【摩根大通】长远视角：人工智能、能源与气候问答

EuropeEquityResearch

08June2026

TheLongView

Q&AonAI,EnergyandClimate

OnMay26th,wehostedThomasSpencer,co-authoroftheIEA’sKeyQuestionsonEnergy&AI.InthisQ&A,weaddresscrucialaspectsoftheIEA’swork:

EMEASustainableInvestingResearch

HugoDubourgAC

(33-1)40154471

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Jean-XavierHecker

(33-1)40154472

jean-xavier.hecker@

NoemiedelaGorce,CFA

(44-20)7134-4229

noemie.delagorce@

J.P.MorganSecuritiesplc

•HowWillDataCentres’(DC)EnergyDemandEvolve?IntheIEA’sBaseCase,DCdoubletheirshareofglobalelectricityfrom1.5%to3%by2030(485→950TWh).TheUSabsorbs45%ofincrementaldemand,followedbyotheradvancedeconomiesandChina.Thepathto2030iscappedontheupsidebyphysicalbottlenecks(memory,turbines)andsupportedbycapex/adoptionmomentum.CumulativeDCcapexof$3.9trnthrough2030includes$780bnofenergy-relatedspend,withrenewables(360TWh)andgas(340TWh)leadingnewgeneration.Beyond2030,scenariosdivergematerially.

•HowMuchComputeDoesAINeed?“Unprecedented”efficiencygainsareoutpacedbyworkloadintensity.Per-queryenergyhasfallenanorderofmagnitude,buttheJevonsParadoxisinfullforce.AgenticReasoningtasksconsume~50Whvs.~0.3Whforsimpletextqueries—pointingtotheimportanceofnewinferenceworkloadsinfuturedemand.

Contents

ExecutiveSummary

2

HowWillDataCentres’EnergyDemandEvolve?

5

HowMuchComputeDoesAINeed?

10

WhereCanAIBoostEnergyEfficiency?

16

WillAIBoostEnergyInnovation?

30

WillAIhaveanetpositiveenergy&climate

footprint?

34

WillAINegativelyImpactAffordabilityThrough

HigherElectricityPrices?

41

WhatShouldInvestorEngagementFocusOn?

44

WhoaretheEMEATopPicks?

51

•WhereCanAIBoostEnergyEfficiency?ExistingAIusecasesinindustry,energy,transportandbuildingscoulddeliversavingsequalto3%ofglobalfinalenergyconsumptionby2035.Wedetailcorporateexamplesacrossthefourindustries.

•WillAIBoostEnergyInnovation?AlphaFold’s2024NobelPrizesuggestsAIwillfosterbreakthroughs,andmosttechnologiesneededforNetZerohaveyettobeinvented.Batteries,catalystsforsyntheticfuels,CO₂capturematerials,andcementarefourkeyareasofAI-ledinnovationpotential.

•WillAIHaveaNetPositiveEnergyandClimateFootprint?IEAandSternprojectemissionreductionsexceedingDCenergydemand,butneitheraccountsforreboundeffects.NGOswarnofgreenwashing;arecentstudyonAI-contrailsshowstechnologyisjustonepartoftheequation—AIalonewillnotsolveclimateaction.

•WillAINegativelyImpactAffordability?Concernsaroundthepriceofelectricityaregrowing,howeverimpactseffectivelydependonlocalconditions.

•WillLocalOppositionBlockDatacentres?98localmoratoriumsandsouringpublicsentimenthavebecomeamaterial,andacceleratingriskthatisalreadyreshapingprojectsiting,timelines,costs,andeconomics.

•WhatShouldInvestorsEngageUpon?ThecredibilityofBigTechcleanenergycommitments,theGHGProtocolScope2overhaul(hourlyvs.annualmatching),andITU-TL.1801disclosurestandardsarekeytopicsforsustainableinvestors.

•WhoaretheEMEATopPicks?CapGoodsandITHardwareOW-ratedcompaniesarewellpositioned:Legrand,SchneiderElectric,Siemens,SiemensEnergy,Prysmian;ASML,ASMInternational,InfineonandNokia.

