Stop Calling Them AI Data Centers

Call it an "AI data center" and you've won half the argument before anyone checks a number. AI is about a quarter of what these buildings actually run. The rest is the boring plumbing of your life: the cloud your bank clears transactions on, the servers holding your hospital's records, payroll that has to land Friday, the logistics network that stocked the shelf this morning, the license-renewal portal you cursed at last month, every app on your phone.

A data center is not an AI thing. It's the thing modern civilization runs on, with a fast-growing new tenant on the top floor. And here's the part the campaign can't survive: the opposition to data centers runs on data centers too β€” the petition site, the Zoom town hall, the email blast, the streamed press conference, the AI that drafted the talking points.

~27% AI workloadThe other three floorsPricing β‰  production A fraction of a fractionNot draining the waterLoads can lower ratesKill the subsidy & the moratoriumThe nuclear it's financing
AI's share
~27%
of data-center workload (2027 proj.)
TX growth w/o data centers
~40%
peak demand still climbs by 2031
Consumer surplus
$172B/yr
US gen-AI value, mostly free tools
AI capex
~5% of GDP
> all consumer spending, H1 2025
Honest target
The tariff
a pricing problem, not production
Nuclear signed
~9.8 GW
hyperscaler deals (mostly announced)
Depth 1 β€” Fundamentals

The Other Three Floors Lead

A data center isn't an AI thing. That's the first move in the campaign against them, and it's the one that does all the quiet work. Call it an "AI data center" and you get to take every anxiety attached to AI β€” the job losses, the bubble, the sense that nobody asked for this β€” and aim it at a slab of concrete. But AI is about a quarter of what these buildings run. The other three-quarters is the ordinary digital economy, and it is not optional.

The opposition's own stack is on those floors too. The platforms that activism runs on β€” the petition sites, the video town halls, the advocacy email tools, the streaming, the search, the generative AI now drafting public testimony β€” are all hosted in the very buildings under dispute. The campaign to condemn the infrastructure is itself a tenant of it. You can oppose data centers. You just can't do it without one.

The building, floor by floor

A moratorium proposes condemning all four floors to slow down the one on top. Select a floor to see what's running there.

  • Frontier models, copilots, the tools driving the productivity gains
  • The floor the building is named after β€” and the one everyone's taught to fear
  • Banking & payments: card networks, ACH/wire clearing, fraud detection, ATM/POS auth
  • Communications: email, messaging, video calls, VoIP, the entire mobile-app layer
  • Media & knowledge: news systems, streaming, search, every website
  • Healthcare: EHRs, medical imaging (PACS), lab results, e-prescribing, scheduling
  • Government: tax filing, benefits, DMV/licensing, courts, 911 dispatch, elections
  • Logistics & retail: inventory, freight matching, warehouse automation, point-of-sale
  • Utilities themselves: grid balancing, SCADA, smart-meter data, outage management
  • Petition platforms, town-hall video, advocacy email tools
  • The streamed press conference, the reporter's cloud CMS, the search that surfaced the outrage
  • The generative AI now drafting the public testimony against data centers
What runs on each floor and what breaks if the buildout halts
Floor / sectorWhat's actually running thereWhat breaks if you halt the buildout
Banking & paymentsCard networks, ACH and wire clearing, real-time fraud detection, ATM and point-of-sale authCards decline, payroll doesn't settle, the fraud check protecting your account goes dark
HealthcareElectronic health records, imaging (PACS), lab results, e-prescribing, hospital schedulingDoctors lose your chart, prescriptions stall, imaging can't route
GovernmentTax filing, benefits, DMV/licensing, courts, 911 dispatch, election systemsThe portal you renew your license on; the system that pays out benefits
Logistics & retailInventory, freight matching, warehouse automation, last-mile routing, point-of-saleEmpty shelves, packages stop tracking, "out of stock" everywhere
CommunicationsEmail, messaging, video calls, VoIP, the entire mobile-app layerYour texts, your work calls, your group chat
Utilities themselvesGrid balancing, SCADA, smart-meter data, outage managementThe power company can't run the power company
Media & knowledgeNews content systems, streaming, search, every websiteIncluding the article telling you to fear data centers
The opposition's stackPetition platforms, town-hall video, advocacy email, the AI drafting the testimonyThe campaign against data centers β€” which is hosted in one
AI (the top floor)Frontier models, copilots, the tools driving the productivity gains~27% of the load β€” the minority tenant getting blamed for the whole building
The campaign that runs on the thing it opposes

