goldman-sachs 将人工智能应用于实体经济 Harnessing AI for the Real Economy

HarnessingAIforthe

RealEconomy

ALETTERFROMDANDEES

DanDees

Co-HeadofGlobalBankingandMarkets

TheAIeraisdrivingindustrialtransformationunlikeanyinmodernhistory—faster,broader,andmore

capital-intensive,creatingnewinfrastructureandindustrysimultaneously.

MostofthecapitalthatwilldefinetheAIeconomyhasnotyetbeendeployed,mostoftheinfrastructurehasnotyetbeenbuilt,andmostoftheM&Athatwillshapethecompetitivelandscapehasnotyetbeenexecuted.Hyperscalersaloneareprojectedtoinvestmorethan$6trillioninAIthrough2030—manytimesthecapitaldeployedtointernet

infrastructureduringthedotcomera.Fundingabuildoutofthisscale,anestimated$7trillion+between2026and2031acrosscompute,power,anddatacenters,willrequirethefullcapitalstack:equity,publicandprivatedebt,sovereigncapital,andnewjoint-venturestructures,someofwhichhaveyettobeinvented.

1

Evenatthatscale,USAIinvestmentequalsonlyabout1.2%oftoday’sannualGDP.

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Andwhileitwillrisefurtherifcurrentprojectionsarerealized,eventhemostoptimisticscenariossuggestitwillremainwellbelowtherailroadbuildoutsofthe1800s,whichran3%to4.5%.

InPoweringtheAIEra(2025),weexaminedtheinfrastructurebuildoutandthefinancinginnovationsmeetingthat

demand.Thisreportaddresseswhatcomesnext:theindustrialreorganizationunfoldingacrosstherealeconomy,thecapitalpoolsbeingassembledtofundit,andthegapbetweentoday’sdigital-infrastructurefinancingandthedemandsofphysicalAIatscale.

Thepatternhasprecedent.GeorgeWestinghousefoundedhiselectriccompanyin1886atthecenterofthelastgreat

energytransition.Today,thecompanyisattheforefrontoftheenergytransitionthatwilldefinewhatcomesnext—

acceleratingthebuildoutoflarge-scalenuclearpowergenerationtohelpmeetgrowingenergydemandandsupport

energysecurityintheUnitedStates.Siemens,foundedin1847aroundthetelegraph,isnowaleaderindefiningthefutureofindustrialAI.Businessesendureacrosssuchtransformationsbyembracingnewtechnologiesandreinventingtheir

strategicplaybooksandcapitalstructuresinresponse.

Thecompaniesemergingalongsidethemarebuildingtheirtechnologyandcapitalarchitecturesimultaneously:AI

labsgrowingatmultibillion-dollarrevenuenumbers,physicalAIandroboticsfirmsdrawingcapitalatsoftware-startupvelocity,defensechallengersreshapingincumbents,spaceventuresreachingthepublicmarketsatunprecedentedscale,andnewcompaniesbuildingAIforengineeringandmanufacturingitself.

GoldmanSachshaspartneredwiththecompaniesbehindeverymajorindustrialtransformationforover150years.Wecontinuetoconnectinnovatorswithcapital,industryexpertise,andstrategicguidanceastheynavigatethe

transformationhappeningtoday.Anditfeelslikewe’rejustgettingstarted.

DanDees

Co-HeadofGlobalBankingandMarkets

Contents

4AConvergenceUnlikeAny

Before:HowAIIsReshaping

theRealEconomy

8TheNewIndustrialEconomy:

WhereAIMeetstheRealWorld

22CapitalArchitecture:Financing

theNextPhaseofExpansion

31GlobalInvestmentBanking

LeadershipandContributors

SECTION01

AConvergence

UnlikeAnyBefore:

HowAIIsReshapingtheRealEconomy

Everymajortechnologytransitionhasfollowedafamiliarsequence:infrastructurebuiltfirst,applicationsdevelopedontop,andcapitalstructuresadaptingalongtheway.TheAIeconomyhasbrokenthatformula,reshapingtherealeconomyatapacenopriortransitionhasmatched.Towininthisera,leaderswillneedincisivecapital

strategyasmuchasthetechnologyitself.

01|ACONVERGENCEUNLIKEANYBEFORE:HOWAIISRESHAPINGTHEREALECONOMY

HARNESSINGAIFORTHEREALECONOMY5

Priorrevolutionsbegannotwhenthetoolsarrived,butwhenthecapitalcaughtuptoscalethem.Thecurrenttransitionisbeingenabledbythelast—withAI’scomputedemandpullingthenextwaveofenergybuildoutbehindit.

Our2025PoweringtheAIErareportsizedtheinfrastructureopportunityat$5trillionoverthenextdecade

3

—morethanelectrificationandtheinternetbuildoutcombined.

