The race to build AI data centers is hitting a critical bottleneck: time. Traditional data centers take two to three years to construct, but companies racing to deploy artificial intelligence (AI) hardware are running out of patience. A new wave of modular data center companies is solving this problem by shipping fully built computing pods that can be deployed in roughly six months, fundamentally changing how the industry scales its infrastructure .

Why Are Data Centers Taking So Long to Build?

Constructing a traditional data center involves far more than just assembling servers. Engineers must identify suitable sites, navigate complex permitting processes, coordinate with construction contractors, and build steel-and-concrete shells to house expensive hardware. While the shell itself is relatively inexpensive compared to the equipment inside, the entire process creates delays that are becoming unacceptable in the AI era .

The problem has become acute. "I just came back from Nvidia's GTC, and a lot of [companies] are sitting on their deployment because their data centers aren't ready, or they can't find the space," said Doug Recker, CEO of Duos Edge AI. "We see the demand there, and we can deploy faster" .

How Do Modular Data Centers Work?

Modular data centers operate on a fundamentally different principle than traditional facilities. Instead of constructing buildings from scratch, companies like Duos Edge AI and LG CNS manufacture self-contained computing pods at factories, then transport them to sites where they can be deployed like puzzle pieces. The pods contain racks of graphics processing units (GPUs), the specialized chips essential for training and running AI models, along with supporting infrastructure and cooling systems .

Duos Edge AI's compute pods measure 55 feet long and 12.5 feet wide, resembling oversized shipping containers designed for truck transport. Each pod houses hundreds of GPUs. In a recent deal with AI infrastructure company Hydra Host, Duos deployed four pods containing 576 GPUs per pod, totaling 2,304 GPUs with an option to double the deployment to 4,608 GPUs .

LG CNS is pursuing a similar strategy with its AI Modular Data Center, which also contains 576 Nvidia GPUs per unit and can be scaled up. "We are currently developing an expanded version that can support more than 4,600 GPUs within a single unit, with a service launch planned within this year," said Heon Hyeock Cho, vice president and head of the datacenter business unit at LG CNS .

What Are the Key Advantages of Modular Deployment?

The benefits of modular data centers extend beyond speed. Site preparation becomes dramatically simpler: instead of constructing elaborate buildings, operators pour a concrete pad, place the modules on it, and connect them with fiber optic cables. This simplicity translates into multiple competitive advantages .

• Deployment Speed: Modular data centers can be operational in approximately six months, compared to two to three years for traditional facilities, cutting construction timelines by roughly 75 percent.
• Cost Efficiency: A five-megawatt modular deployment costs approximately $25 million, with Duos reporting that its cost per megawatt is roughly half what larger traditional facilities charge.
• Regulatory Simplicity: Smaller, modular deployments face less resistance from local governments increasingly skeptical about large-scale data center construction, and permitting processes are less complex.
• Scalability: Operators can start small and expand incrementally as demand grows, avoiding massive upfront capital commitments.

"Everything is built off-site at a factory, and we can put it together like a jigsaw puzzle," explained Recker, comparing the process to lining up school buses in a parking lot .

Is the Market Actually Growing?

The modular data center market is expanding rapidly. Hewlett Packard Enterprise, Vertiv, and Schneider Electric now have modular data centers available or in development. Market research firm Grand View Research estimates that the modular data center market could more than double by 2030, reflecting the industry's shift toward faster, more flexible infrastructure .

LG's ambitions illustrate the scale potential of this approach. The company plans to deploy up to 50 modular units in the South Korean port city of Busan, which would bring the total number of GPUs to over 28,000, rivaling the capacity of conventional hyperscale facilities. "By adopting a modular approach, the AI Modular Data Center can be incrementally expanded through the combination of dozens of AI Boxes," Cho noted. "It's enabling the construction of even hyperscale-level AI data centers" .

What Challenges Remain?

Despite the advantages, modular data centers face real constraints. While manufacturing a prefabricated unit can take 60 to 90 days, site preparation and permitting often extend timelines. "Site preparation extends the timeline because you can't get the permits that fast," Recker acknowledged .

Additionally, the modular approach works best for smaller deployments where permitting is less complex. Companies targeting massive hyperscale operations may still need to combine modular units with traditional infrastructure to achieve their goals. The technology is not a universal solution, but rather a powerful tool for companies that need to deploy AI infrastructure quickly without the overhead of traditional construction .

The modular data center revolution reflects a broader reality in the AI era: speed matters. As companies race to deploy AI models and compete for computing resources, the ability to go from site selection to operational infrastructure in six months rather than three years represents a genuine competitive advantage. For the AI industry, modular data centers are becoming less of a novelty and more of a necessity.