Seepage65foranalystcertificationandimportantdisclosures,includingnon.USanalystdisclosures.

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ExecutiveSummary

HowWillDataCentres'EnergyDemandEvolve?

Datacentresaccountedforapproximately1.5%ofglobalelectricityconsumption

in2025,withdemandgrowingatfourtimestherateofbroaderelectricity

consumptionsince2017.UndertheIEABaseCase,datacentreelectricityconsumptionisprojectedtoroughlydoublefromaround485TWhin2025to950TWhby2030,

representingjustunder10%ofglobalelectricitydemandgrowthovertheperiod.TheUnitedStatesisexpectedtoaccountfor45%ofthisincrementaldemand,followedbyotheradvancedeconomies(19%)andChina(6–7%).

Fourscenarios—Base,Lift-Off,Headwinds,andHighEfficiency—converge

through2030duetobindingphysicalconstraints,includingIThardwaresupply

(notablymemory),gridconnectionwaittimesof4–5years,gasturbineavailability,

transformerleadtimes,andskilledlabourshortages.Cumulativedatacentrecapexisestimatedat$3.9trillionbetween2026and2030,ofwhichroughly20%(~$780bn)isenergy-related.Renewablesareexpectedtocontributethelargestshareofnew

generation(~360TWhby2030),withgasaclosesecond(~340TWh),particularlyintheUS.OnsitebatterystorageandUPScapacityareprojectedtogrowfrom~5GWtodayto20–25GWby2030.

HowMuchComputeDoesAINeed?

AIenergyefficiencygainsareprogressingatapacedescribedasunprecedentedinenergyhistory.Per-queryenergyconsumptionhasfallenbyanorderofmagnitude

annuallyinrecentyears:Google'smedianGeminitextpromptconsumes0.24Wh,

OpenAI'saverageChatGPTquery0.34Wh—broadlycomparabletoa2011Googlesearch(0.3Wh).Hardwareperformanceperwatthasimproved30–40%annuallyoverthepastdecade,andbest-in-classhyperscalefacilitiesnowachievePUEratiosof1.1–1.2versus1.5–1.7forolderfacilities.TheIEAestimatesthatreplacingallGoogle

searchqueriesbyGenAItextquerieswouldonlyrepresent1%ofcurrentDC.

Thesegainsarebeingoutpacedbyashifttowardfarmoreenergy-intensive

workloads.Whilesimpletextqueriesconsume0.05–0.3Wh,reasoningqueries

consume~1Wh,andagentictaskswithreasoningenabledcanconsume~50Whpertask.ThisJevonsparadoxdynamic—wherebyefficiencyimprovementsdrive

broaderadoptionandmoresophisticatedusecases—explainswhyaggregateAIelectricityconsumptioncontinuestoclimbdespiteper-taskefficiencygains.

TheIEAflagsbutdoesnotdeeplyexplorewhichworkloadswillfillits2030AI

datacenterprojections;ourAI-assistedthoughtexperimentfindsthatper-query

economics(text,image,search)explainlessthan5%ofprojectedinferencedemand,withfourhigh-intensityworkloadclasses—agentic,video/multimodal,ambient

assistants,andembeddedenterpriseinference—accountingfor75–85%ofthebuild-outandquantifyingtheoptimismbakedintotheIEA'sbasecase.

WillAIBoostEnergyEfficiency?

Thewidespreadadoptionofwell-documentedAIapplicationscoulddeliverenergysavingsequivalenttoapproximately3%ofglobalfinalenergyconsumptionby

2035.Sector-levelpotentialincludes:oil&gas(methaneleakdetection,~10%cost

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reductioninoilfielddevelopment);power(upto$110bninannualsavingsby2035,30–50%reductioninoutagedurations,~3%efficiencygainsatfossilplants);industry(8%energysavingsinlightindustryby2035);transport(energysavingsofupto20%,

equivalentto120millioncars);andbuildings(~300TWhofelectricitysavingsby2035,equivalenttoAustraliaandNewZealandcombined).