Every modern political campaign is now a digital campaign, which means it is a data-center campaign. The petition reaches you through a hyperscaler. The outrage clip streams from one. The "ban data centers" mailing list is managed in one. This isn't hypocrisy worth a gotcha β€” it's evidence of the actual claim: this infrastructure is so foundational that even its opposition can't function without it. The thing you're being told to fear is carrying the message that tells you to fear it.

"AI data center" is a framing weapon

Naming the building after its newest, scariest floor lets you import every AI anxiety and aim it at concrete. It's shutting the power plant to slow down crypto. The thing you're afraid of is one floor of the building you want to condemn.

Quick Reference β€” Claims vs. Reality

The cheat-within-the-cheat: the highest-frequency rebuttals, in one scan.

What you'll hearWhat's actually true
"AI data centers are eating the grid."AI is ~27% of data-center workload. The other ~73% is conventional cloud and legacy enterprise β€” the digital economy you already use.
"A moratorium pauses AI."It freezes the physical layer of the entire digital economy to slow down one floor of the building.
"Data centers raise everyone's electric bill."Only where power is tight and a monopoly smears the cost across the base. Where the load pays its own way, they can lower rates.
"Data centers are driving the demand spike."On ERCOT's forecast, even with zero new data centers, Texas peak demand still climbs ~40% (β‰ˆ87β†’121 GW by 2031) on manufacturing, oil & gas, crypto, and electrification.
"AI is spiking your bill."A fraction (AI) of a fraction (data centers) of total demand growth β€” wearing the costume of the whole.
"Data centers are draining and polluting the water."Cooling water is evaporated or recirculated in closed loops, not contaminated. US data centers' direct use is ~0.01% of national water β€” a whole year β‰ˆ a few hours of farm irrigation.
"This is a runaway luxury nobody asked for."The buildout added more to US GDP growth over two quarters than all consumer spending combined.
"Big Tech is getting a free ride."Partly true β€” the tax breaks are indefensible. But that argues for killing the subsidy, not banning the building.

The Workload Mix (What the Dollars Hide)

The confusion between "data center" and "AI" isn't an accident of language β€” it's baked into how the money looks.

The function is mostly plumbing; the dollars skew to AI. By 2027 the workload mix is projected at roughly half conventional cloud, a quarter legacy enterprise, and about 27% AI Goldman Sachs proj., Feb 2025. But the capital spending tells a different story, because an AI rack draws far more power than a conventional one: NVIDIA's current rack-scale systems pull around 130 kW, with next-generation designs targeting 250 kW, against 10–15 kW for a conventional rack β€” and they cost to match. So in dollars, this is unmistakably an AI buildout. In what the buildings do, it's the machinery of daily life with a fast-growing tenant on the top floor.

How to read any data-center statistic

Always ask which lens it's using. In dollars, AI dominates β€” it's where the capex and the power draw concentrate. In function, AI is the minority β€” most of what these buildings do is the ordinary digital economy. A claim that uses the dollar figure to describe the workload (or vice versa) is doing a magic trick. Watch which cup the ball is under.

Depth 2 β€” Working Knowledge

The Newest Tenant Is Also the Most Valuable

The top floor everyone's afraid of happens to be the most valuable thing in the economy right now β€” and most of the value doesn't land where you'd expect.

The value lands on users, not sellers

US consumer surplus from generative AI ran about $172 billion a year by early 2026, up from $112 billion twelve months earlier, with median value per user roughly tripling β€” and most tools are free or close to it Stanford HAI, Apr 2026 Β· modeled. Surplus is the part the seller doesn't capture; it lands on the user.

