Evaluate a data center claim by separating temporary construction work from permanent operating jobs, gross tax receipts from net public benefit, and facility-level environmental impacts from broader grid and watershed effects. For each number, check who reported it, what was measured or modeled, where and when it applies, and which public costs or environmental boundaries were left out.
Start with the claim, not the headline number
A proposal may combine projected construction jobs, future tax receipts, and a renewable-energy commitment into one persuasive headline. Those figures answer different questions and may rely on different sources, periods, and assumptions. Assess each claim separately before deciding whether the project is likely to benefit a community.
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For every material figure, record its source and publisher, publication date and reporting period, geography, units and denominator, whether it is a direct measurement or a model, baseline or counterfactual, project phase, treatment of incentives and public costs, environmental context, uncertainty, and independent verification status. A national estimate can provide context; it cannot substitute for evidence about a particular site.
How many jobs are temporary, and how many last?
Separate construction from operations
Construction employment is temporary: a large buildout may employ thousands of workers, but those positions end as construction winds down. The operating workforce is a different count and is typically much smaller. Colorado Legislative Council Staff’s March 2026 memorandum cites a study estimating about 43 workers per 100 megawatts of capacity. That is a study estimate, not a universal staffing ratio or a replacement for a project’s staffing plan.
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Ask the developer or public agency to report construction-period employment and steady-state operating employment separately, each with a date range and a clear definition. A useful disclosure identifies whether the numbers are headcounts or full-time equivalents, whether contractors and tenant employees are included, and how many workers are expected to be local. Wages, skills, and the duration of positions help show what the count means for residents.
Distinguish direct hires from modeled jobs
“Jobs supported” may refer to direct employees, or to an economic model’s indirect and induced jobs at suppliers and in the wider economy. Request the model, its geography and baseline, how it handles displacement, and its assumptions about local purchasing. Do not add modeled jobs to direct hires as if both were payroll headcount.
Virginia’s Department of Taxation, using data reported to the Virginia Economic Development Partnership (VEDP), lists 1,197 net new jobs in FY2024 and 1,610 in FY2025 among operators participating in the state tax exemption. The report says those operator-reported figures were not independently validated by VEDP or the Department. They are not independently verified jobs caused by the exemption.
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How to assess tax revenue against incentives and public costs
Build a ledger by government and year
“Tax revenue” is not one pot of money. Track state and local revenues separately, by year, and identify the tax base and payer. Depending on the jurisdiction, relevant categories may include real-estate and business-personal-property taxes, sales and use taxes, utility taxes, and income or corporate taxes. Distinguish taxes paid directly by the operator from taxes associated with workers, suppliers, tenants, or modeled economic activity.
Then list each exemption, abatement, or other incentive: its legal duration, estimated value, and actual use where records allow. Subtract documented public costs, which may include roads, water or sewer upgrades, grid connections, and additional public services. If a cost cannot be established from available records, identify it as unquantified rather than assuming it is zero. Compare actual receipts and incentive use with projections instead of treating proposed investment as money already delivered.
Check what “return” means
A return-on-investment figure can refer to public-budget revenue, total regional economic activity, or a private financial return. These are not interchangeable. For a modeled public return, ask about the time horizon, the level of government counted, the assumptions, and whether the calculation includes public infrastructure and service costs.
Virginia’s 2026 Department of Taxation and VEDP report models state and local revenue against incentive costs over five-year periods. It estimates a 1.7 revenue-to-cost ratio and $2.1 billion in cumulative revenue above exemption value across two overlapping five-year periods. Those are model results, not an audited account of realized net revenue. The same report presents operator-reported tax savings of $1.3 billion in FY2024 and $1.9 billion in FY2025; those figures describe savings to operators and corresponding negative revenue impact, not additional public revenue.
A different Virginia finding illustrates why the government level matters. The Joint Legislative Audit and Review Commission, as quoted by Colorado Legislative Council Staff in March 2026, said: “Like most economic development incentives, the data center exemption does not pay for itself when considering just the state portion of the exemption cost and the state return in revenue.” The Commission’s state-only comparison found 48 cents in state revenue per dollar spent on the exemption, compared with a 41-cent average return for Virginia incentives. This state-only result should not be read as a finding about combined state and local revenue.
