New evidence on data center employment effects | Brookings

The data center debate

On March 25, 2026, Senator Bernie Sanders and Representative Alexandria Ocasio-Cortez introduced the AI Data Center Moratorium Act, a bill that would pause all new large-scale AI data center construction until Congress passes legislation addressing AI safety, worker protections, and environmental standards. The bill reflects a sharp turn in the national conversation. Five years ago, data centers were ribbon-cutting events. Today, more than 100 local communities have enacted moratoriums, more than 300 state data-center bills were filed in the first six weeks of 2026, and several states that once competed to offer the largest tax incentives—Virginia, Georgia, and Oklahoma—are now reconsidering those programs entirely.

The backlash is not hard to understand. Data centers consume enormous amounts of electricity and water. In the PJM grid region, which serves 65 million people across 13 states, power supply costs jumped from $2.2 billion to $14.7 billion in a single year, with data centers accounting for nearly two-thirds of the increase. Residential electricity rates nationally rose about 32% between July 2020 and July 2025. Communities near proposed facilities face noise, strained infrastructure, and the loss of farmland, costs that are immediate and visible.

The trade-offs

Proponents counter that data centers bring high-paying jobs, construction activity, and tax revenue. A single hyperscale campus, such as those built by Amazon, Google, and Microsoft, can become one of a county’s largest taxpayers. Supporters also argue that the United States cannot cede AI infrastructure to geopolitical competitors, and that pausing construction amounts to surrendering technological leadership.

Critics respond that these benefits are overstated, in part because data centers are among the least labor-intensive structures in the economy. For instance, large data center projects often promise only dozens to a few hundred permanent workers while the associated construction jobs are temporary. And the tax incentives are costly: in Virginia alone, the data-center sales-tax exemption cost an estimated $1.6 billion in fiscal year 2025. These incentives may simply be subsidizing investments that would have happened anyway.

What the evidence says about jobs

What has been largely missing from this debate is rigorous evidence on the economic effects that data centers actually produce. To this end, we assembled a dataset of approximately 770 U.S. data center facilities linked to county-level employment and wage data from the Bureau of Labor Statistics (2003-2024).¹ The dataset covers 93 counties that received their first large data center between 2008 and 2024 and approximately 3,000 control counties that never received one.

We estimate the impact of the data centers on jobs using the synthetic control method (SCM), which constructs a counterfactual for each treated county by finding a weighted combination of control counties that matches the treated county’s pretreatment employment trajectory. This approach is important because before the facilities arrived, data center counties were growing faster than other counties. As a result, a naive comparison of treated and control counties, as some industry-sponsored reports have done, would overstate the impact on jobs by a factor of three.

We find that data centers do create local jobs, with caveats (Figure 1). Counties that receive their first large data center see total private employment rise by 4%-5% over five to six years. Construction employment jumps 11%, and information sector employment—IT services, telecommunications, software—grows by 22%. Wages rise by 3%-4% for both existing workers and new hires, without a significant increase in home prices. At a typical treated county with 98,000 workers, these estimates imply roughly 2,000 to 4,000 additional jobs after six years, depending on facility type.

Not all data centers are the same

The most policy-relevant finding is that the employment effects depend on facility type. We classify facilities into two types: hyperscale (built by cloud and AI companies—Amazon, Google, Microsoft, Meta—to run their own workloads) and colocation (built by data center landlords—Equinix, Digital Realty, CyrusOne—who lease space to remote tenants). This distinction, absent from prior research and current policy, turns out to be critical.

Hyperscale counties see large information sector gains while colocation counties do not (Figure 2). A hyperscale campus creates demand for local fiber installers, network operations centers, managed service providers, and IT contractors, firms that set up nearby to serve the campus. A colocation facility leases space to remote tenants who may have no local operational presence. A bank in New York renting a server cage in Dallas doesn’t hire IT staff in Dallas.

Importantly, the largest information sector gains don’t come from a single facility. Specifically, counties with a single data center see modest total employment effects but no significant information sector growth. However, counties with four or more facilities see an impressive 23% increase in information sector employment, indicating that the technology ecosystem that drives these gains takes time and scale to develop.

Takeaways

Communities have legitimate concerns about energy costs, water use, and environmental impact, and those concerns deserve evidence-based answers of their own. But the labor market dimension of this debate has been conducted largely without data, and our findings suggest several things policymakers should know:

1. Data centers do create local jobs, though fewer than industry advocates claim. Naive estimates that fail to account for preexisting growth trends overstate the effect by a factor of three.
2. Not all data centers are equal. The technology ecosystem effects that distinguish data centers from warehouses are concentrated in hyperscale investment. Colocation facilities generate construction activity but not the IT agglomeration that makes data centers a distinctive economic development tool.
3. Clusters generate the largest effects. Single facilities produce modest employment gains. The information sector benefits require multiple facilities in the same area.
4. Workers see modest real gains. Wages rise 3%-4% for both existing workers and new hires, with no significant effect on home prices.
5. Incentives may be poorly targeted. Overall, state incentives are small relative to private investment. In hyperscale counties, incentives represent about 2% of total construction investment. Location decisions for these facilities are driven by power availability, land, and fiber infrastructure, not by tax breaks. In colocation counties, incentives represent a much larger share of total investment (62%), meaning subsidies may matter more for precisely the facilities that generate the smallest employment benefits.

The data center debate is moving fast, but the evidence base has not kept pace. Whether the question is a federal moratorium, a state incentive program, or a local zoning decision, policymakers will require rigorous evidence in order to make these types of decisions.