Loudoun County in Virginia illustrates how the rapid expansion of data centers is reshaping regional energy systems, as a once pastoral area now contains the highest concentration of such facilities worldwide. Ten years ago, these data centers mainly powered email and e-commerce, but the surging demand for artificial intelligence services is driving local utility Dominion Energy to keep up with sharply rising loads, and Dulles International Airport is building the largest airport solar installation in the country to help support the region’s power mix. Similar data center campuses are proliferating across the United States to satisfy an insatiable demand for artificial intelligence, and the resulting buildout is putting intense pressure on grids and communities.
Data centers consumed roughly 4% of national electricity in 2024, and projections suggest that figure could stretch to 12% by 2028. In the same context, a single 100-megawatt data center consumes roughly as much electricity as 80,000 American homes, and some facilities under development are preparing for gigawatt scale comparable to the needs of a mid-sized city. For enterprises, the energy costs tied to artificial intelligence and data infrastructure are becoming both a major budget issue and a potential cap on future growth, elevating the importance of energy intelligence, defined as understanding where, when, and why energy is used, then applying those insights to optimize operations and manage costs. These concerns also carry reputational implications, as residents in communities hosting large data centers increasingly scrutinize the local energy impact.
Survey findings from 300 executives highlight how quickly energy intelligence is moving to the center of strategy. One hundred percent of executives surveyed expect the ability to measure and strategically manage power consumption to become an important business metric in the next two years. Two-thirds of executives (68%) report their companies have faced energy cost increases of 10% or more in the past 12 months due to artificial intelligence and data workloads, and nearly all respondents (97%) anticipate their organization’s artificial intelligence-related energy consumption will increase over the next 12-18 months. Half of executives (51%) rank rising costs as the single greatest energy-related risk to their digital and artificial intelligence initiatives, and most efforts to track and optimize data center energy use are primarily motivated by cost management. In response, three in four leaders (74%) are optimizing existing infrastructure, 69% are partnering with energy-efficient cloud and storage providers, 61% are implementing artificial intelligence workload scheduling, and 56% are investing in more efficient hardware. Yet a significant measurement gap remains, especially for organizations dependent on third-party cloud and managed services, where 71% say rising consumption-based costs originate but energy metrics are often opaque, underscoring that obtaining granular data is the next frontier for true energy intelligence.
