The magnitude of demand for AI has surprised everyone. McKinsey predicts that global demand for AI capacity could triple by 2030. And it’s created some challenges for data center operators, who are rushing to modernize power and cooling infrastructure to support the technology. One way to accelerate data center deployments is through AI pods – prefabricated infrastructure blocks that contain all the power and cooling required for AI.

Speed to market: What’s the rush?

As demand soars, data center providers are looking to realize a return on their AI investments as quickly as possible. The first companies to establish AI-ready infrastructure become market leaders, gaining a competitive edge.

The challenge is demand for AI grew so fast that most data centers weren’t ready for deployment. AI workloads require much higher rack densities, which are already reaching 227 kW per rack. This is largely a result of the power requirements of new chips, which are evolving rapidly – almost doubling with each release at 1.5-year intervals.

Increased infrastructure complexity

Higher densities equal more heat. Direct-to-chip cooling is becoming an operational necessity as air cooling cannot efficiently handle the intense heat generated by AI racks. This poses a challenge in some data center operations, depending on water access or their operating footprint. While air cooling could be handled with hot/cold aisle containment and in-row and in-rack cooling, direct-to-chip cooling, the predominant liquid cooling method in the market requires complex plumbing and piping networks for each rack.

Explore AI-ready liquid cooling resources

AI is also driving up power densities, adding further complexity to the infrastructure. It’s not unusual to see six to eight power whips (flexible electrical cables) connected to each AI rack. With the emergence of new open rack architectures designed specifically for AI workloads, power requirements are increasing even further. And with 800 VDC architectures and 1MW racks on the horizon, the shift toward higher-voltage, high-efficiency power distribution is accelerating even faster.

As a result of liquid cooling, high density, and new power architectures, every connection is even more critical. Every pipe, fitting, valve, cable, and power interface is a potential point of failure. A misplaced sensor can cause commissioning delays or poor operation, which gets amplified when building AI factories by the hundreds or thousands.​ The answer is to build these pods in a controlled factory environment, where precision, repeatability, and quality control ensure both speed and certainty.​

Accelerate speed to market with AI Pods

Data center operators can accelerate AI deployments by leveraging AI pods. These prefabricated infrastructure units reduce installation work from months to days. A pod consists of a reinforced steel truss that sits on four legs above the rack, supporting a superstructure that carries power cables and the plumbing and piping for liquid cooling.

Each truss supports up to 15,000 pounds of busway and piping materials, including copper, aluminum, and stainless steel. In traditional data centers, all of this infrastructure was crammed under the floor, but that is no longer practical. The traditional approach required months to build the infrastructure, with components delivered in separate boxes.

AI pods come preconfigured with a power and cooling architecture that is already designed and optimized for performance. Everything is shipped together in prefabricated and pre-integrated units. AI pods can be delivered and deployed when new data center sections are ready to be populated, allowing operators to add megawatts of capacity as quickly as possible.

AI racks deliver the last mile in the vital backbone of this integrated approach, which is specifically engineered to manage the complex physical intersection of high-capacity power distribution and liquid piping. These solutions, which include MGX-compatible racks and ORV3-based designs, are purpose-built to accommodate the high-wattage power needs and intricate manifold systems required for direct-to-chip liquid cooled AI servers.

Supporting the AI ecosystem

As the AI ecosystem rapidly evolves, Schneider Electric continues to innovate across power, cooling, and digital infrastructure to help operators deploy AI more quickly and efficiently.

Schneider Electric provides prefabricated AI pods to enable faster time-to-market for new AI data centers. The pods represent a revolutionary approach, enabling the construction of data centers from prefabricated units and addressing the complexities of power and liquid cooling for AI.

Liquid cooling is not a bolt-on feature – it is a necessity and a foundational design decision within the AI ecosystem. That’s why Schneider Electric engineers AI Pods as fully integrated blueprints, aligning power, liquid cooling, and digital management from day one. Working closely with NVIDIA engineering teams, creating reference designs such as reference design 110 for the NVIDIA GB300 NVL 72 and reference design 113 for NVIDIA’s Vera Rubin NVL72 racks, we help ensure infrastructure is ready not just for today’s accelerators, but also for the next generation of higher-density, more powerful chips.

Built with scalability and flexibility at the core, AI Pods enable operators to expand capacity as technology evolves – without rearchitecting their facilities. The result: reduce complexity to faster deployment, future-ready performance, and a clearer path from AI investment to revenue generation.

Discover how Schneider Electric AI Pods can help you deploy AI infrastructure faster, smarter, and ready for what’s next.