Reliable access to power is no longer a given for data center facilities teams. As demand surges, driven primarily by AI workloads, many regions are facing grid constraints, long interconnection timelines and increasing uncertainty around capacity.
“It’s no longer a given that there is going to be power available, especially for the size of the loads that are required for AI data centers,” says Drew Gravitt, senior director of distributed generation and microgrids at Mission Critical Group.
That sobering reality is forcing a shift in how facilities approach their planning. Site selection is no longer driven by connectivity or location alone, but increasingly by where power can be secured and how quickly it can be brought online.
Further complicating the issue is the nature of AI itself. Unlike traditional data centers, which operated with relatively stable, predictable loads, AI introduces a new level of unpredictable intensity.
“The challenge becomes managing higher overall demand with periods of high peaks layered on top,” says Arvin Ganesan, chief executive officer at Fourth Power.
Those peaks, layered onto an already elevated baseline demand, create strain not only on the grid but also on the infrastructure designed to support it. Systems built for steady-state operation are now being pushed to handle rapid spikes and sustained high usage, making traditional planning models less sufficient.
To adapt, data center operators are turning to a combination of on-site energy resources and advanced optimization strategies. Instead of relying entirely on utility power, many facilities are deploying hybrid systems that include on-site generation, battery storage and, in some cases, renewable energy.
“If generators are the muscle and uninterruptable power supplies are the heart, the optimizer is really the brain,” Gravitt says.
That “brain” plays a critical role in coordinating these resources — determining when to draw from the grid, when to dispatch stored energy and how to balance supply with highly variable demand. Without that layer of intelligence, operators risk overbuilding infrastructure or failing to respond effectively to rapid load changes.
Storage is emerging as a key tool — not just for backup power, but for actively shaping how facilities interact with the grid.
“Flexible-duration storage gives operators a way to smooth those ramps, maintain reliability and avoid overbuilding generation,” Ganesan says.
By absorbing energy during off-peak periods and discharging during periods of high demand, storage can reduce the need to size systems, and grid connections, for peak load at all times.
That has important implications for project timelines. With interconnection queues backed up for years in some markets, operators are looking for ways to move forward without waiting for large-scale utility upgrades.
“Storage can reduce how much interconnection a data center actually needs,” Ganesan says.
At the same time, many are adopting modular, phased deployment strategies, bringing capacity online in smaller increments rather than waiting for full buildouts.
These shifts are also changing the relationship between data centers and utilities. Rather than acting solely as large, passive consumers of power, facilities are beginning to play a more active role in grid operations.
Data centers are moving toward “a more collaborative partnership model” with utilities, Gravitt says, with opportunities to support the grid during periods of peak demand.
In that sense, optimization is doing more than improving efficiency. It is enabling data centers to operate with greater flexibility, reducing strain on the grid while, in some cases, helping stabilize it.
As AI continues to drive demand higher, that shift may prove essential — not just for data centers, but for the grid systems they depend on.
Jeff Wardon, Jr., is the assistant editor of the facilities market.
