2026年AI竞赛下的能源竞速研究报告：发展中国家的绿色机遇窗口？（英文版）

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THEENERGYSPRINTOFTHEAIRACE

AGREENWINDOWOFOPPORTUNITY

FORDEVELOPINGCOUNTRIES?

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Acknowledgements

ThisreportwaspreparedbytheUnitedNationsDevelopmentProgramme(UNDP),underthestrategicdirectionofRiadMeddeb,HeadofDecarbonizationandSustainableEnergy,incollabo-rationwithAmirLebdioui,DirectoroftheTechnologyandIndustrialisationforDevelopmentCen-tre(TIDE)attheUniversityofOxfordandAngelMelguizofromtheOxfordTIDECentre.ThisworkalsobenefitedfromthevaluablecontributionsbytheDecarbonizationandSustainableEnergyteam,particularlyClementAmponsah,CalumHandforth,StefanoPistolese,BenjaminKellerandAndreaRenzulli.DesignwascompletedbySiNaeSong.

ThereportfurtherbenefitedfromvaluableinputsandguidancefromHiroshiWaldandRobertOpp,UNDPChiefDigitalOfficerandtheteam,particularlyKeyzomNgodupMassally,RaiyanAr-shad,andNormanSonntag.Thisworkalsobenefitedfromtheinsights,guidance,andsupportofseveralexternalindividualsandorganisations.WeextendoursincereappreciationtocolleaguesattheUNDPPlanetHub,particularlyMidoriPaxton,TimScott,andBahtiyarKurt.Theworkad-ditionallybenefitedfromcontributionsbyformerinterns,particularlySerenaThiToandPraveshRaghoo,aswellasUNVOnlineVolunteerswhosupportedthestartupmappingdatacollection.

TheauthorsalsowishtoexpresstheirappreciationtocolleaguesacrossUNDP,theTIDECen-tre,theUniversityofOxford,andpartnerinstitutionswhoseinsightsenrichedthispaper.SpecialthanksareextendedtothemanystakeholdersshapingthefutureofAIandsustainableenergytransitionsindevelopingcountries,whoseexperiencesandperspectiveshelpedinformthiswork.

TableofContents

Executivesummary2

1.TwoConvergingRevolutions:

TheAIRaceandtheGlobalEnergyTransition 7

2.AIasaGreenWindowofOpportunity? 21

3.OperationalizingtheGreenWindowofOpportunity

ThroughthePeople-Planet-ProsperityFramework 33

4.AGreenAIEcosystemintheGlobalSouth:

OpportunitiesandBarriers53

5.PolicyRecommendationsforDevelopingCountries:

BuildingaPeople-CentredAI-EnergyEcosystem 65

6.Conclusion:GoverningAIforSustainableDevelopment 81

Bibliography 85

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Executivesummary

ThefutureofArtificialIntelligence(AI)willbeshapedlessbyalgorithmsthanbyaccesstosustainableenergy.

AImayreshapeeconomies,butitisultimatelyfoundedonphysicalinfrastructure,particularlyenergysystems.Thelong-termcompetitivenessofnationalAIecosystems–andtheopportunitiesthattheycanunlock–willthereforedependonaccesstoabundant,reliable,cheapandcleanelectricity.Thiscouldfundamentallyreshapethebalanceofpoweringlobalinnovation,shiftingthecomparativeadvantageforthistransformativetechnologytowardscountrieswithsignificantrenewableenergypotential,manyofwhichareintheGlobalSouth.

TheAIandclimateagendasarenotseparateandrequireintegratedpolicyapproaches.Theydrawonthesamefoundations,includingelectricity,water,land,financeandgovernance.Yettoooftentheyarepursuedinisolation.Thissiloedapproachisnolongerviableandwasneverdesirable.Countriesneedtodrivestrategicandcoherentapproachestoboth–viewingtheenergyandAItransitionsastwonew,intertwinedstrandsofindustrialandeconomicpolicy.ThiscoherencewillbekeyinunlockingthepotentialofAIandkeepingAIdevelopmentwithinplanetaryboundaries.