NotablecorporatedeploymentsincludeSaudiAramco($2bnTRVfromAIin2024),Equinor($130mdirectAIvaluein2025),Veolia(90%N₂Oreductionacross120+

wastewaterplants),E.ON(70AIusecases,30,000smartsubstations),HeidelbergMaterials(€380msavedin2025),andSchneiderElectric(~10%electricitysavingsacross600+Swedishschools).

Theseelementswilllikelyrepresentmaterialdriversofenergy-andcost-efficiencygainsforenergy-intensiveindustries.Wearethereforeoptimisticabouttheiradoptionwhereverthebenefitscanbecaptured/monetizedbycompaniesexposedtonewAI

solutions.Inturn,theadoptionofthesetechnologieswilllikelybenefitelectrificationandsolutionprovidersincludingCapGoodsandITHardwarecompaniesmentionedinthisreport.

WillAIBoostEnergyInnovation?

ThereismuchdiscussionaroundthepotentialforAItoboostinnovation.The2024NobelPrizeinChemistrywasawardedtoDavidBaker,DemisHassabisandJohn

Jumper.Thetwolatter,GoogleDeepmindresearchers,contributedtothedevelopmentofAlphaFold2,anAImodeldesignedtosolvea50-year-oldproblem:predicting

proteins’complexstructures.

AI'spotentialtoaccelerateinnovationishighestwherefourconditionsalign:high-complexitydesignspaces,strongstructureddatasets,straightforwardverification,andreceptivemarketswithdrop-inpathways.

Batteries,catalystsforsyntheticfuels,CO2capturematerials,andcementrepresentfourkeyareasofAI-ledinnovationpotential,thoughcommercialscalingremains

constrainedbyindustrialqualification,capitalcosts,andregulatoryframeworksratherthandiscoveryitself.

WillAIHaveaNetPositiveEnergy&ClimateFootprint?

UndertheIEA'sWidespreadAdoptionCase,AI-enabledemissionsreductionsinend-usesectorscouldexceeddatacentreemissionsby2035.However,thispathwayisnotguaranteed:itassumesthatsector-widebarriers(limiteddata,poor

interoperability)arelargelyovercomeandexplicitlyexcludesreboundeffects.

AmaterialdistinctionexistsbetweentraditionalAIandgenerativeAI.Schneider

ElectricanalysisindicatesgenerativeAIconsumes6–14xmoreenergythantraditional

AI.Of154documentedclimate-benefitclaims,97%relatetotraditionalAIandonly3%toconsumergenerativesystems,withnoverifiablesubstantialemissionsreductions

attributabletogenerativeAI.

Thecontrailscasestudyillustratesthattechnologicalsolutionsaloneare

insufficient:aGoogle–AmericanAirlinestrialachieveda62%reductionincontrail

formationonsuccessfullyexecutedflights,butonly11.6%acrossalleligibleflightsdue

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tooperationaladoptionbarriers.

WillAINegativelyImpactAffordability?

TheIEAfindsnosystematicrelationshipbetweenloadgrowthandretailelectricitypricesacrossmajormarketsfrom2019–2024—butnationalaveragescanmasksharplocalisedpressuresindatacentreclusters.

Intheshortterm(0–3years),pricepressureisconcentrated,notuniversal.In

constrainedmarkets,wholesaletighteningandtransmissioncongestioncandrivepriceshigher.Long-termoutcomesdivergebasedonwhetherjurisdictionspursueintegrated,anticipatorygrowth(neutraltodownwardpressure)orreactivegrowthin

constrainedsystems(sustainedupwardpressure).Across-cuttingconcernisthatco-locationandonsitegenerationcanshiftcostsontootherconsumers.

Threepolicyleversdeterminethepath:costallocationandtariffdesign(e.g.,

Virginia'snewrateclassforlargedatacentreloads,effectiveJanuary2027),thepaceofgenerationandtransmissionbuild-out,andtheflexibilityprofileofthedatacentrefleet—wheretheIEAestimatesthatflexibilityforjust0.1–1%ofhoursperyearwouldsufficetointegrateallprojectednewcapacitythrough2035.

