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Data-center construction can benefit far more than chipmakers and cloud operators. Contractors, skilled trades, electrical-equipment suppliers, cooling providers, engineers, material suppliers, transport firms, and power-infrastructure businesses all sit along the delivery chain. But rising industry demand does not prove that any particular company will win: projects can be delayed, power requests can fall through, and supplier revenue depends on what actually gets built.
What the data-center power forecasts actually say
The scale of the opportunity is tied to a substantial, but uncertain, rise in electricity use. Lawrence Berkeley National Laboratory’s 2026 publication of its 2025 update estimates that U.S. data centers will use 649 terawatt-hours (TWh) of electricity in 2030 in its reference case, equal to 11.8% of total U.S. electricity use. Its scenario range is 9.5% to 15.3%; the model’s compounded uncertainty bounds are 521 to 843 TWh.
Those figures are forecasts, not a measurement of 2030 consumption. LBNL’s model incorporates planned equipment shipments, device-energy models, cooling simulations, and information about facility types and locations. The range matters: companies supplying new capacity may face different outcomes depending on how quickly computing demand grows and where facilities are built.
The recent trend is also stronger than in the prior period. The U.S. Energy Information Administration reported annual electricity-demand growth of 1.7% from 2020 to 2025, compared with 0.1% from 2005 to 2019. That comparison describes overall U.S. electricity demand; it does not attribute the increase entirely to data centers.
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Who benefits from data-center construction beyond chips and cloud?
Associated General Contractors of America identifies a broad construction chain that includes contractors, skilled trades, equipment and component suppliers, design services, materials, and transport. Its May 2026 figure shows how much activity the build-out can generate: data-center construction spending reached $59.3 billion at a seasonally adjusted annual rate, up 23% from a year earlier and about 8.0% of private nonresidential construction spending. The annualized rate is a run-rate measure, not the amount spent during May alone.
| Beneficiary category | Why it is exposed to the build-out | What the evidence establishes |
|---|---|---|
| Construction contractors and skilled trades | Facilities require specialized construction and installation work for electrical systems, backup power, cooling, fiber, security, and utility infrastructure. | AGC identifies contractors and trades in the construction chain and reports the spending measure above. |
| Transformers and electrical components | Facilities need to connect to power and distribute electricity within the site. | AGC identifies transformers and electrical components as supply-chain categories; the cited evidence does not quantify any supplier’s sales. |
| Cooling providers | Operating data centers requires cooling, and cooling systems are part of the facility’s energy use. | LBNL’s electricity model incorporates cooling-system simulations; AGC also identifies cooling systems as a construction category. |
| Architects, engineers, and project services | Complex facilities need planning, design, and engineering as well as physical construction. | AGC identifies architecture and engineering services in the construction chain. |
| Building-material suppliers and transport firms | Projects require materials and equipment to be sourced and moved to construction sites. | AGC identifies building materials and trucking as indirect supply-chain categories. |
| Power generation and grid infrastructure | Large loads require generation and a way to deliver electricity, which may involve transmission, interconnection, storage, or onsite supply. | EIA describes demand and supply scenarios; FERC’s 2026 action addresses grid-connection rules. The eventual generation mix and business returns depend on location, policy, and timing. |
This is a map of exposure, not a ranking of publicly traded companies. The category-level evidence does not establish firm-specific revenue, margins, market share, or the share of a supplier’s business that comes from data centers.
Why the power opportunity varies by region
Data-center demand does not affect every electricity market in the same way. In its March 12, 2026 analysis, EIA used the February 2026 Short-Term Energy Outlook as its baseline and tested a higher-demand case. In regions with significant data-center development, that case assumes load growth rates 50% above baseline and keeps future generating capacity the same as in the February forecast. EIA cautions that results may differ from later forecasts.
