As technology companies prepare to invest nearly $3 trillion in data center infrastructure by the end of the decade, a logistics industry veteran argues that artificial intelligence expansion will create, not eliminate, jobs for working-class Americans—reversing historical patterns where technological progress has threatened manual labor.
Kris Edney, director of Service Center Operations at Interstate Moving, Relocation, Logistics, Inc. in Springfield, Virginia, contends that the massive buildout of AI infrastructure will require hundreds of thousands of skilled tradespeople whose work cannot be automated. His argument challenges the prevailing narrative in technology circles that AI poses an existential threat to employment across sectors.
The Scale of Investment and Labor Demand
This year alone, Big Tech is projected to spend an estimated $650 billion on infrastructure expansion, including data center capacity to support artificial intelligence technology. The scale of this investment creates concrete labor demands: more than 300,000 new electricians will be needed in the next decade to bring these facilities online, alongside legions of plumbers, construction workers, and other skilled tradesmen.
Edney's employer, Interstate Moving, Relocation, Logistics, Inc., has operated for over 80 years and currently employs more than 70 licensed drivers. The company reports feeling the infrastructure boom directly through increased demand for transporting heavy equipment, including data servers, to hundreds of locations across the country.
Microsoft President Brad Smith has acknowledged the need for a new generation of skilled tradespeople to support technology infrastructure development. In January, Nvidia boss Jensen Huang predicted that people working to build technology facilities will soon be earning six-figure salaries, signaling confidence in both job availability and compensation in the sector.
Who Bears the Risk—and Opportunity
Edney emphasizes that the logistics and transportation sector is experiencing a demographic shift. Several of Interstate's 70-plus licensed drivers are under 25 and have completed the company's industry-leading training program. These young workers are entering the field directly from high school, seeking lifelong careers with good pay and benefits from day one.
The company is actively training 18-year-olds to manage high-intensity situations, such as hauling 40 tons at 70 miles per hour across state lines—a responsibility that requires both skill development and genuine workplace investment in worker preparation.
The Human Element in Automation
Edney argues that while machines may operate in controlled environments like highways, real-world logistics demands human judgment and experience. Navigating dense urban traffic with tight turns, preventing cargo theft, and managing fully loaded rigs in unpredictable conditions require decisions that computers cannot reliably make. The margin for error in these situations—potential accidents, property damage, or loss—remains too high for full automation.
Moreover, logistics extends beyond point-to-point transportation. In the data center boom, logistics teams function as part of the construction process itself. They procure specialized equipment from overseas, coordinate secure shipments, and ensure critical components arrive in the correct sequence. When deliveries slip, entire projects stall; cooling systems, power supplies, racks, or switchgear cannot be installed until the required hardware arrives. In many cases, drivers and logistics crews support the installation process directly, handling sensitive loads and maintaining project schedules.
A Reversal of Historical Patterns
Edney notes an ironic historical shift. During the Industrial Revolution, technological progress automated muscle power and harmed blue-collar employment. The current AI expansion follows a different trajectory: white-collar workers in office roles now face displacement, while blue-collar workers find demand for their skills rising.
Workers in the logistics and trades sectors, according to Edney, express optimism about their prospects. He characterizes the current moment as potentially the beginning of a golden age for the working class, with truckers positioned at its center.
Why This Matters:
The relationship between technological advancement and employment opportunity has historically been unequal: some workers and communities benefit while others face displacement without adequate support systems. This infrastructure investment presents a concrete case study in how technology spending can create or destroy working-class opportunity. The scale—$650 billion this year alone, nearly $3 trillion by decade's end—represents one of the largest capital investments in recent history. Whether these opportunities translate into stable, well-compensated employment for working-class Americans depends on factors beyond market forces: training accessibility, wage standards, workplace safety regulations, and whether companies invest in worker development as Edney's employer claims to do. The contrast between optimism in logistics and anxiety in white-collar sectors also raises questions about whose interests technology policy prioritizes and which workers receive institutional support during economic transitions.