Therightquestionisthereforenot"aredatacentresraisingprices?"but"which

jurisdictionsarebuildingtheinstitutionstopreventdatacentregrowthfromraisingconsumerprices?"

WillLocalOppositionBlockDatacentres?

LocaloppositionwillnotstoptheAIdatacentresbuildout,butithasbecomea

material,andacceleratingriskthatisalreadyreshapingprojectsiting,timelines,

costs,andtaxeconomics.Investorsshouldnowtreatcommunityandregulatoryriskasafirst-ordervariable—comparabletopoweravailabilityandsupplychainconstraints.

WhatShouldInvestorEngagementFocusOn?

TheelectricityintensityofBigTechrevenueshasnearlydoubledoverrecentyears,raisingquestionsaboutthecredibilityofcleanenergycommitments.Among

hyperscalers,onlyAlphabetandMicrosofthavecommittedto24/7carbon-freeenergyby2030,thoughMicrosoftisreportedlyreconsideringitstarget.

TheproposedGHGProtocolScope2overhaul—shiftingfromannualtohourly,location-matchedaccounting—hassplitBigTech,withMeta,Amazon,and

Salesforcebackingan"impactaccounting"approachversusAlphabetandMicrosoftsupportinghourlymatching.IEAanalysisindicates50–80%hourlymatchingiscost-competitivewithgasturbinesintheUS,withcostpremiarisingsharplyonlyas

procurementnearsfull24/7.

ThenewITU-TL.1801standardforassessingAIenvironmentalimpactacrossfourlife-cyclestagesprovidesaframeworkforinvestorstoengageonimproveddisclosure.

EMEATopPicks

Intheregion,webelieveCapGoodsandITHardwarearebest-placedonthetheme,withbothsectorsratedOWbyJ.P.MorganEquityStrategy.CapGoodsOWnamesinclude

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Legrand(30%datacentreexposure),SchneiderElectric(26%datacentreexposure),Siemens,SiemensEnergy,andPrysmian.ITHardwareOWnamesincludeASML,ASMInternational,Infineon,andNokia.

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HowWillDataCentres’EnergyDemandEvolve?

AdoublingDCshareofelectricitydemandby2030

Datacentresaccountedforabout1.5%ofglobalelectricityconsumptionin2025,

withdemandgrowingatfourtimestherateofbroaderelectricityconsumption

since2017.Whileroughly15%ofcurrentdatacentredemandisattributabletoAI(withuncertainty),theIEApinshalfthenear‑termgrowthinserverstoAI‑linkedhardware

andwarnsthismaystillunderestimateAI’sshareofgrowth.

Initslatestupdate,theIEA’sBaseCaseseesdatacentreelectricityconsumption

doublingfromaround485TWhin2025toaround950TWhin2030.Thatputsdatacentresataroundone-tenthofglobalelectricitydemandgrowthto2030,thefourth

biggestdriverofdemandbehindindustry,EVs,appliancesandspacecooling.However,thisishighlyregionspecificanddatacentrescouldaccountforabout45%ofUS

electricitydemandgrowthto2030.Physicalconstraints(DCbuild,gridconnection,availabilityofservers,memory,gasturbines)explaintheIEA’sunchangedoutlookto2030.

FourScenarios:FromHeadwindstoLift-Off

TheIEA'smodellingapproachisbottom-upandgroundedinthephysical

shipmentsofservers—thecoreelectricity-consumingequipmentwithindata

centres.InputstothemodelcomefromIT-sectorprojectionsforserver

manufacturingandshipments,bothhistoricalandforward-lookingoverafive-yearhorizon.Acentralvariableistheannualshipmentofaccelerators(GPUs,TPUs,

andsimilarspecialisedchips),whichdrivethehighpowerintensityofAI-focusedfacilities.Layeredontopofthesephysicalinputsareassumptionsaboututilisationrates,idlepower,andpowerusageeffectiveness(PUE),whichtogethertranslateITcapacityintototalfacilityelectricityconsumption.