Compare incentive findings only within their scope
| Jurisdiction and program | Period and approach | Reported results | Program finding |
|---|---|---|---|
| Virginia data center tax exemption | Virginia Department of Taxation and VEDP, 2026; modeled returns over five-year periods | 1.7 modeled revenue-to-cost ratio and $2.1 billion estimated cumulative revenue above exemption value over two overlapping five-year periods | Model estimate; operator job and tax-savings figures are self-reported and not independently validated by the agencies |
| Washington urban-county preference | Washington Joint Legislative Audit and Review Committee, July 2026; review of the preference and its use | Estimated $42.4 million in tax savings from 2023 to 2026; beneficiaries reported 53 family-wage jobs and nearly 300 temporary construction jobs | The auditor found the preference had been used for refurbishment projects only, not new data center construction, and recommended that it expire |
These are different programs, geographies, and methods; neither result predicts what another jurisdiction’s incentive will produce. In particular, Washington’s finding concerns that specific urban-county preference, not every data center tax incentive.
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What to ask about electricity and emissions
Request a facility-specific annual and peak-load forecast, expected commissioning schedule, grid-connection information, and assumptions behind any claimed renewable supply or emissions reduction. A facility’s electricity demand alone does not determine its grid-related emissions: the local generation mix and the hours in which the facility uses power matter.
- Ask whether a renewable-power claim is based on annual matching or on power matched by time and location. An annual purchase claim by itself does not demonstrate that hourly local grid emissions were eliminated.
- Request direct facility emissions separately from emissions associated with grid electricity, and ask whether backup generation is included.
- Check the forecast’s baseline, load assumptions, and timing against utility planning information where available. A projected load is not an observed operating result.
For U.S. context, Colorado Legislative Council Staff’s March 2026 memorandum cites Lawrence Berkeley National Laboratory’s 2024 U.S. Data Center Energy Usage Report. It estimates that U.S. data center electricity consumption grew by about 100 terawatt-hours from 2018 to 2023, while data centers’ share of annual U.S. electricity use rose from 1.9% to 4.4%. The report projected a 2028 share of 6.7% to 12%; that range is a forecast, not a measured 2028 result.
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A water figure is meaningful only with its accounting boundary and local context. Ask for withdrawals and consumptive use separately; the water source (potable, reclaimed, surface water, or groundwater); cooling design; seasonal peak demand; and discharge or reuse information. Establish whether the number covers only on-site use or also water used to generate the facility’s electricity.
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Compare the reported volumes with watershed availability, competing demands, and seasonal or drought constraints. A national total cannot establish whether a particular facility’s water demand is manageable in its location. Colorado Legislative Council Staff notes that proprietary information and a lack of reporting make exact facility-level electricity and water impacts difficult to assess.
The same Colorado memorandum reports a U.S. Department of Energy estimate of 66 billion liters of direct data center water consumption in 2023 and an LBNL estimate of 21.2 billion liters in 2014. Both figures concern direct, on-site water and exclude water consumed upstream to generate electricity. Because they come from different estimates and years, do not treat them as a like-for-like facility comparison or as a complete account of data center water use.
Make digital-versus-physical comparisons fair
If a proposal claims that digital delivery is more environmentally efficient than a physical alternative, define the service and output being compared. Count the full relevant delivery chain on both sides rather than just a data center on one side or a physical product on the other.
UK Department for Energy Security and Net Zero studies compare representative services and include data centers, transmission networks, and user devices in the digital chain. For physical alternatives, they include relevant manufacturing, transport, retail, office delivery, and user devices. The studies cover streaming versus Blu-ray, e-books versus printed books, and AI translation versus human translation, with ten additional use cases in a 2026 follow-up. Their findings vary by use case: digitalization can raise or reduce energy use, so a result for one service should not be generalized to another or treated as a direct estimate of a particular facility’s local impacts.
Quick Recap
A practical checklist for reviewing a proposal
- Break apart the headline. Record each jobs, tax, electricity, emissions, and water claim separately, with its source and reporting period.
- Identify the measure. Mark whether each figure is observed, self-reported, projected, or modeled; record its units, denominator, geography, and baseline.
- Check the project phase. Separate construction work and impacts from expected steady-state operations.
- Reconcile public finances. List revenue by government level and year, then identify incentive value and documented infrastructure or service costs.
- Test environmental boundaries. For electricity, examine load timing and grid context; for water, separate on-site from upstream use and locate the demand in its watershed.
- Check verification and uncertainty. Note whether an agency independently validated a figure, what the source could not measure, and which assumptions drive the result.
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