Research and advisory firm Gartner has published a forecast projecting that data-center electricity consumption will grow 26% in 2026. The figure, released in June 2026, puts a number on what utilities, grid operators, and data-center builders have been experiencing on the ground: power — not land, capital, or chips — has become the binding constraint on digital-infrastructure growth.

Executive Summary

Gartner’s headline claim is simple: the electricity consumed by data centers will rise 26% in 2026. For context, most mature electricity systems in developed economies have spent two decades planning around annual demand growth in the low single digits. A single customer class growing 26% in one year is the kind of step-change that utility resource plans — documents typically written on five-to-fifteen-year horizons — were not designed to absorb.

The forecast matters less as a precise number than as a planning signal. If even a substantial fraction of that growth materializes, it shapes generation procurement, transmission buildout, interconnection queues, and electricity rates for every other customer sharing the grid. For data-center operators and their customers, it also signals that access to secured, deliverable power will continue to separate projects that get built from projects that wait.

A 26% Jump Is a Planning Problem, Not Just a Number

Electric utilities plan in decades. Building a new gas plant, a transmission line, or a large substation typically takes years of permitting, procurement, and construction. Demand that grows 26% in a single year — even within one customer segment — compresses those timelines past what traditional integrated resource planning can handle. The practical consequence is already visible across the industry: multi-year interconnection queues (the waiting list to connect large new loads or generators to the grid), utilities demanding long-term take-or-pay commitments from data-center customers, and regulators debating who bears the cost if forecast demand fails to show up.

The forecast, in other words, is best read as a statement about mismatch: digital infrastructure now moves at software-industry speed, while the electricity system that feeds it still moves at heavy-civil-engineering speed. Closing that gap — through faster permitting, on-site generation, or demand flexibility — is the defining infrastructure challenge the number points to.

AI Is Rewriting the Load Curve

Growth of this magnitude is not organic expansion of traditional enterprise computing. Conventional data-center workloads — web serving, databases, storage — grew steadily for years while efficiency gains (better chips, better cooling, higher utilization) kept electricity demand roughly flat. What changed is accelerated computing: AI training and inference run on dense GPU racks that can draw several times the power of traditional server racks and tend to run at sustained high utilization rather than in daily peaks and troughs.

That load profile is a mixed blessing for utilities. Flat, predictable, around-the-clock demand is easier to serve than spiky demand and can improve grid economics by spreading fixed costs over more kilowatt-hours. But it also removes slack: a grid serving large always-on loads has less headroom for extreme weather events and less tolerance for generation shortfalls. How much of Gartner’s projected growth is firm, flexible, or interruptible will matter as much as the total.

Winners, Losers, and the Power Value Chain

If the forecast is directionally right, the beneficiaries extend well beyond data-center operators. Makers of transformers, switchgear, generators, and cooling equipment — many already quoting extended lead times — see demand visibility measured in years. Generation developers, from gas turbines to nuclear restarts to utility-scale renewables paired with storage, gain a creditworthy customer class willing to sign long-dated contracts. Utilities in data-center-heavy regions gain load growth after decades of stagnation, though with real execution and rate-design risk.

The squeezed parties are those competing for the same electrons and equipment: other large industrial loads, smaller colocation players without utility relationships, and — if cost allocation is handled poorly — residential ratepayers. For data-center operators themselves, the forecast reinforces an emerging hierarchy: companies holding contracted, deliverable power capacity own an appreciating asset, while those still in interconnection queues hold an option of uncertain value.

Treat the Number as a Signal, Not a Certainty

A forecast is a model, and this one — as syndicated — arrives without its assumptions attached. Projections of AI-driven power demand have varied widely across analysts, and history urges caution: early-2000s forecasts of runaway internet power consumption overshot badly because they underestimated efficiency gains. Chip-level performance-per-watt improvements, smarter model architectures, and rising inference efficiency could all bend the curve; conversely, faster-than-expected enterprise AI adoption could steepen it.

The even-handed reading is that Gartner’s 26% figure is a credible-sounding midpoint from an established research house, but its value depends on methodology the public headline does not disclose — baseline year, geographic scope, and workload assumptions among them. Planners should treat it as one scenario input, not a settled fact.

Background

Data-center electricity demand was, for roughly a decade before the AI era, a story of successful restraint: workloads migrated into ever-more-efficient hyperscale facilities, and total consumption grew far more slowly than computing output. That equilibrium broke with the generative-AI buildout that began in earnest in 2023, as operators raced to deploy GPU clusters whose power density and utilization patterns overwhelmed the old efficiency offsets. Since then, power availability has displaced real estate as the industry’s primary constraint, and forecasts from analysts, utilities, and government agencies have been repeatedly revised upward.

Gartner, a research and advisory firm whose projections are widely used in enterprise technology planning, publishes recurring forecasts on data-center spending and infrastructure. Its June 2026 electricity-consumption forecast lands amid active debate among utilities, regulators, and operators over how much of the projected AI load will actually materialize — and who should pay to serve it.

Source: Gartner Says Data Center Electricity Consumption to Grow 26% in 2026 — Gartner’s June 2026 forecast announcement, as syndicated via Google News.