Jobs & wages went up where AI is heaviest

The industries most exposed to AI posted higher productivity, employment, and wages β€” not lower: 34% vs 24% productivity growth since 2018, 52% vs 36% headcount growth, a 62% AI-skills wage premium PwC 2026 Β· correlational. If AI were the job-destroyer of the narrative, the damage would show first where the tools are used most. It's the opposite.

The Buildout Is Carrying the Economy

The buildout isn't riding the economy. For the moment, it's carrying it.

AI capex has out-driven all consumer spending. Over the first two quarters of 2025, AI-related capital expenditure added more to US GDP growth than all consumer spending combined Renaissance Macro, 2025. It now runs near 5% of GDP β€” a leading driver of US economic growth KKR, 2025–26.

The counterfactual nobody states

Pull the buildout out and you don't land in a world with cheaper power and the same prosperity. You land in the recession it's been papering over. "Pause the data centers" is also "pause the thing currently holding up the economy" β€” said in a calmer voice.

The Cost Grievance Is Real β€” and It's a Pricing Problem

None of which makes the cost complaint fake. It isn't.

Residential power is genuinely up. Prices rose about 42% from March 2021 to March 2026 on EIA monthly data PolitiFact, Jun 2026 β€” and about 27% on EIA's annual-average basis (2019–2024), with more in some regulated markets. Pick either yardstick: the bill went up, and it's a real grievance.

But a pricing problem and a production problem share no solutions. The complaint is about who pays for the grid and how the cost is allocated β€” a pricing question. The moratorium attacks supply β€” a production answer. They don't connect. And the pricing fixes are already arriving:

WhereMechanismWhat it fixes
FERC (federal)Show-cause orders (Jun 2026) directing the six grid operators to make large loads bear the cost of upgrades built to serve them tariffs pendingStops the buildout's grid costs from landing on ordinary ratepayers
Oregon & VirginiaDedicated large-load rate classes β€” Oregon's POWER Act (2025); a Virginia SCC order (Nov 2025, β‰₯85% contracted demand)Separates big-load costs from the residential base
Texas (SB6, 2025)Puts interconnection cost plus curtailment / remote-disconnect duties on loads β‰₯75 MWMakes the data center carry the capacity it triggers
The honest target of your anger is the PUC, not the server hall

Set the tariff right and the grievance shrinks to a line item. You don't halt the most productive infrastructure wave since electrification to spare someone forty dollars a month that a rate class already fixes.

A Fraction of a Fraction

The grievance leans on a conflation that runs the whole way down.

Data centers are a minority of demand growth. AI is a minority of the data centers. On ERCOT's 2025 long-term load forecast, data centers account for roughly 46% of projected load growth through 2031 β€” and even with no new data centers at all, peak demand would still climb about 40% (from ~87 GW to ~121 GW) on manufacturing, oil and gas, crypto, and electrification ERCOT forecast, Apr 2025. So the bill pressure that exists mostly isn't data centers, and the data-center share mostly isn't AI.

Watch the scary number shrink
Total projected demand growth100%
…of which data centers (ERCOT, through 2031)46%
…of which AI (~27% of data-center workload β€” illustrative)~12%

"AI is spiking your bill" β€” let's decompose that claim, one layer at a time.

Fraction of a fraction

"AI is spiking your electric bill" is a fraction of a fraction wearing the costume of the whole. Strip the costume off and you're left with a line item inside a line item β€” being blamed for the entire bill.

"They're Draining and Polluting the Water"

The second-most-common attack after electricity β€” and, like the bill, it's mostly a conflation. Three different things get fused into one scary sentence: water withdrawn vs. water consumed, on-site cooling vs. power-plant cooling, and national totals vs. local stress.

"Pollution" is the wrong word. Cooling water isn't chemically contaminated and dumped. It is evaporated in cooling towers, withdrawn and returned, or recirculated in a sealed closed loop. Evaporated water doesn't vanish β€” it returns to the hydrologic cycle as rain. Of all the water claims, "polluting our water" is the easiest to retire.

The national numbers are a rounding error. US data centers directly consumed about 66 billion liters β€” roughly 17 billion gallons β€” of cooling water in 2023 LBNL, 2023. That's on the order of 0.01–0.02% of US water withdrawals. For scale: American agriculture withdraws about 118 billion gallons per day for irrigation β€” so data centers' entire year of direct water use is a few hours of farm watering.

