The AI revolution is palpable. Reputable sources, like EY, Bloomberg, and JP Morgan, have reported that AI-related infrastructure investment became a major driver of US economic growth in 2025 – with some estimates suggesting it accounted for roughly one percentage point of GDP growth.

As a result, power or supply chain shortages that stall data center expansion could trigger significant financial ripple effects. Clearly, in today’s market, accelerating business operations to match rapid industry evolution is a necessity. Yet, while customer demand surges, utility interconnection and energization timelines are increasingly becoming schedule-critical constraints.

Where demand is immediate, infrastructure readiness is not. And in the capital-intensive data center industry, time quite literally equals money – each month of delay pushes revenue realization, inflates financing costs, and compresses project returns. As Thiago Fogaca Bianco, director of sales at Hitachi Energy, attests:

“Where data centers are concerned, the winner takes all – or the winner takes most. AI is driving another industrial revolution. If we don’t keep pace, we will be left behind.”

What’s on everyone’s mind

The goal? Accelerated time to market. Everyone – including Hitachi Energy, already a global leader in mission-critical electrification – has had to respond to market demand by making prefabricated, modular solutions a business necessity rather than an option.

The move to modular emerged from the simple reality that traditional delivery models could not scale at hyperscaler speed, withstand mounting financing pressures, or absorb the volatility driven by AI growth. Rooted in accountability, repeatability, and grid-first integration at scale, prefabrication addresses many of the structural gaps that are fueling widespread industry concern.

Hitachi’s Grid-eXpand portfolio uses pre-engineered, modularized, factory-built blocks – a model that shifts away from bespoke, site-intensive construction toward modular designs built around a common core – with fewer interfaces, reduced physical construction, and ‘drop-in-place’ pretested modules.

Time

In today’s market, a single day of delay for a hyperscale data center can represent millions of dollars in lost AI-as-a-Service revenue. The benefits of prefabricated solutions are clear and directly aligned with market demand for scalability.

In a traditional build, the electrical heart of the facility cannot be installed until the roof is complete and the dust has settled. The modular advantage allows equipment to be fabricated in parallel with building construction – while the site is being graded and foundations are poured – significantly reducing the overall project timeline by 30 to 50 percent, according to some projections.

This model eliminates longer construction cycles and reduces sequencing inefficiencies. Joseph Farina, business development manager for the grid integration team at Hitachi Energy, says:

“At Hitachi, we take lessons learned seriously. One of those lessons was recognizing that by working closely with utilities on interconnection requirements, and leveraging pre-engineered designs already approved by them, we have the capability of reducing the overall project schedule upwards of 12 months, as we’ve seen on recent projects.”

Workforce

Another critical consideration is how to deploy these vast sites at scale. Data centers are operating in the midst of an electrician and skilled technical labor drought. Given the sheer volume of projects required, it is unrealistic to expect this workforce to simply materialize – particularly in increasingly power-scarce and remote locations.

“These projects used to be in places like New York, Chicago, and Atlanta – large population hubs. Now they’re moving further out, with locations like Abilene, Texas, and parts of Louisiana seeing new developments,” says Bianco.

Prefabricating equipment in a factory and shipping it to the site requires far fewer personnel for installation, since the complex assembly work has already been completed. Factory fabrication also ensures higher quality control and safety outcomes. At the same time, Farina highlights the risks associated with overcrowded job sites:

“By minimizing the number of people needed on-site to wire complex breakers, you reduce the risk of installation errors that could lead to arc flash incidents or delayed inspections.”

Susan McLeod, VP of business development for North America at Hitachi Energy, explains:

“Anytime you have an issue, you’re going to have to send different resources back out to the site. We don't want that. It brings risk to everyone.

“We're in the factory doing this. You have all of those subject matter experts (SMEs) and critical resources there; they can immediately retest, redesign, and work through it, versus having to submit a case or ticket to get people back onto the customer site. It really expedites the process, mitigates risk, and helps manage the labor force.”

Predictability

Standardizing from the bottom up – and taking lessons from leaders like Nvidia in building “AI-ready” – helps create a more repeatable, almost cookie-cutter solution for customers. It provides an element of familiarity at a time when the broader landscape feels anything but stable.

This ties directly to repeatability, which is critical for efficient scalability. Standardized skid designs enable a near ‘copy-and-paste’ model when scaling up or down.