Withoutsustainableenergysystems,AIrisksdeepeningglobalinequalities.Electricityconsumptionbydatacentresisprojectedtomorethandoubleby2030,reaching945terawatthours.AIisthereforebecomingconstrainednotbyalgorithmsordatabutbyaccesstoabundant,affordableandlow-carbonelectricity.Countrieswithoutreliableandsustainableenergysystemsriskexclusionfromthenextdigitalrevolution.

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AI-energytensionsopen

agreenwindowofopportunity

Beyonditsdirectenergyneeds,AIisalsoembeddedinheavyphysicalsystemswithstrategicimplications.Thisincludessemiconductorfabricationplants,high-performancecomputeclustersandhyperscaledatacentresthatrequirestablepower,waterandrareminerals.Yetthismaterialityalsocreatesstrategicleverage.Countriesthatstrengthenboththeirenergyanddigitalinfrastructurescouldbecomekeyactorsintheglobalinnovationeconomy.Whendesignedaspublicinterestinfrastructure,integratedAI-energysystemscanreducesystemlosses,stabilizetariffsandexpandaccessforpeople,allowinghouseholdsandsmallenterprisestobenefitfromlowercostsandmorereliableelectricity.ThiscanalsoopenupnewAIopportunitiesandpathways.Formanydevelopingeconomies,especiallyinAfricaandSmallIslandDevelopingStates,modularanddistributedsystemsofferamorerelevantentrypointbyaligningwithcurrentlocaldemand,easingpressureonfragilegridsandenablinggradualscaling.

AIstandsatadecisivemomentforglobaldevelopmentandinequality.Thisreportcomesataninflectionpoint.AIisprojectedtoaddUS$15.7trilliontoglobaloutputby2030,yetlessthan10percentofthisvalueisexpectedtoaccruetodevelopingeconomies.Thisisthefoundationofwhatthereportterms‘GreenAI’:thebalanceddevelopmentofAI,energyandnature.GreenAIplacespeopleatthecentre,framingAI-energyintegrationasameanstoexpandhumancapabilities,improvelivelihoodsandsupportajusttransition,ratherthananendinitself.Thisisa‘greenwindowofopportunity’thatAIcouldopen.

ResourcegeopoliticsoftheAIrace

AIisreshapingglobalpowerdynamicsbyturningenergyintoacorestrategicasset.TheriseofAIasanenergy-dependentsectorcouldreshapealliancesandbargainingpower.TherivalrybetweenChinaandtheUnitedStatesofAmericanowextendsbeyondsemiconductorexportcontrolstoincludecompetitionforenergy-secureAIclusters.Thisreconfigurationcreatesnewandmultipolardynamicsinwhichenergy,mineralsanddataconvergeintoasinglestrategicdomain.Theseshiftshavefar-reachingimplicationsfordevelopingeconomiesseekingtocarveoutdevelopmentspaceinarapidlyshiftingglobaltechnologicalorderlinkedtoenergy-intensivedigitalinfrastructure.

Arenewables-basedcomparativeadvantagealoneisnotsufficienttosecureasustainableAIpathway.Solarandgeothermalpotentialmustbematchedbystablegrids,predictablepolicy,robustregulationandindustrialcapability-building.Withoutthis,AIcoulddeependependenceonforeigncloudservices,strainfragileenergysystemsandleavedevelopingeconomiesinextractivedigitalrolesratherthanascreatorsofvalue.ThequestionishowdevelopingcountriescanharnessAIasagreenwindowofopportunityratherthanreinforceexistinghierarchies.

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AkeygapintheAI-energydebateisthatithasfocusedlargelyonsupply-sideconstraints,whiletheconditionsforadoptionanddemandcreationhavereceivedlessattention.AIdoesnotdiffuseautomaticallyfromglobalinnovationhubsintolocaldevelopmentsystems.Itrequirestrustedlocalusecases,affordableservices,institutionalbuyers,skilledusers,accessibledataandfinancingmodelsthatallowfirms,utilitiesandpublicagenciestoexperimentwithouttakingonexcessiverisk.Users,entrepreneurs,utilitiesandpublicinstitutionsarethereforecentraltoAIdiffusion,particularlyintheenergysector,whereadoptiondependsonrealoperationalneeds,procurementcapacityandcrediblepathwaystoscale.Cross-countryinequalitiesinAIreadinessreinforcethisdivide.Withincountries,unevendigitalskillsandwideninggenderandurban-ruralgapsathigherskilllevelsshapewhocanbuild,useandbenefitfromAI.