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Under those assumptions, the strongest modeled wholesale-price effect is in ERCOT, the Texas grid. EIA’s modeled 2027 ERCOT price is $37 per megawatt-hour (MWh) above its February 2026 forecast. In PJM, the modeled change is $2.60/MWh, or 4%. These are scenario results, not price predictions or guarantees of what power producers will earn.
EIA identifies ERCOT and PJM as the fastest load-growth regions in its near-term outlook, forecasting average annual load growth of 10% in ERCOT and 3% in PJM from 2025 to 2027. The larger modeled ERCOT price response reflects, in part, the grid’s limited connections to neighboring regions. A result from one regional model should not be generalized to every U.S. market.
In EIA’s high-demand case, natural gas is the primary source of available generation for incremental demand. As historical context, natural gas supplied 40% and coal 17% of U.S. generation in 2025. Those national generation shares do not show the source of electricity used by a particular data center or the terms of its power contract.
How grid rules shape connections and costs
On June 18, 2026, the Federal Energy Regulatory Commission directed the six regional grid operators under its jurisdiction to justify their existing tariffs or propose reforms within 60 days for data centers and other large energy users. The action concerns how large loads connect, how their costs are handled, and what information is available—not a guarantee that a particular project will receive service or that a specific tariff will be adopted.
- Transmission-service applications and study processes, including how to make them more efficient.
- Cost transparency and protections against shifting costs to other customers.
- Co-location with power sources and behind-the-meter generation.
- Flexible service options for large loads that can adjust consumption.
- How to study generation serving nearby or co-located large loads.
These proceedings can affect project timing and economics for data-center developers and the businesses that supply them. Their eventual outcomes were not established by the commission’s announcement.
The Department of Energy’s December 2024 summary of an earlier LBNL report described possible responses to rising demand, including onsite power and storage, reusing infrastructure at retired coal sites, rate structures, transmission expansion, and efficiency and flexibility measures. These are potential approaches, not a list of adopted requirements or guaranteed choices for new projects.
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McKinsey’s 2026 analysis describes uncertainty in corporate AI execution, capital markets, energy prices, and supply chains. It also notes that speculative or duplicate requests for power can distort utility planning, equipment orders, and engineering, procurement, and construction capacity. A request for grid capacity is not the same as a completed facility or a supplier sale.
If data-center demand slows, some proposed projects may not materialize, and suppliers exposed to construction schedules could see orders delayed or canceled. The effect need not be identical across the power sector: McKinsey notes that power assets may serve other sources of demand. Whether an asset can be redirected, and on what terms, depends on its location, design, and operating arrangements.
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There is also a meaningful difference between announced projects, requested grid capacity, contracted capacity, construction starts, completed facilities, and revenue recognized by suppliers. Treating all announced or requested capacity as committed spending overstates what is known about near-term business results.
How to assess whether a supplier is truly benefiting
For a specific company, look beyond the general growth story and test its exposure against the project pipeline and the economics of its business. The sources cited here do not provide comparable company-level data, so these are questions to investigate in a company’s disclosures rather than conclusions about named firms.
- Measure directness. Is the company selling equipment or services directly into data-center projects, or is its exposure indirect through construction, utilities, or general building demand?
- Identify the bottleneck. Does it supply a component or service that is difficult to source, and what do the company’s disclosures say about delivery times and capacity? Category-level demand alone does not establish pricing power.
- Check geography. Where are the company’s customers and projects, and how exposed are they to the grid and power constraints in those regions?
- Separate pipeline stages. Distinguish requested capacity and announced projects from contracted work, construction in progress, and completed facilities when evaluating claimed demand.
- Look at revenue quality. Compare one-time equipment or construction revenue with recurring service and replacement work, using the company’s own reporting.
- Account for execution and financing. Consider whether the company can deliver on schedule and fund its capacity, and whether delayed projects would leave it with costs or unused resources.
The clearest beneficiaries are therefore categories with a role in physically delivering facilities and power—not automatically every company whose business has a connection to technology, construction, or electricity. Confirming a company-level winner requires company disclosures that link actual orders or revenue to projects that are moving forward.
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