On May 19, 2026, the U.S. Energy Information Administration (EIA) — the federal government’s independent energy statistics agency — published new commercial-buildings data showing that energy consumed by data center servers is growing across the nationwide commercial building stock. The finding lands in the middle of an intense public debate over how much electricity the AI build-out actually consumes.

The release matters less for any single number than for its source: this is federal survey data, not a vendor forecast, quantifying how server energy use has expanded within America’s offices, dedicated data centers, and the server rooms tucked inside ordinary commercial buildings.

Executive Summary

EIA’s announcement extends its commercial-buildings statistical program — best known through the Commercial Buildings Energy Consumption Survey (CBECS), the government’s long-running census-style study of how U.S. commercial buildings use energy — to document rising server energy consumption across the building stock. In plain terms: the computers doing the computing inside commercial buildings are drawing a growing share of those buildings’ electricity.

Why it matters: nearly every claim about the ‘AI power crunch’ to date has rested on private-sector estimates from consultancies, utilities, and technology vendors, each with its own methodology and, in some cases, its own commercial interest in the answer. A federal statistical agency measuring the same trend from building-level survey data gives regulators, utilities, and investors a common, disinterested baseline — the kind of number that ends up cited in rate cases, siting decisions, and congressional testimony.

For infrastructure operators, the direction of the data is unsurprising. The significance is that the growth is now visible across the commercial building stock — not only in purpose-built hyperscale campuses, but in the broader population of buildings that house servers.

Federal Numbers Change the Power Debate

Until now, the data center energy conversation has been dominated by projections — analyst decks, utility interconnection queues, and corporate sustainability reports. Projections are arguments; survey data is evidence. EIA’s commercial-buildings program measures what buildings actually consumed, which makes it the closest thing the industry has to a scoreboard. When a .gov dataset says server energy use is growing across the building stock, it becomes much harder for any side of the debate — boosters or critics — to dismiss the trend as hype or alarmism.

That cuts both ways. Utilities seeking rate recovery for grid upgrades, developers seeking permits, and efficiency advocates seeking standards will all now cite the same federal source. Expect this data to surface in state utility commission filings and local zoning fights, where the credibility of the underlying numbers is often the whole battle.

The Hidden Data Center Problem

The phrase ‘commercial building stock’ is doing important work in EIA’s framing. Public attention fixates on gigawatt-scale AI campuses, but a substantial slice of America’s server fleet has historically lived in less visible places: server rooms in office buildings, hospital basements, university closets, and small enterprise data centers. These embedded loads are dispersed, often inefficient, and poorly captured by headline hyperscale statistics.

Growth measured across the whole stock suggests the compute boom is not just a story of a few hundred giant facilities — it is diffused through the built environment. For the efficiency industry, that is a market signal: dispersed, aging server rooms are prime candidates for consolidation into professionally run colocation facilities, which typically achieve far better power usage effectiveness (PUE — the ratio of total facility power to the power that actually reaches computing equipment).

Winners, Losers, and the Grid in Between

The beneficiaries of officially documented demand growth are the companies positioned to serve it: colocation and cloud operators with contracted power in hand, transmission developers, and equipment suppliers across the cooling and electrical chain. Utilities gain justification for capital programs, though they also inherit the political risk of rising rates being blamed on data centers.

The exposed parties are energy buyers competing for the same electrons — manufacturers, electrified transport, and ordinary ratepayers — and any data center developer whose business case assumes cheap, quickly available power. Federal confirmation of demand growth strengthens the hand of grid planners who argue for building ahead of load, but it equally strengthens critics who ask whether that growth should pay its own way. The honest reading of EIA’s data is that it quantifies the trend without settling the policy argument.

Background

EIA has surveyed U.S. commercial buildings for decades through CBECS, producing the government’s authoritative picture of how offices, schools, hospitals, and other non-residential buildings consume energy. Data centers historically registered as a small but disproportionately energy-intensive slice of that stock — buildings that consume many times more electricity per square foot than a typical office.

The context shifted sharply after 2023, when large-scale AI training and inference drove a wave of data center construction and record utility interconnection requests, making data center electricity demand a national policy issue. Against that backdrop, federal measurement of server energy use across the building stock arrives as a reference point both industry and its critics have lacked.

Source: Data center server energy use grows across the commercial building stock — U.S. Energy Information Administration announcement of new commercial-buildings energy data, published May 19, 2026.

The Midcontinent Independent System Operator (MISO) — the grid operator coordinating electricity across a footprint spanning 15 U.S. states and the Canadian province of Manitoba — expects electric load to jump roughly 35% by 2035, according to an April 2026 report from Utility Dive. The primary driver named in the forecast is data center growth.

A 35% increase over roughly a decade represents a dramatic break from the era of essentially flat U.S. electricity demand that prevailed from the late 2000s through the early 2020s, and it puts one of the largest grid operators in North America on record quantifying the scale of the AI-and-cloud buildout.

