One of the biggest obstacles to building AI data centers involves people. While AI is often feared as a replacement for workers, the technology requires significant human effort to deploy. The problem is that people with the right skills aren’t always readily available due to significant shortages of electricians, plumbers, HVAC technicians, and construction workers needed to physically build these data centers in local markets.
Data center operators and hyperscalers are under intense pressure to add AI capacity, and the shortages create a twofold issue: Construction labor shortages slow down building. And once the facilities are built, it’s hard to find skilled people to assemble the complex infrastructure for AI – especially at the unprecedented scale required. Data centers need skills not just to run IT and infrastructure but also to plan, design, manufacture, and ultimately assemble and maintain the intricate plumbing of liquid-cooling systems for AI chipsets and GPUs.
Shortages in the trades
One of the biggest skills-related issues hindering data center projects involves trade worker shortages. According to the U.S. Census Bureau, the construction sector is currently short about 500,000 workers, a number likely to continue rising.
Meanwhile, the U.S. Bureau of Labor Statistics estimates that 81,000 electricians will be needed yearly through 2034. During the same period, the Bureau predicts 44,000 openings yearly for plumbers, pipefitters, and steamfitters, and 42,500 for HVAC technicians. As people reach retirement age in these occupations, there are not enough workers to replace them.
So how can data center operators and hyperscalers get around these skills shortages? The answer is to minimize on-site work. That means relying on prefabricated, modular data center units that arrive on site ready to be fitted into the infrastructure like pieces of a puzzle. One type of unit built specifically for AI data centers are called AI pods. Designed to meet high-density computing requirements, AI pods are shipped complete with power infrastructure, and liquid cooling solutions and prepare the space for AI-ready racks.
AI pods support AI growth
Prefabricated modular units reduce on-site installation time from months to days and scale easily as AI deployments grow. They can be installed as new data center sections become available, allowing operators to add capacity quickly. Because they are assembled and integrated at the factory, prefab modules require minimal on-site staff for installation.
As such, AI deployments and expansion become less dependent on workers at data centers and enable faster deployment. This is important because AI demand is soaring. Gartner estimates AI spending will exceed $2.5 trillion during 2026, a 44% year-to-year increase. And according to McKinsey, “companies across the compute power value chain will need to invest $5.2 trillion into data centers by 2030 to meet worldwide demand for AI alone.”
The scale of investment in AI is unprecedented, triggering a rush to build new data centers. In some places, the availability of tradespeople with experience in complex data center projects is scarce or nonexistent. Training people on this work slows down installation. So access to prefabricated modular data centers is especially valuable.
Prefabrication allows data centers not only to mitigate many skills shortage-related issues but also to benefit from standardization. Every modular unit that leaves the factory is built to customer specs and replicated for easy deployment, reducing the possibility of on-site installation issues. Standardization reduces risk and increases quality.
A global partner built for AI infrastructure at scale
For data center operators and hyperscalers, working with a partner like Schneider Electric is key to accelerating deployments and overcoming skills shortages. No matter where you are in the world, Schneider has the capacity and expertise to build and deliver prefabricated modules to accelerate your AI expansion and time-to-revenue. Discover how our prefabricated modular AI pod solutions help you scale faster, reduce deployment time, and overcome skilled labor shortages.
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