Where US water goes, by sector share of withdrawals
UseShare of US water
Thermoelectric power generation~41% of withdrawals
Irrigation (agriculture)~42% of freshwater
Public water supply~12%
Data centers (direct cooling)~0.01–0.02%

Sector shares: USGS national water-use survey (withdrawals). Data-center direct use: LBNL (2023). Power and farming together are ~80% of US water; data centers are a rounding error beside them.

Withdrawal vs. consumption β€” the distinction the headlines drop

Withdrawal is water taken from a source; most of it is returned. Consumption is the part that evaporates and doesn't come straight back. Thermoelectric power withdraws ~41% of US water but consumes only a sliver of it. A statistic that quotes a big withdrawal number as if it were all "used up" is doing the same magic trick as the electricity bill β€” counting the gross to imply the net.

Most "AI water" is really power-plant water. A data center's indirect water footprint β€” the cooling at the power stations feeding it β€” runs roughly 12Γ— its on-site cooling LBNL, 2023. Which means the water story mostly tracks the grid, not the server hall: shift that power toward nuclear, wind, and solar β€” which consume little to no operating water β€” plus efficiency, and the larger share shrinks. The clean-firm-power buildout covered below is also a water story.

The cooling is going closed-loop and recycled

Hyperscaler water efficiency (WUE) now runs about 0.12–0.30 liters per kWh, a fraction of older designs. Microsoft's 2024 data-center design uses sealed, chip-level liquid cooling with zero evaporative loss β€” avoiding more than 125 million liters per facility per year. AWS reports dozens of sites running on 100% reclaimed (non-potable) water. New AI builds trend toward closed-loop and immersion cooling, where the water is a sealed coolant, not something consumed company reports, 2024–25. One honest tradeoff: closed-loop and air cooling can raise energy use, which nudges the indirect footprint up β€” so it's efficiency, not magic.

"ChatGPT drinks a bottle of water per question" β€” real paper, mangled stat

The viral line traces to a legitimate peer-reviewed study (Ren et al., "Making AI Less 'Thirsty'"). But it actually estimated that a 500 mL bottle covers roughly 10–50 medium responses β€” not one β€” and is highly location- and season-dependent. The famous "700,000 liters to train GPT-3" is the on-site slice of a ~5.4-million-liter total. Cite the concept; don't repeat the bumper-sticker version, which overstates the original several-fold Ren et al., 2023–25.

Where the concern is real: local, not national

The honest concession: tiny nationally doesn't mean harmless everywhere. Siting an evaporative-cooled facility in a drought-stressed region, drawing on potable municipal supply instead of reclaimed water, or sending concentrated "blowdown" to a small wastewater plant β€” those are real, local problems. And the fix is the same shape as the electricity answer: site it where water is available, require reclaimed or closed-loop cooling, and make the load carry its own impact. That's a permitting-and-design problem, not a reason to ban the building.

Depth 3 β€” Edge & Advanced

Data Centers Can Lower Rates

Here's what should retire "data centers raise prices" as a flat claim: they don't, everywhere.

Where load pays its own way, big customers spread fixed costs. In inflation-adjusted terms, North Dakota's residential rates fell between 2019 and 2024 β€” one of the largest real declines in the country Lawrence Berkeley Nat'l Lab β€” even as the nominal rate ticked up from 10.3Β’ to 11.5Β’/kWh, because new large loads spread the grid's fixed costs across more usage. Oncor told Texas legislators that a single Dallas-area project would throw off $160 million in revenue against $143 million in cost β€” a net gain for everyone else on the system, as long as the load pays for the capacity it triggers Oncor testimony, Apr 2026.

When big loads push rates UP vs. DOWN

Where power is plentiful and the customer carries its own weight, big loads push rates down by spreading fixed costs. Where power is tight and a regulated monopoly smears the cost across the base, they push up. Same building either way. The variable is the rate-and-energy policy wrapped around it β€” which means the honest target of your anger is your public utility commission, not the server hall down the road.