Executive Summary

MISO’s forecast is a planning document, not a press release from a company selling something — which makes it one of the more consequential data points in the ongoing debate over how much electricity the data center boom will actually consume. Regional transmission organizations (RTOs) like MISO exist to keep supply and demand balanced in real time and to plan the wires and generation needed years ahead. When an RTO raises its ten-year demand outlook by more than a third, that number flows directly into transmission planning, capacity auctions, and the resource plans of dozens of utilities.

The significance is twofold. First, it validates what individual utilities across the Midwest and Gulf South have been reporting piecemeal: hyperscale data center projects are arriving in interconnection queues at a pace with no modern precedent. Second, it sets up a decade of hard trade-offs. Meeting 35% growth requires new generation, new transmission, and new large-load interconnection rules — all on timelines that historically run slower than the two-to-three-year construction schedule of a data center campus.

For the infrastructure industry, the headline number is both an opportunity signal and a warning: the grid is now the binding constraint on digital infrastructure growth, and the regions that solve power delivery fastest will win the next wave of siting decisions.

The End of Flat Demand Is Now Official Planning Doctrine

For roughly fifteen years, U.S. grid planners could assume that efficiency gains — LED lighting, better HVAC, industrial offshoring — would offset economic growth, keeping total electricity demand nearly flat. That assumption underpinned everything from utility rate cases to power plant retirement schedules. A 35% load-growth forecast from MISO formally retires it for one of the largest grid footprints in North America.

What makes an RTO forecast different from a consultant’s projection is accountability: MISO must plan transmission and resource adequacy against this number. If the forecast is right and the buildout lags, the result is capacity shortfalls and price spikes. If the forecast is wrong and infrastructure is overbuilt, ratepayers carry stranded costs. Either error is expensive, which is why the assumptions behind the number — how much announced data center load actually materializes — deserve as much scrutiny as the number itself.

Data Centers as the Marginal Buyer of Power

A data center is, from the grid’s perspective, an unusual customer: it demands large blocks of power (often hundreds of megawatts per campus), runs at high utilization around the clock, and wants to connect years faster than traditional industrial load. When such customers become the dominant source of demand growth, they effectively set the terms of grid expansion — and grid operators, utilities, and regulators are still working out who pays for the upgrades those connections require.

The economics cut in several directions. Utilities in MISO territory gain a growth story they have not had in a generation, which supports investment in wires and generation. Existing ratepayers face the risk of subsidizing infrastructure built for loads that may not fully arrive — a concern regulators in several states are already addressing through special large-load tariffs and financial-commitment requirements. Data center developers, meanwhile, face the reality that power availability, not land or fiber, now determines where and when they can build.

Winners, Losers, and the Speed Mismatch

The core tension in a 35%-by-2035 scenario is timing. Gas turbines face multi-year order backlogs, new nuclear operates on decade-plus horizons, and large transmission projects routinely take seven to ten years from planning to energization. Data center campuses go from groundbreaking to load in two or three. That mismatch favors whoever can bridge it: developers with early interconnection positions, utilities with spare capacity or fast-track large-load processes, suppliers of grid equipment, and operators pursuing on-site or co-located generation.

It also raises competitive stakes between regions. MISO’s footprint — stretching from the upper Midwest to the Gulf Coast — competes with PJM, ERCOT, and the Southeast for hyperscale siting. A credible, well-executed plan to serve 35% more load is itself an economic-development asset; a forecast without matching buildout is a queue of frustrated customers who will site elsewhere.

Forecast Versus Reality: The Phantom Load Question

Every load forecast in the current environment must grapple with duplicate and speculative requests. Developers commonly file interconnection requests in multiple jurisdictions for the same project, and some announced campuses will never be built. Grid operators know this and apply screening assumptions, but the industry has little historical data on what fraction of AI-era announced load converts to actual consumption. The honest read of any 35% figure is that it is a planning scenario with meaningful uncertainty in both directions — actual growth could undershoot if projects evaporate, or overshoot if AI demand keeps compounding.

That uncertainty is not a reason to dismiss the forecast; it is a reason to watch how MISO and its member utilities structure commitments. Mechanisms that require large customers to put capital at risk — minimum-take contracts, collateral requirements, contribution to network upgrades — are the market’s way of separating real load from phantom load, and their adoption across the footprint will be a better indicator of true demand than any single projection.

Background

MISO was founded in 1998 and became the first FERC-approved regional transmission organization in the United States in 2001. It coordinates generation and high-voltage transmission across a footprint stretching from the upper Midwest down through the Gulf South, serving tens of millions of people through its member utilities. Like other RTOs, it does not own power plants or lines; it operates markets and plans the system that its members build.

The forecast arrives amid a broader U.S. re-acceleration of electricity demand after more than a decade of stagnation, driven by AI and cloud data center construction, manufacturing reshoring, and electrification. Grid operators across the country have been revising load outlooks upward repeatedly since the early 2020s, and interconnection queues for both large loads and new generation have swelled to historic levels — making forecasts like this one central to the industry debate over how much of the announced boom is real.

Source: MISO expects load to jump 35% by 2035 on data center growth — Utility Dive report, April 21, 2026, on MISO’s ten-year load forecast.