4

ButasecondtransformativelayerisconvergingasAIisremakingindustrialoperationsandmarkets—reshapingtherealeconomyasawhole.

ParallelShifts

MostofthebuildoutrequiredtopowertheAIeconomyisstillunderway,yetAIdisruptionisoutpacingthosefoundations.

GlobalhyperscalerCapExisprojectedtoreachover$760billionin2026(approximately$2billionperday).Globaldatacentersupplygrewfrom30gigawattsin2019to57gigawattsin2024,withanother

65gigawattsprojectedonlineby2030.

5

Thecapitalismovingsimultaneouslyacrossgeographies:US

hyperscalersleadtheheadlinefigures,butMiddleEastsovereignwealthfunds,Europeanindustrial

investmentindomesticAIcapacity,andAsiancapitaldeploymentaroundregionalsupplychainsare

nowstructuralcomponentsoftheglobalbuildout.InJune2026,GoogleagreedtopaySpaceXroughly$920millionamonth—about$30billionthroughmid-2029—foraccesstoapproximately110,000

NvidiaGPUs,asignthatcomputedemandnowoutrunswhateventhelargestownersofAIcompute

canbuildontheirowntimelines.

6

Gridoperatorsareprioritizinginterconnectionrequestswithenergyrequirementsthatdidn’tappearinanyplanningmodelthreeyearsago,andmostelectricaldistributionequipmentcarriesmultiyearbacklogsateverymajormanufacturer.Themismatcharrivesunevenly

acrosssectors—firstwheremarketcyclesrunshortest.

Fornow,softwarerepresentsthefirstmajorsignal,andphysicalAIiswhereitlands.Today,SaaS

accountsforlessthan0.5%ofglobalGDP.Therealeconomy—theother~99.5%oftheglobaleconomythatAIhasbarelytouched,frommanufacturingandroboticstodefense,construction,andenergy—

definestheactualscaleofopportunity.

7

In2025,industrylabsshippedapproximately90notable

AImodelreleases—morethandoublethe2023count—andthepacehasacceleratedfurtherinto2026.

8

Whatbeganasdisruptionwithinsoftwarewillspreadacrosseverysectoroftheeconomyasintelligencebecomesdeeplyembeddedinproducts,workflows,anddecision-making.

TheindustrialeconomyisalreadydeployingAIatscale.SiemensrunsAI-drivenpredictivemaintenance

atitsAmbergelectronicsplantinGermany,achievinga40%reductioninproductiondowntime.

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FigureAI’shumanoidrobotsran10-hourdailyshiftsfor5+monthsonBMW’sbodyshoplineinSpartanburg,SouthCarolina,contributingtotheproductionofmorethan30,000vehiclesacrossroughly1,250operatinghours.

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Theseareclearsignsofanindustrialparadigmbeingrebuilt

aroundAI.

TherealAIopportunityistheother~99.5%

TECHNOLOGYSECTOR

~$5tn+

SaaS

<$500bn

TOTALECONOMY

$100tn+

1213

~5%ofglobalGDP~0.5%ofglobalGDP

11

GlobalGDP

HARNESSINGAIFORTHEREALECONOMY6

01|ACONVERGENCEUNLIKEANYBEFORE:HOWAIISRESHAPINGTHEREALECONOMY

“We’reexperiencinguniqueparallel

momentsunfoldinginrealtime—buildingtheinfrastructurerequiredtoadvance

AI,whileAIisrewritingtherulesoftheglobaleconomy.”

MarkSorrell|GlobalHeadoftheIndustrialsGroupinInvestmentBanking

01|ACONVERGENCEUNLIKEANYBEFORE:HOWAIISRESHAPINGTHEREALECONOMY

HARNESSINGAIFORTHEREALECONOMY7

BaselineaggregateAICapExestimates

~$7.6tnofcapitalbetween2026and2031acrosscompute,datacenters,andpower

ComputeDataCentersPower

$1.01tn

$50bn

$765bn$300bn

$39bn

$232bn

$661bn$494bn

202620272028202920302031

Source:GoldmanSachsGlobalInstitute.14

$1.39tn

$65bn

$1.22tn

$59bn

$393bn

$1.07tn

$934bn

$808bn

$1.64tn

$73bn

$436bn

$1.58tn

$72bn

$433bn

$353bn

$1.13tn

CapitalatStake

Existingcapitalarchitecturesweredesignedforsequentialbuildouts,notparalleldemand.Traditionalinstruments—investment-gradecorporatebonds,syndicatedbanklending,projectfinance—cannot,ontheirown,simultaneouslyfunddigitalinfrastructureandAI

deploymentacrossindustries,exceedingwhatanysinglecategoryofcapitalcanefficientlyprovide.

Newinstrumentsareemerging.Privatecreditfacilitiesnowfinanceindividualdatacentercampusesexceedingonegigawatt—Vantage’s1.4gigawattTexascampus,financedin2025,anchorsthelargestdatacenterconstructionfinancingonrecordatover$25billion.