Consistent configurations reduce engineering redesign cycles, improve cost predictability, and support the reservation of manufacturing and delivery slots for long-lead equipment, ensuring it arrives when and where it’s needed. Bianco contextualizes:

“From my time as a quality manager, I learned that when you’re assembling a complex piece of equipment in a factory, and something isn’t working correctly, it’s much faster and cheaper to fix it there than in the field, where you may not have the right engineers on hand. It prevents the cascade effect on cost and time.”

Importantly, predictability extends beyond the walls of the data center. We are living in unpredictable times – shifting weather patterns, force majeure events, and evolving regulatory requirements are reshaping project parameters in real time. A centralized facility that controls all of the design and construction of key equipment provides a stabilizing factor, shielding progress from external disruptions that would otherwise derail schedules.

Taken together, this approach reduces unknowns, limits interface failures, and speeds up final acceptance.

Balancing speed with reliability

In an industry that prizes speed to market and scale, it is imperative to ensure rapid delivery does not compromise reliability. Where Hitachi is concerned, speed and reliability are not competing priorities – they are engineered together by design.

A quality product built to last the ages undergoes a rigorous factory acceptance testing (FAT) regime. This begins with detailed component-level performance testing and progresses to full system-level validation as those components are integrated.

A complete system is ‘a different animal’ as Bianco puts it. Each element is energized, integrated with the control architecture – the brains of the system – and tested to ensure everything behaves as intended before it leaves the factory. By the time it reaches the field, it is ready to operate. McLeod explains:

“Design alone can take six to nine months. But with a repeatable approach, you’re down to about a month because you’re starting with an 80 percent solution that’s already proven. You only need to tweak the remaining 20 percent. Over time, that solution becomes even more refined, contributing to sustainable design and continuous improvement.”

For example, early FAT cycles in the Hitachi Energy factory reinforced the need for tighter harmonization between protection and controls, as well as clearly documented cutover plans from interim to permanent infrastructure.

In response, the team strengthened standard interfaces, codified commissioning playbooks, and defined objective completion tests to reduce rework during site energization.

This removes many of the variables that traditionally introduce risk and delay in site-built approaches. As Farina emphasizes:

“We’re not speeding up to cut scope. We’re speeding up by removing variability within the scope.”

Grid-grade engineering

In the name ‘Grid-eXpand,’ you get a sense of Hitachi’s emphasis on grid-grade engineering – an approach that, as Farina explains, begins far earlier and with more theory than most might assume:

“To design with grid-grade engineering, we have to have an understanding of what’s required to connect to the grid. That means incorporating interconnection studies, including power quality management, protection coordination, grid code compliance, validation of fault duty, and harmonic mitigation. All of it must be addressed upfront to fully understand utility requirements.”

This approach builds on Hitachi’s long-standing experience working alongside utilities, as McLeod explains:

“Customers value our experience with the utilities that we’ve worked with for decades and our deep understanding of their requirements across all regions of the US.”

On the hardware side, the Grid-eXpand portfolio standardizes the ‘power blocks’ into repeatable increments (20, 40, 60 MW blocks) that have clearly defined interface points across utility, EPC, and customer scopes. The blocks are directly aligned with phased capacity plans, regional code requirements, and interconnection study parameters to streamline acceptance.

Operationally, global manufacturing and supply chains align module form factors with regional shipping constraints and site realities, while preserving design repeatability.

Software forms the unified control layer that allows modular assets to function as a single, dispatchable, grid-compliant system – supporting predictable performance even amid AI-driven load volatility. These grid-aligned controls also enable customers to participate in cleaner, more flexible grids as they scale.

“Digital sensors and predictive maintenance give us real-time insights. We design these systems so Hitachi Energy can manage them proactively and predictably,” says McLeod.

“We’re shifting from time-based maintenance to condition-based maintenance. Sophisticated controls allow us to connect operational data and extend asset life by preventing failures before they happen,” adds Bianco.

Layered on top of this, digital twin protocols enable customers to model their entire systems, anticipate potential issues, and future-proof the lifecycle of their infrastructure. Whether workloads shift from AI training to inference or other applications, full system digitalization provides complete visibility and predictive insight.

A word on sustainability

Factory-built, modular systems that minimize rework and material waste are inherently sustainable by design. Every element of a quality grid-interactive behind-the-meter (BTM) solution – from power quality controls to lifecycle services – should be engineered to maintain operational efficiency over decades.

When a power architecture can absorb AI load swings, phased expansion, and shifting operational demands without major retrofits, it reduces stranded assets, avoids unnecessary material replacement, and limits repeat construction impacts. With proper maintenance, these systems are designed to last for decades – up to 80 years by some estimates – often outliving the data center itself. Where degradation occurs, Hitachi services and restores equipment, managing assets across their full lifecycle.