AI-energyecosystem

developmentintheGlobalSouth

GreenAIstartupsareemergingaskeyactorsintranslatingtheAI-energytransitionintoagreenwindowofopportunityfordevelopingeconomies.Theysitattheoperationalintersectionofpowersystems,digitalinfrastructureandclimatesustainability.Thisreportanalysesnearly90ofthemfromacrosstheGlobalSouth—comprisinginnovatorsworkingonenergy-climatetechnologiesforAI(renewables,storage,gridoptimizationandefficientdata-centreinfrastructure)andAIforclimate(forecasting,automation,decarbonizationandresourceoptimization).Thesestartupscouldofferstrategicpathwayswheregovernmentsanddevelopmentpartnershelpcreateviablemarketsthroughprocurement,regulatorysandboxes,utilitypartnerships,concessionalfinance,openenergydata,testingfacilitiesandsupportforearlyadopters.

Despitegrowingmomentum,GreenAIecosystemsfacesignificantstructuralconstraints.ThemappingrevealsthatstartupsareclusteredinnineGreenAIactivityareas,dominatedbyAIforenergy,gridedgeintelligenceandAI-enabledinfrastructure.Commercialtractionishighlyconcentratedinasmallsubsetofthestartups,however,reflectingdeepdemand-sideandinstitutionalconstraints.Theseconstraintsreflectweakdemand,limitedearlyadopters,thinventurecapitalecosystemsandmisalignmentbetweenpublicinstitutionsandprivateinnovation.

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Apeople-planet-prosperityroadmap

Tomeetthesechallenges,thereportadvancesaholisticframeworkwiththreepillars:people,planetandprosperity.Thepeoplepillarfocusesonbuildingskills,inclusionandpublicbenefitdigitalinfrastructuresocommunitiesareempoweredbyAIandcleanenergytransitions.TheplanetpillaremphasizessafeguardingenvironmentalboundariesbymanagingtheAIresourcefootprintwhiledeployingAItostrengthenclimateresilience.TheprosperitypillarlooksatsteeringAIinvestmenttowardsrenewableenergy,industrialupgradingandinclusivegrowth.

FivestrategicpolicyactionscanguidedevelopingcountriesinshapingAIandenergytransitions:

1.StrengtheneconomicresiliencebybuildingalocalAI-energyinnovationecosystemthatlinksdomesticskills,institutionsandinfrastructure.

2.AdoptGreenAIasthedefaultapproachtosteerAIinfrastructure,procurementandinvestmenttowardlow-carbondevelopment.

3.Moveupthecriticalminerals-energy-computevaluechainthroughstrategicactiontosupportdomesticAI-energyinnovation.

4.AlignAI,energyandindustrialstrategiesthroughintegratednationaldevelopmentplanningandpartnerships.

5.SupportGreenAIstartupsthroughtargetedentrepreneurship,financeandmarket-creationpolicy.

TheseactionslinkAIdevelopmenttoenergysystemssothatcleanenergyabundancesupportsinclusivegrowth,resilienceandsharedprosperity.Fordevelopingeconomies,thepolicychallengeistoshapethetermsonwhichAIexpands:whethercountriesremainsuppliersofland,energy,mineralsanddata,orwhethertheyusetheAI-energytransitiontobuildcapabilities,improveservices,strengthenpowersystemsandcapturehigher-valueeconomicactivity.

Thisreportcriticallyexaminesthesedynamics,aimingtocontributetoglobalpolicydebatesattheintersectionofAI,energyandsustainabledevelopment.

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FivePolicy

Recommendations

Figure1.FivepolicyactionsfordevelopingcountriesonAIandenergytransitions

Source:Authors’elaboration.

