology can directly compensate for workforce shortfalls, even unpredictable ones.
Of course, what represents progress to some translates into threat to others. Chris Treml, Director of Construction Training at the International Union of Operating Engineers (IUOE), addresses this complexity. While acknowledging that “the last thing I want to see is people losing their jobs,” Treml recognizes that autonomous equipment “is going to be part of our industry, and so we want to be a part of it.”
Worker displacement concerns are valid. Research from the Midwest Economic Policy Institute projects that 2.7 million construction workers could face displacement by 2057, with displaced workers historically experiencing wage drops averaging 32% when transitioning to other industries. The impact varies dramatically by occupation. For instance, roughly 90% of operating engineers, cement masons, and painters could face displacement while other trades are associated with greater resilience.
Key components of the U.S. construction industry are already responding to emerging realities. The IUOE’s partnership with Built Robotics exemplifies new training partnerships, one in which union members learn to work alongside autonomous excavators rather than operating them. Workers are evolving from direct operators to “machine supervisors,” with Built Robotics CEO Noah Ready-Campbell explaining that “computers are not smart enough” to replace human judgment entirely, but “can free up operators to do the more challenging and valuable work.”
Looking Ahead
Consider this science non-fiction: the confluence of AI and robotics stands to transform construction delivery during the years and decades ahead. Even amidst today’s skilled construction worker shortages, it is straightforward to contemplate a future in which such shortages no longer exist. One can imagine a set of autonomous heavy equipment linked together by neural networks collaborating to repave highways, expand mines, or widen lanes as a remotely situated human passively monitors activity.
What’s more, because of the nature of the work, autonomous equipment is far more likely to be impactful in heavy highway settings than in other construction segments. For contractors, this creates a massive conundrum. Autonomous equipment is expensive. For instance, large haul trucks like the Komatsu 930E or 980E can cost between $5-8 million. Does one invest in such technology now or wait for further improvement along the dimensions of capability and cost? Does one wait for competitors to transition to autonomous equipment and then follow suit, or does one lead the way? Such decisions have major implications for future profitability, enterprise reputation, and market share.