Thefourcasesdifferintheirassumptionsabouttheseunderlyingdrivers.TheBaseCaseprovidesthecentralprojectionandreflectscurrenttrendsinAIdevelopment,investment,andthepersistenceofsupply-chainbottlenecks.TheLift-Off

CaseassumesstrongerAIadoption,surgingdigitalservicesdemand,andeffectiveresolutionofbottlenecksthroughexpandedchipandenergy-equipment

manufacturingcapacity,alongsidepolicyprogressthateasesgridconnectionwaittimes.TheHeadwindsCaseassumesslowerdemandgrowth,AImonetisation

challengesthatdampeninvestment,andpersistentlocalandelectricity-supply

constraints;broadermacroeconomicfactorssuchashigherinterestratesortrade

restrictionscouldpushoutcomesinthisdirection.Finally,theHighEfficiency

CaseholdsAIanddigitalservicesdemandonthesametrajectoryastheBaseCasebutassumesthataggressiveefficiencystrategies—modelrightsizing,continued

model-efficiencygains,andapartialshifttoedgecomputing—counterbalancedemandgrowth.

IntheupdatedBaseCase,datacentreelectricityconsumptiongrowsfromaround485TWhin2025toroughly950TWhby2030,accountingforjustunder10%ofglobalelectricitydemandgrowthovertheperiod.Near-termphysicalandfinancialfrictionsmeanthattheLift-OffCasetracksclosertotheBaseCaseintheshort

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term,whiletheHeadwindsandHighEfficiencyCasesdivergelaterthantheydidintheIEA's2025report,reflectingstrongnear-termmomentumininvestmentandtherapiduptakeofenergy-intensiveAImodessuchasagenticAI.Beyond2030,

uncertaintywidensmateriallyinbothdirections.

Figure1:DatacentredemandgrowthhasbeensignificantandlargelydrivenbytheUS…

Shareofelectricitydemand(%)

4%

3%

2%

1%

0%

20052010201520202024

USAChinaEurope

Source:IEA(2025),EnergyandAI,IEA,Paris

/reports/energy-and-ai

,Licence:CCBY4.0

Figure2:TheIEApointstostronggrowthtotheendofthedecade-cappedbyphysicalconstraints-withabroaderrangeof2035

estimates

GlobalAIdatacenterelectricityconsumption(projections-TWh)

1800

1600

1400

1200

1000

800

600

400

200

-

20232024202520302035*

HeadwindsHighEfficiencyBaseLift-Off

Source:J.P.MorganbasedonIEA(2026),KeyQuestionsonEnergyandAI,IEA,Paris

https://

/reports/key-questions-on-energy-and-ai

,Licence:CCBY4.0

Figure3:AIDC’selectricityconsumptionshouldalmostmatchthatofconventionalDCby2030

Datacentreconsumption(TWh)

1000

900

800

700

600

500

400

300

200

100

0

20252030

ConventionalAI-focused

Source:J.P.MorganbasedonIEA(2026),KeyQuestionsonEnergyandAI,IEA,Paris

/reports/key-questions-on

-energy-and-ai,Licence:CCBY4.0

Capacityis“maxedout”to2030:AccordingtoThomasSpencer,co-authoroftheIEAreport,theunchangedBaseCaseisexplainedbyphysicalconstraintsthatlimitthe

outlook’svariabilitythroughtheendofthedecade.TheIEAidentifiesthemostbindingphysicalconstraintsondatacentrebuild-outas:(1)high-endIThardwaresupply,

notablymemory,withorder-of-magnitudedemandincreasesstrainingglobal

manufacturing;(2)gridconnectionwaittimesof4–5yearsminimuminmajormarkets;(3)gasturbineavailability,withordersup70%anddeliverynowslippingpast2030;(4)transformerandspecialisedelectricalequipmentleadtimes,whichhavedoubled;and

(5)skilledlabourshortages,particularlyelectricians.From2030,however,theIEA

scenariosaremoredifferentiated,thankstomarketdynamicseasingtheseconstraints.