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1.TWOCONVERGINGREVOLUTIONS:THEAI

RACEANDTHEGLOBALENERGYTRANSITION

“Greenisnotatechnologicalrevolution.Itisthedirectioninwhichtheinformationrevolutionneedstobetaken.”

—CarlotaPerez

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Introduction

TherapiddevelopmentanddeploymentofAIisreshapingtheglobaleconomyinwayscomparabletotheintroductionofelectricityortheInternet.AIisincreasinglyrecognizedasasimilarlygeneral-purposetechnologyshapinglong-termeconomicandsocietaltrajectories.Yetitsprogressisconstrainednotprimarilybydataavailabilityoralgorithmicsophisticationbutbyaccesstoabundant,affordableandlow-carbonenergy.AImodels,particularlystate-of-the-artsystems,butalsoanexpandingrangeoftask-specificanddecentralizedapplications,requireexponentiallygrowingcomputationalpower.Thisinturndependsonenergy-intensivedatacentres,specializedchipsandcoolinginfrastructure(Sevillaetal.2022;HernandezandBrown2020;UNESCO2024;Gmyreketal.2024).FundamentalquestionsemergearoundwhethertheglobalAIraceisultimatelyanenergyrace,andwhatthismeansfordevelopingeconomies.

Energyremainsoneofthesharpestdividinglinesindevelopment.Globalelectricityaccessreached92percentin2023(IEA2025b),yetthisheadlinemasksdeepstructuralinequalities.Insub-SaharanAfrica,progresshasstalledand,insomecountries,reversed.TwothirdsofSouthSudan’spopulationstilllackselectricity,whileinpartsofruralNiger,clinicsrelyonfragiledieselgenerators.Nearly730millionpeopleareprojectedtoremainwithoutpowerby2030(ibid.).Energykeepshospitals,schools,watersystems,factoriesanddigitalnetworksrunning.Whenpowerisunreliable,developmentfalters.Almost1billionpeoplerelyonhealthfacilitieswithnoorunstableelectricity,andfirmsinpartsofAsiareportlosing5to7percentofannualsalesduetooutages.Thesefailuresmagnifypoverty,disrupteducation,constrainenterprisesandweakenalreadyfragileinstitutions.

AItrainingoccursinlargedatacentres,whichconsumeabout415terawatt-hoursannually(IEA2025b),afigureprojectedtoreach1,000TWhin2026,roughlyequivalenttoJapan’stotalenergyconsumption(Berreby2024;IEA2025b).Globalelectricityconsumptionfromdatacentressurgedin2025,drivenbyAI,andissettoalmostdoubleby2030,whileelectricitydemandfromAI-focuseddatacentrescouldtriple(seeFigure2).

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Figure2.DataCentreElectricityDemandAcceleratesin2025andContinuestoRise

Source:IEA(2026)

Note:2030valuesareprojections

Thisdemandhasgrownbyapproximately12percentannuallyoverthepastfiveyears;newglobalinvestmentsoverthelasttwoyearshaveincreasedby70percent(IEA2025b),drivenbylarge-scalemodeltraininganddatastorage.ThesurgeingenerativeAI(GenAI)modelsfollowingthereleaseofChatGPTinlate2022hasdramaticallyintensifiedcomputationaldemandsondatacentres,withdemandprojectedtocontinueincreasing.Severalstudiesdocumentexponentialincreasesinthecomputational(andthusenergy)requirementsoffrontierAImodels,showinga300,000-foldincreaseincomputeusagesince2012(HernandezandBrown2020;Sevillaetal.2022).TheInternationalEnergyAgency(IEA)projectsthatdatacentresmayconsumeupto8percentofglobalelectricityby2030comparedto2percenttoday(Figure3),raisingconcernsthatAIgrowthcouldoverwhelmnationalgrids,particularlyinemergingeconomies.