The Patterns Underneath

The housing shortage with cooling towers

A local veto over construction. The cost landing on the neighbors. The benefit diffusing across the country. The whole thing dressed up as protecting the character of the place. We've watched that movie for forty years with housing β€” the same zoning machinery that made it illegal to build homes where people want to live is now being swung at the infrastructure the modern economy runs on. We know how it ends.

Kill the subsidy and the moratorium β€” in the same motion. One concession, and it cuts against the companies: the tax breaks are indefensible. Texas alone is forgoing at least $1.3 billion this fiscal year β€” and a projected $3 billion-plus over the 2027–2028 biennium β€” on its data-center sales-tax exemption alone, separate from any local incentives TX Comptroller, 2025. If a project already pencils out on cheap land and cheap power β€” which is exactly why these things cluster in Texas β€” it doesn't need a tax holiday on top. Make them pay market price for power and full freight on taxes, like any other industrial load. That isn't carrying water for Big Tech. It's refusing to socialize either the costs or the gains.

The buildout is financing the nuclear revival fifty years of energy politics couldn't deliver. Every major hyperscaler has now signed nuclear. Customers with 24/7 baseload needs and the balance sheets to underwrite first-of-a-kind reactors are the best thing to happen to American nuclear in a generation.

Hyperscaler nuclear deals
PlayerProject / siteScaleStatus
MicrosoftThree Mile Island Unit 1 (Crane Clean Energy Center) restart~835 MW20-year PPA; restart targeted 2028
AmazonTalen Susquehanna~1.9 GWFront-of-meter PPA (after FERC rejected the original co-location, 2024–25)
AmazonX-energy Xe-100 SMRs (Energy Northwest)up to ~960 MWDevelopment; led ~$500M round
GoogleKairos Power SMRs~500 MWDevelopment
MetaOklo Aurora SMRs~1.2 GWDevelopment
Industry totalAnnounced hyperscaler + data-center nuclear deals (13)~9.8 GWMostly announced/contracted near-zero operating

The strategic floor. The federal push to speed grid connections was framed explicitly as a China race: Energy Secretary Chris Wright urged FERC to help the US "better compete with China for superiority in the fast-growing AI sector," and in June 2026 FERC unanimously directed grid operators to connect large AI loads AP, Jun 2026. Compute is the binding constraint on frontier models, and frontier AI is the strategic technology of the next two decades the way oil was for the last hundred. "Pause the data centers" is "cede the lead," said in a calmer voice. That's a real floor of the building too β€” the most consequential one β€” even if it isn't most of the square footage.

The irony, twice over

The movement that strangled nuclear for decades, then recoiled when gas turbines filled the gap, is now trying to block the load that's financing the clean firm power it says it wants.

Common Mistakes & Anti-Patterns

Each is a trap on the left, the correction on the right.

MistakeTreating "data center" and "AI" as synonyms
CorrectionAI is ~27% of the workload; the rest is the digital economy you already depend on
MistakeReading capex share as workload share
CorrectionDollars skew to AI (~130 kW racks); function stays mostly conventional cloud
MistakeBlaming data centers for the whole demand curve
CorrectionEven with zero new data centers, ERCOT projects Texas peak demand still climbs ~40% (β‰ˆ87β†’121 GW by 2031)
MistakeAssuming big loads always raise rates
CorrectionWhere the load pays its own way, it spreads fixed costs and lowers them
MistakeConflating a pricing problem with a production problem
CorrectionRate design fixes the bill; a moratorium just freezes supply against rising demand
MistakeThinking a moratorium "pauses AI"
CorrectionIt freezes the physical layer of the entire digital economy
MistakeConfusing the subsidy fight with the moratorium
CorrectionKilling the tax break is right; banning the building is not β€” do the first, not the second
MistakeCalling data-center cooling water "pollution"
CorrectionIt's evaporated or closed-loop recirculated, not contaminated; most of the footprint is power-plant water that shrinks with clean energy

The Honest Position

The position was never pro-data-center or anti. It's that the thing being built runs the economy we already have, is financing the one we're about to get, and delivers more value to more people than nearly anything else going.

