Many discussions of large artificial intelligence data center investments focus on the expected benefits of job creation. But there also are costs, which might include the lost tax revenue for states which offer tax incentives to data center operators; higher consumer power bills; higher water consumption; stranded utility assets and even far fewer new jobs than anticipated.
In that regard, large AI data centers remind me of large sports stadiums: the argument is that government subsidies will promote economic growth. In fact, such investments mostly shift consumer spending from one category to another, with possible net zero gains.
Study / Source | Main Finding on Net Economic Benefits |
Baade and Dye (1990), Growth & Change | No consistent evidence that stadiums boost metropolitan income or employment. |
Noll & Zimbalist (eds.), Sports, Jobs & Taxes (1997) | Broad survey finds subsidies rarely generate promised jobs or growth; most benefits overstated. |
Coates & Humphreys (2008 review) | Majority of peer-reviewed studies show little to no positive impact on city-wide income/employment. |
Baade and Matheson (2000, 2004) – Super Bowl studies | Event impacts overstated; spending largely shifted from other activities, little net new growth. |
Matheson (2018, J. Policy Analysis & Management) | Citywide gains minimal; limited neighborhood or intangible benefits possible, but not enough to justify heavy subsidies. |
Mercatus Center (2015 working paper) | Finds no evidence subsidies increase growth; in some cases correlate with lower growth. |
Bradbury, Coates, Humphreys (2022/2023 survey) | Comprehensive literature survey: consensus remains that stadium subsidies almost never deliver large net benefits. |
Policy briefs (Journalists’ Resource, CBCNY) | Ex-ante booster studies overstate benefits; opportunity costs of public spending usually higher than stadium returns. |
That is not to deny the need for large AI data centers, simply to point out that the local economic benefits might not be as often touted.
Study/Report | Year | Promised/Expected Jobs | Actual/Direct Jobs | Key Findings |
Upwind Industry Research | 2025 | N/A (hype around economic catalysts) | 1,688 (construction, temporary); 157 (permanent operations) | Construction jobs are short-term and high-volume, but permanent roles are minimal relative to facility size (~$243M economic add during build vs. $32.5M annually ongoing); underscores automation's role in limiting ops staffing. |
University of Michigan / STPP Report ("What Happens When Data Centers Come to Town?") | 2025 | High-paying jobs as primary benefit (per subsidy pitches) | Few permanent positions (not quantified) | Jobs generated are disproportionately low compared to subsidies (e.g., billions in tax breaks); recommends redirecting funds to education or renewables for better ROI; no broad economic uplift observed. |
Wall Street Journal (on Stargate AI Project) | 2025 | Employment "bonanza" (tech/political hype) | ~100 full-time | Lowest jobs per square foot of any major facility (1M sq ft campus); contrasts with 500 jobs at a nearby 286k sq ft cheese plant—exposes AI boom as labor-light post-construction. |
Good Jobs First (analysis of subsidies) - Google Indiana | 2025 | 200 jobs (governor's announcement) | 30 (local tax abatement minimum; no state mandate) | Massive gap between promises and enforceable commitments; subsidies flow without job guarantees, prioritizing corporate gains over local employment. |
Good Jobs First (analysis of subsidies) - Amazon Indiana | 2025 | >1,000 jobs | 400 direct (plus 600 subcontractors) | Subcontractor roles often lack benefits/wage parity; highlights "illusory" totals and long timelines (e.g., spread over years), diluting immediate impact. |
Oxford Economics (for Google Data Centers) | 2018 | N/A (focus on multipliers) | 1,900 direct (national); ~700-1,700 total per state | Positive multiplier (3.3-4.6x, national 5.9x) boosts indirect jobs to 11,000 total, but direct ops roles remain low (~100-200 per campus); early study predates AI surge but shows pattern of limited core employment. |
CBRE Economic Ripple Effects | 2024 | N/A | 3.5M direct-related (up 20% from 2017) | Strong growth but concentrated (e.g., 490 ops + 1,500 construction in NE, 2022); 7.4x multiplier inflates totals, yet critics note it masks low direct density in AI era. |
Then there are the other issues such as higher consumer electricity bills and impact on water usage.
McKinsey estimates suggest that by 2030, data centers globally will require $6.7 trillion in investment for compute operations, of which $5.2 trillion in capital expenditures will support artificial intelligence operations.
If correct, that represents nearly $7 trillion in capital outlays by 2030, and would be an increase of 3.5 times the capacity of data centers from 2025 to 2030 alone.
source: McKinsey
source: McKinsey
Data center power needs in the United States alone are expected to add about 460 terawatt-hours of demand from 2023 to 2030, three times the current level of consumption, McKinsey estimates. At the same time, data center water demand could rise about 170 percent by 2030, according to analysts at WestWater Research.
Those forecasts might be wrong on the high side, but even so, much to all of that capacity will mostly have to be built, somewhere.
And the point is that the benefits and costs will accrue to different participants in the information technology value chain, in different quantities. There will probably be less benefit for local economies, taxpayers and electricity and water ratepayers than often is assumed.
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