TheenergydivideisnowcollidingwiththerapidexpansionofAI.By2030,almostUS$7trillionincapitalinvestmentmayberequiredtoexpandglobaldatacentresandcomputeinfrastructure,withmorethanUS$5trillionlinkeddirectlytoAIworkloads(Noffsingeretal.2025).Attheheart

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ofthisexpansionliescompute,theprocessingpowerthattrainsandrunsmodernAIsystems.Computeisdeliveredthroughalong,energy-intensivepipelinethatbeginswithsemiconductorfabrication,passesthroughhigh-performancecomputingsystemsandendsinhyperscaledatacentresdesignedforAIdevelopmentandinference(manylocatedintheGlobalNorth).Eachstepcarriesaheavyelectricity,waterandmineralfootprint.Asingleadvancedsemiconductorfabricationplantcanconsumeasmuchelectricityasamid-sizedcitysuchasMombasa,alevelofpowerthatmanycountriesstillstruggletodeliverreliablytoclinicsandschools.ThisisamicrocosmofapotentialeraofglobalAIinequity.AIisexpectedtoaddUS$15.7trilliontoglobaloutputby2030,butonlyaround10percentofthisvalueislikelytoaccruetodevelopingcountries(PwC2018;UNDP2024b).

Evenso,thehyperscaleAImodelshouldnotbetreatedasauniversalblueprint.Formanydevelopingcountries,particularlyinAfricaandSmallIslandDevelopingStates,modular,distributedandedge-computingsystemsmaybemoreappropriateastheycaneasepressureonfragilegrids,bedesignedforenergyefficiencyfromtheoutset,andprovidethecomputeneedsfornearer-termAIexplorationandimplementation.Ratherthancompetingtohostlargefrontier-modelclustersthatareassociatedwithsignificantfinancialandresourcecosts,theyenablemoregradual,context-sensitivescalingalignedwithexistinginfrastructure.Thisapproachcouldalsoopenpathwaysforvaluecreationthroughlocallyrelevantapplicationsandservicesratherthancapital-intensiveinfrastructurealone.ThiscouldopennewmodelsandopportunitiesforapproachestoAIenergyinfrastructure.

Figure3.Globaldatacentreelectricityconsumptionbysensitivitycase,2020–2035

Source:IEA2025b.

Note:TWhreferstoterawatt-hour.

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Newopportunity—andnewinequality?

EnergyisbecomingoneofthedecisiveconstraintsshapingthegeographyofAI,alongsidedata,talent,capital,chips,institutionsandmarketdemand.Countriesthatcancombinereliablelow-carbonpowerwithdigitalcapability,regulatorycredibilityanddomesticdemandwillbebetterpositionedtocapturevaluefromAI.Thisgeopoliticalroleintersectswithothercoredevelopmentpriorities,including(seeFigure4):

•Mineralgeopolitics:withcriticalrawmaterialsforchipsandbatteries.

•Energygeopolitics:withcleanelectricityastrategicasset,andenergyintellectualpropertypoisedtobecomeanewdividingline.

•Digitalgeopolitics:thecontrolofourdigitalandinnovationhighways,platforms,anddataandcloudinfrastructure.

•Economicgeopolitics:withresearch,developmentandtechnicalhumancapitalafluidasset,oneincreasinglyavailabletocountrieswiththedeepestpocketsandmostattractivepackages.

Thereisanimportantnuance,however.Countrieswithstrongrenewableprofilescouldpositionthemselvesstrategicallyiftheyavoidbeingrelegatedtoextractiveroles.China,forinstance,hasshownthattechnologicalhegemonyhasbeenanchoredinpublicandregulatorycontrolthataligns

Figure4.GlobalgeopoliticaldriversofAI

Source:Authors’elaboration.

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infrastructurewithnationalindustrialanddevelopmentobjectives.Itsexperiencedemonstrateshowstatecoordinationovercoreinfrastructure(e.g.,railways,electricitygrids,semiconductorfactories,datacentres)canunderpintechnologicalupgradingandcompetitiveness.