As AI compute and data center requirements continue to evolve, Hitachi provides a cross-speciality team – spanning Hitachi Energy, Hitachi Digital Services, Vantara, GlobalLogic, and others – offering end-to-end support. Across these sister companies, service remains a single point of accountability, ensuring seamless, integrated service across the entire lifecycle of their infrastructure.

Considerations of grid-integrated electrification

At the core of hyperscale electrification lies a fundamental mismatch between the rapid payback expectations of data center investors and the longer horizons of power generation assets. Private equity often expects returns within three or four years, yet generation projects can take five to 15 years to break even.

This disparity creates a financial tension, forcing data center investors to rethink their funding structures, risk appetites, and ownership strategies. After all, if you don’t have power, you don’t have revenue.

Modular BTM solutions – rooted in technical repeatability – allow operators to unlock capacity earlier, de-risk schedules, and accelerate the path to revenue.

Beyond these financial considerations, the practical implementation of BTM solutions requires expert-led refinement. Where large public grids typically rely on substantial spinning generators (coal, gas, hydro turbines, and nuclear plants) that provide inertia to stabilize the grid during sudden load swings, BTM solutions and microgrids lack that inherent inertia. They can respond quickly, but they don’t provide the same natural grid stability.

The key here lies in active management and integration. Instead of treating these assets as simple generators or battery packs, operators should leverage BTM modules as fully controlled, grid-compliant solutions to ensure they behave predictably and safely, contributing to overall system reliability – especially in phased energization scenarios, or where utility timelines are uncertain. As Bianco notes:

“It’s usually best to have a mix of generating assets – a portion behind-the-meter for speed and capacity, and a portion from the grid for electrical stiffness and stability.”

And the regulatory landscape is anything but simple

Regulatory frameworks add another layer of complexity, shaping what is feasible and profitable for data center operators.

Today, the North American Electric Reliability Corporation (NERC), which sets reliability standards across North America, and the Federal Energy Regulatory Commission (FERC), which regulates interstate transmission and wholesale markets, both heavily influence how data centers can connect to the grid.

For example, for the PJM Interconnection system that coordinates electricity and ensures reliability across 13 states in the Mid-Atlantic and Midwest, even small changes can cascade across the system. Bianco paints the picture:

“Imagine you have operating assets, particularly in unregulated markets, where you can connect directly to a nuclear power plant. That plant may have previously provided reliability to PJM. If you redirect that capacity, you’re effectively removing reliability from the grid. Regulatory authorities have to limit how many megawatts can be allocated to avoid broader impacts across the entire PJM.”

Layer on regional and federal dynamics, and you add further complexity. In West Virginia, for example, integrated resource planning reflects the explosive data center demand growth. Utilities are bringing new gas generation assets online, while shifts in investment tax credits affect the economics of wind, solar, and battery storage, influencing both project design and payback profiles.

At the same time, federal initiatives like the CHIPS and Science Act are streamlining permitting and infrastructure development, and ISOs are modernizing interconnection processes to keep pace with hyperscale demand.

The result is a regulatory environment that is fast-moving, fragmented, and chaotic – to say the least. In this context, standardization becomes a critical strategic lever. When designs are repeatable, organizations can reduce financial friction, simplify regulatory compliance, and ensure technical resilience in a climate where the legacy mindset of ‘every location is unique’ simply doesn’t work for hyperscale growth.

No regrets

One of the most enduring insights from the team is simple: “The most sustainable move a developer can make is getting the backbone right once, so it carries the program forward without tearing it apart every few years.”

A ‘no-regrets’ approach does exactly that. It standardizes repeatable, phasable power blocks with objective completion tests, de-risks interconnection through factory-tested modules, and treats BTM systems as compliant, controllable assets.

“This environment reduces risk, and that’s essentially the idea behind each system we design. Whatever the density curves or grid quality, the system delivers predictability – the backbone of our design strategy,” says Farina.

In the rush to accelerate power delivery, hyperscalers and colocation providers often purchase components piecemeal, only to face delays, retrofits, or expensive repurchases because the complete design and configuration weren’t fully considered.

A system-level, modular, prefabricated solution takes that risk off the table. It enables faster energization, the flexibility to pause or accelerate deployment as demand shifts, and the ability to evolve toward higher-density or hybrid AC/DC architectures without a full redesign. In short, the power platform must be built to scale – or pivot – ensuring infrastructure can adapt to unpredictable AI demand shifts, without ever having to tear it apart.

For more information, please visit Hitachi Energy.