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Figure4:Industryprojectionsseeadoublingofaccelerators

shipmentsto2030-with2035estimatesseeinghighuncertainty

AcceleratorsShipment(Index,2025=1)

6

5

4

3

2

1

0

20152020202520302035

Source:J.P.MorganbasedonIEA(2026),KeyQuestionsonEnergyandAI,IEA,Paris

https://

/reports/key-questions-on-energy-and-ai

,Licence:CCBY4.0

Figure5:The2030IEABaseCaseisderivedfromindustryprojections

AcceleratedServerCapacityShipped(GW)

25

20

15

10

5

0

20152020202520302035

Source:J.P.MorganbasedonIEA(2026),KeyQuestionsonEnergyandAI,IEA,Paris

https://

/reports/key-questions-on-energy-and-ai

,Licence:CCBY4.0

Finally,regionaldynamicsarecrucial,astheUnitedStatesisexpectedtoaccountfor

45%ofDCelectricitydemand,followedbyotheradvancedeconomies(19%)andChina(6-7%).

Figure6:TheUSisexpectedtoaccountfor45%ofDCelectricitydemandgrowthto2030

ShareinDCelectricitydemandgrowth(%)

50

45

40

35

30

25

20

15

10

5

0

UnitedStatesAEChinaEMDE

Source:J.P.MorganbasedonIEA(2026),KeyQuestionsonEnergyandAI,IEA,Paris

/reports/key-questions-on

-

energy-and-ai,Licence:CCBY4.0

$3.9trnofCapexbetween2026and2030,including20%forEnergy

Cumulativeenergycapex2026–2030:$780bn($156bn/year)

TheIEA’slatestBaseCaseestimatesfordatacentregrowthimplycumulative

investmentindatacentresof$3.9trnbetween2026and2030ofwhichroughly20%

—approximately$780bn—isenergy-relatedcapexcoveringgrids,generation,

backupgenerators,anduninterruptiblepowersupply.Theremaining80%goesto

ITequipmentsuchasservers,accelerators,andstorage.TheIEAnotesthatacrosscases,theabsoluteenergy-relatedinvestmentrangesfromapproximately$500bninthe

HeadwindsCasetoaroundUSD1trillionintheLift-OffCase—adifferenceofmore

than$500bndrivenbythescaleofcapacityadditionsandthecostofresolving

bottlenecks.Onanannualbasis,thatgivesabout$780bnofDCCapex,including

$156bnforenergybetween2026and2030.TheIEAstopsshortofprovidingtotalcapexestimatesinallscenarios.

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Figure7:20%of$3.9trnDCCapexforEnergyintheBaseCase

BasecaseCapex(%)-2026-2030

Energy,20%

Source:J.P.MorganbasedonlEA(2026),KeyQuestionsonEnergyandAl,lEA,Paris

https://

/reports/key-questions-on-energy-and-ai

,Licence:CCBY4.0

Figure8:TheIEAestimatesbetween$500bnand$1trnofEnergyCapexby2030

Energycapexbycase($bn)-2026-2030

1200

1000

800

600

400

200

0

HeadwindsCaseBaseCaseLift-offCase

Source:J.P.MorganbasedonlEA(2026),KeyQuestionsonEnergyandAl,lEA,Paris

https://

/reports/key-questions-on-energy-and-ai

,Licence:CCBY4.0

AmongEMEAstocks,weviewCapGoodsandITHardwareasthebest-placedsegments,andwedetailtheJ.P.MorganOW-ratedstocksinthededicatedsection,includingASML,Legrand,NokiaandSchneiderElectric.