TheemergingAIeconomyfollowsthesamepattern.AsAImodelsbecomelargerandmorecompute-hungry,theyrequirevastamountsofelectricity,coolingwater,refrigerants(dependingonthetechnologyusedforcooling),andlandforhyperscaledatacentres.TheserequirementsbindAItomaterialandterritorialconstraintstypicallyassociatedwithheavyindustryratherthandigitalservices.Thenextwaveofglobalcompetitionwillhingeonwhichcountriescansupplyabundant,affordableandreliableelectricityatscale.IntheUnitedStates,thesitingofdatacentresisincreasinglyshapedbyacomplexmixofpoweravailability,gridinterconnectiontimelines,land,taxincentivesandaccesstolow-costelectricity.Whilelow-carbonpowerremainsanimportantstrategicconsiderationformanyfirms,newdata-centregrowthhasalsobeenconcentratedinregionswheregridsremainsignificantlyfossil-fueldependent,underscoringtheneedtolinkAIinfrastructureplanningmoredirectlywithclean-powerexpansionandgriddecarbonization.

TheriseofAIasanenergy-dependentsectorisreshapingalliancesandbargainingpower.TheChina-UnitedStatesrivalrynowextendsbeyondsemiconductorexportcontrolstoincludecompetitionforenergy-secureAIclusters.NationssuchasBrazil,India,Malaysia,SaudiArabiaandSouthAfricaarepositioningthemselvesasalternativehubsforAIinfrastructure,creatingnewmultipolardynamicsinwhichstrategiesonenergy,mineralsanddataconverge.

However,positioningasaninfrastructurehubdoesnotautomaticallytranslateintobroad-baseddomesticgains.AbundantcleanpowerdoesnotbyitselfcreateaviabledomesticAIeconomy.Inmanydevelopingcontexts,AIdemandremainsconstrainedbylowfirmdigitalization,limitedpurchasingpower,weakaccesstoaffordablecomputeandcloudservices,shortagesoftechnicalandmanagerialskills,andlimiteddiffusionoflocallyrelevantapplications.Withoutdeliberatedemand-shapingpolicies,countriesmayhostdatacentreswhilecapturingonlyanarrowshareofthebenefits,creatingenclave-stylegrowthbuiltaroundimportedtechnology,foreignplatformsandlimitedlocallinkages.ThedevelopmenttestiswhetherAIinfrastructurestrengthensthewidereconomybyimprovinggridreliability,expandinglocalsuppliernetworks,creatingtechnicaljobs,supportingpublic-interestapplicationsandenablingdomesticfirmstoadoptAI.

Theseinequalitiesarealsoreflectedincross-countryAIreadiness(seeFigure5).TheUnitedStatesandChinadominateinscale,whilesmallereconomiessuchasIsrael,SingaporeandSwitzerlandperformstronglyonintensitythroughconcentratedinvestmentandefficientecosystems.Manydevelopingeconomies,bycontrast,remainatthelowerendofthedistribution.CountriessuchasEthiopiaandKenya,forexample,continuetofacemajorconstraintsinbroadbandaccess,digitalcapabilitiesandinnovationcapacity,whilemiddle-incomecountriessuchasBrazilandMalaysiaoccupyamoreintermediateposition,reflectingunevenbutgrowingreadiness.ThefigurethereforereinforcesthebroaderpointthatAIopportunityremainshighlyuneven,withmanydevelopingeconomiesstillneedingtobuildthebasicfoundationsforadoption.

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Figure5.GlobalpatternsofAIreadinessbyscaleandintensity,2024

Source:WorldBankcalculationsusingdatafromTortoiseMedia’sGlobalAIIndex.

TheseconstraintsreflectwideninginequalitiesbothbetweenandwithincountriesinaccesstothefoundationsoftheAIeconomy.Digitalskillsremainhighlyunevendespiterisingglobaldemand(seeFigure6),withastarkcross-countrydivide.ThisAIreadinessindexcombinesindicatorsrelatedtodigitalinfrastructure,innovationcapacity,humancapital,governance,investmentandecosystemmaturity.ThedistinctionbetweenscaleandintensityhelpsseparatecountrieswithlargeabsoluteAIecosystemsfromsmallereconomiesthatperformstronglyrelativetotheirsize.AccordingtoarecentWorldBankreport,fewerthan5percentofpeopleinlow-incomecountrieshavebasicdigitalskills,comparedto21percentinlower-middle-income,38percentinupper-middle-income,and66percentinhigh-incomecountries(seePanela).