The people selling you the pause aren't protecting your bill. They're using it β€” and they're reaching you through the very infrastructure they're telling you to fear.

Sources & Methodology

Verified 2026-06-24 against primary sources where reachable. Forecasts are labeled as projections with their vintage. Figures that drift quickly β€” consumer surplus, GDP share, electricity prices, the ERCOT and tax-exemption forecasts β€” are dated inline.

  1. Workload mix (27% AI by 2027): Goldman Sachs Research, "AI to drive 165% increase in data center power demand by 2030," Feb 4, 2025. Projection.
  2. Rack power density (~130 kW AI today, 250 kW roadmap; 10–15 kW conventional): NVIDIA technical blog (GB200/GB300 NVL72); Schneider Electric, "The 1 MW AI rack is coming," Oct 2025; Uptime Institute Global Data Center Survey 2024.
  3. Consumer surplus ($172B / $112B; value-per-user tripled): Stanford HAI, 2026 AI Index Report, Ch. 4 (Economy), Apr 2026. Modeled willingness-to-pay estimate.
  4. AI-exposed industries (productivity / employment / wages): PwC, 2026 Global AI Jobs Barometer. Correlational.
  5. AI capex > consumer spending (H1 2025): Renaissance Macro Research (Neil Dutta), 2025, via DataCenterDynamics, Aug 6, 2025.
  6. ~5% of GDP: KKR (Henry McVey), "Beyond the Bubble: Why AI Infrastructure Will Compound," 2025–26.
  7. Residential prices (+42% Mar 2021–Mar 2026 monthly / +27% annual 2019–24): PolitiFact fact-check, Jun 12, 2026; U.S. EIA Electric Power Monthly.
  8. FERC large-load cost recovery: FERC show-cause orders, Docket RM26-4, Jun 18, 2026. Tariffs pending.
  9. Rate classes: Oregon POWER Act (2025); Virginia SCC order, Nov 2025.
  10. Texas SB6 (β‰₯75 MW): Texas SB 6, 89th Legislature, signed Jun 20, 2025.
  11. ERCOT load growth (46% data centers; ~40% / β‰ˆ121 GW ex-data-centers by 2031): ERCOT 2025 Long-Term Load Forecast, Apr 2025; data-center share derived via electricityplans.com. Projection.
  12. North Dakota real-dollar rate decline: Lawrence Berkeley National Laboratory; nominal prices per U.S. EIA. Inflation-adjusted.
  13. Oncor ($160M vs $143M): Brian Lloyd testimony, Texas House State Affairs Committee, Apr 2026. Project forecast.
  14. Texas data-center sales-tax exemption ($1.3B/yr; $3B+/biennium): Texas Comptroller, Tax Exemptions & Tax Incidence, 2025.
  15. Hyperscaler nuclear (~9.8 GW; TMI; Susquehanna; X-energy / Kairos / Oklo): SMR Intel deal tracker (Jun 2026); Constellation Energy (Sep 2024); Utility Dive (Jun 2025). Mostly announced/contracted, near-zero operating.
  16. China-competitiveness framing: Energy Secretary Chris Wright / FERC action, Associated Press, Jun 18, 2026.
  17. Data-center water (direct ~66B L in 2023; indirect β‰ˆ12Γ— direct; WUE): Lawrence Berkeley National Laboratory, "2024 United States Data Center Energy Usage Report," Dec 2024. Modeled.
  18. US water-use shares (irrigation / thermoelectric / public supply; withdrawal vs. consumption): USGS, "Estimated Use of Water in the United States" (latest national survey). Withdrawals.
  19. Closed-loop / zero-evaporation cooling & reclaimed water (WUE 0.12–0.30 L/kWh): Microsoft "zero-water" data-center design announcement, Dec 2024; Amazon/AWS water-use disclosures, 2025. Company reports; some figures forward-looking.
  20. "500 mL per 10–50 responses" / GPT-3 training water: Li, Yang, Islam & Ren, "Making AI Less 'Thirsty'" (arXiv:2304.03271), 2023–25. Estimated; widely misquoted.