Significantroll-outofRenewables,Gas,UPSandBESS

Renewablesareexpectedtoaccountforthelargestshareofadditionalpower

demand.GasisaclosesecondduetolargeexpecteddeploymentintheUS.The

latestIEAprojectionsincreasedbothrenewablesandgasexpectedroll-outby2030,

basedonupdatedmarketandprojectpipelinedata.Withanadditional200TWh

(360TWhin2030),renewableswouldaccountformorethanone-thirdofDCtotal

generationby2030.Gasisexpectedtogrowstrongly,mostlyintheUS,doublingto

around340TWhandreachingaround30%ofthemix.Thetwowouldcoverabout65%ofDCelectricitydemandbytheendofthedecade.

Figure9:Renewablesareexpectedtoaccountforthelargestshareofdatacenterpowersupplycapacity…althoughgasisaclosesecondwithmeaningfulgenerationdeploymentintheUS

GrowthinDCgeneration2025-2030(TWh)

200

150

100

50

0

RenewablesNaturalgasCoalNuclear

Source:lEA(2026),KeyQuestionsonEnergyandAl,lEA,Paris

/reports/key-questions-on-energy-and-ai

,Licence:CCBY4.0

Onsitebatterysystemswillseesignificantgrowth,beingcrucialfordatacentre

powersupplyreliability,providingshort-termbackupthroughUninterruptible

PowerSupply(UPS)unitsinbothgrid-connectedandoff-gridsetups.IntheUS,theIEAprojectsthatonsiteprojectscouldcover6-13%oftotalgrowthindatacentre

capacityto2030.GlobaldatacentreUPScapacityisexpectedtorisebymorethan100GW,broadlymatchingthegrowthindatacentreinfrastructure.

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Globalinstalledcapacityoflonger-durationbatteryenergystorageindatacentreswillrisefromaround5GWtodayto20-25GWby2030.ThemajorityofthiswillbeintheUnitedStates,whereonsitebatterystorageindatacentresisexpectedtoreach10-12GWby2030,comparedwithmorethan90GWofgrid-connectedutility-scale

batterystorage.

Powermeup,Scotty!Alphagenerationinthebatteryrevolution(V.Heriz&al.)

highlightsAnekaTambang,L&F,Sungrow,LGES,CATLandSamsungSDIasJ.P.MorganOWratedbatterystocks.

Figure10:WhileonsitegenerationisoneofthemosttalkedaboutangleofAIDCpower...

InstalledOnsiteGasCapacity(GW)

30

25

20

15

10

5

0

202520262027202820292030

Low(GW)High(GW)

Source:IEA(2026),KeyQuestionsonEnergyandAI,IEA,Paris

/reports/key

-questions-on-energy-and-ai,Licence:CCBY4.0

Figure11:Onsitebatterystorageisexpectedtogrowasfast

InstalledOnsiteBatteryStorageCapacity(GW)

30

25

20

15

10

5

0

202520262027202820292030

Low(GW)High(GW)

Source:IEA(2026),KeyQuestionsonEnergyandAI,IEA,Paris

/reports/key

-questions-on-energy-and-ai,Licence:CCBY4.0

CoalwillremainasignificantsourceofAIpowergenerationinChina,while

Nuclearisexpectedtoseemoderategrowthto2030.Thelongdevelopmenttimeofnuclear,aswellaslackofmaturityofSMRsarelimitingtheprojectedroll-outof

capacitybytheendofthedecade.

Europe’sNuclearRenaissance:RecentDevelopments,FutureOutlookStockIdeas(Hecker&al.)underlinesCentrica,Rolls-RoyceHoldings,SiemensEnergy,

Bouygues,BabcockInternational,IMI,andRotork,asJ.P.MorgannuclearexposedOWEMEAstocks.

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HowMuchComputeDoesAlNeed?

“Unprecedented”energy-efficiencyimprovements

TheIEAreportdescribestheenergyefficiencygainsinAIasoccurringata

paceunprecedentedinenergyhistory.Measuredperindividualtask,softwareand

hardwareadvanceshavedriventheenergyuseperAIquerydownbyatleastanorderofmagnitudeannuallyinrecentyears.Thefirstofficialper-que