Moreover,inlow-incomecountries,advanceddigitalskillsareaboutfivetimesmorecommoninurbanthanruralareas.Inlower-middle-incomecountries,theurban–ruralgapreaches5.30foradvancedskills,whilethegendergapincreasesfrom1.21(basic)to1.52(advanced).Upper-middle-incomecountriesshowsmallerbutpersistentdisparities,withgendergapsrisingfrom1.05to1.47andurban–ruralgapsfrom1.88to2.70(seepanelb).Eveninhigh-incomecountries,bothgenderandurban–ruralgapspersistandwidenathigherskilllevels.

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Figure6.Supplyofdigitalskills,2023

Source:WorldBank(2025a)

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Computeisevenmoreconcentrated.High-incomecountrieshost86percentoftheworld’stopcomputingsystemsandalmostalloftheircapacity,whilemiddle-incomecountriesexcludingChinaandIndiahostjust3percentdespiteaccountingfornearlyhalfoftheglobalpopulation(WorldBank2025a).Theseasymmetriesriskreinforcingapatterninwhichsomecountriessupplyland,energyandmineralswhileotherscapturemostofthevalue,innovationanddecision-makingpower.Connectivitygapsfurthercompoundtheseinequalities.Around2.6billionpeopleremainoffline,including1.8billioninruralareas(ibid.).Althoughmobilecoverageexceeds98percentglobally,meaningfulinternetaccessremainsasignificantchallenge.Inlow-incomecountries,penetrationisjustoverone-quarterofthepopulation,andbasicaccesscancostnearly30percentofmonthlyincome.

Ifthesedividesareleftunaddressed,AIcoulddeepeninequalitybothacrossandwithincountries,includingbywideninggendergapsinskills,employment,andaccesstodigitalpublicservices.Thekeychallenge,therefore,extendsbeyondsecuringcleanelectricityforAIsystemstoensuringthataccesstoAIcapabilities,infrastructure,andopportunitiesisdistributedmorebroadlyandmorefairly.Thiswillrequirepoliciesthatexpandaffordableconnectivity,supportinclusiveinnovationecosystems,andstrengthendigitalandmanagerialcapabilitiesthatbetterreflecttheneedsofunderservedcommunities.

TheAIraceandtheglobalenergytransition

Theworldhastwoconvergingraces(seeFigure7).OneistobuildandscaleupadvancedAIsystems.Theotheristodecarbonizeenergysystemswhileexpandingaccesstoreliablepower.Theseareintersectinganddrawonthesamefoundations,includingelectricitygrids,waterresources,financeandregulation.Yettheyarestilltreatedasseparateagendas.Thisfragmentationriskslockingcountriesintoshort-termfixesthatbuckleunderlong-termpressures.IfAIdeploymentracesaheadofenergyplanning,inequalitymaydeepen,gridsmaycomeundernewpressure,andcountriesmayincreaserelianceonfossil-basedgenerationortemporaryhigh-emissionsolutions,potentiallylockingAIgrowthintocarbon-intensiveenergypathways.Thisdemandsfocusandattentionfromdecision-makers.LeveragingthepowerandpotentialofAI,andshapingenergyfoundationsandinfrastructuretoleverageitsbenefits,couldbeakeyto21stcenturyindustrialpolicyandsustainabledevelopment.

Atthesametime,thisconvergencecreatesahistoricopportunity.Usedstrategically,AIcanimprovepower-systemmanagementbystrengtheningdemandforecasting,identifyingflexibilityopportunities,optimizingstorageanddistributedenergyresources,reducinglosses,andimprovingthedispatchofvariablerenewables.Thesegainscanhelpdeferorreducesomecapital-intensivegridinvestmentswhileimprovingreliability,especiallyinconstrainedsystems.

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Morefundamentally,thepoliticalandeconomicurgencysu