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Sovereign

wealthfundsandpensionfundshavemovedfrompassiveallocatorstodirectco-investorsupanddowntheentireinfrastructurestack.

SecuritizationofstabilizeddatacentercashflowsthroughAsset-Backed-Securities(ABS)andCommercialMortgage-BackedSecurities

(CMBS)isestablished;IGcapitalmarketsarenowfinancingdatacentersstillindevelopment,withinstitutionalinvestorstakingconstructionriskonAI-erabuildoutsatascalethatdidnotexistthreeyearsago.

Noonecanpredictwithprecisionhowthenextdecadeunfolds.Theheadlinefigurerestsonfoursupply-sideassumptionsthe

GoldmanSachsGlobalInstituteidentifiesassettingthescale:theeconomicusefullifeofAIsilicon,thecostandcomplexityofnext-

generationdatacenters,thechipandarchitecturemix,andelongationfrompower,labor,andequipmentbottlenecks.Modelswillimproveinwaysthatcannotbefullyanticipated,infrastructurewillbuildoutfasterorslowerthancurrentprojectionssuggest,andgeopolitical

forcesshapingcapitalflowswillintroducesurprisesnoframeworkfullyaccountsfor.Today’ssizingassumesexistingmodelarchitectureswilldefinetomorrow’scomputedemand—areasonablebasecase,butifworldmodelsscalealongsidelanguagemodelsratherthan

replacingthem,theactualtotalmayproveundersized.

“Thistransitionhasnodirecthistorical

precedentanddemandsadifferentkindofinstitutionalexpertisetonavigate.”

PeteLyon|GlobalCo-HeadoftheCapitalSolutionsGroup

SECTION02

TheNewIndustrialEconomy:WhereAIMeetstheRealWorld

Withthedigitalinfrastructurebuildoutunderway,AI’snextphasemovesintotherealeconomy—themanufacturing,construction,energy,andoperationalsystemsithasbarelybeguntoreach.Theinstrumentsthatfinancedigitalinfrastructurearemature;their

equivalentsforphysicalAIarenot.Howquicklythatgapcloses,sectorbysector,willseparatewhatcompoundsfromwhatstalls.

02|THENEWINDUSTRIALECONOMY:WHEREAIMEETSTHEREALWORLD

HARNESSINGAIFORTHEREALECONOMY9

I.Software:TheFirstDomainandEnterpriseShock

GoldmanSachsGlobalInvestmentResearchestimatesAIwillexpandthetotaladdressablemarketforautomationandenterprisesoftwarebyroughly2.5xoverthenextdecadeasagenticcapabilitiesextendsoftware’sreachintoworkthatwaspreviouslyhuman-only.

16

The

repricingunderwaytodayishappeninginsideacategorythatisstructurallygettinglarger,notsmaller.Thequestionforincumbentsisnotsurvival,butpositioning.

AIisnowrapidlydisruptingsoftwareitself,drivenbyAI-automatedcodegenerationandagenticworkflows.Unlikethecloudtransition,wherecategoryleadersprovidedaclearmigrationtemplate,theAItransitiondoesnotyetofferanestablishedplaybook.FewpubliclylistedsoftwarecompanieshavedemonstratedafullyAI-nativebusinessmodelatscale.Themarketdoesnotyethavecompletevisibilityintowhichincumbentswillrefoundthemselvesfirst,andtherepricinghasbeensignificant.

TheiSharesExpandedTech-SoftwareSectorETFdeclinedapproximately17%in2026throughJune,andabout26%fromitsOctober2025high,withthesector’s10largestholdingssheddingnearly$800billioninmarketcapitalizationoverthesamespan.ForwardP/Emultiplescompressedfromroughly35xinlate2025toabout22x,thelowestlevelsince2014.

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Regardlessoftheunderlyingfundamentals,that

uncertaintyhasdrivencapitaloutofenterprisesoftwareandintotheinfrastructurethatsitsbeneathit.

Thatsaid,thecompaniesreadingthismomentasarefoundingratherthanathreatarepullingahead.TheyshipAIcapabilitiesnativetotheirworkflows,disrupttheirownproducteconomicsdeliberately,andbuildtowardtheemergingvaluehierarchyratherthandefendingtheexistingone.

“Softwareisthecanaryinthecoalminefor

AIeconomics—whereAI’simpactonproductivity,pricing,andmarginstructureisappearingfirst.”

BrianCayne|Co-HeadofSoftwareInvestmentBanking

02|THENEWINDUSTRIALECONOMY:WHEREAIMEETSTHEREALWORLD

HARNESSINGAIFORTHEREALECONOMY10

PricingPowerMigrates

IntheSaaSera,theapplicationlayercommandedthepremium.Systemsorganizeddata,standardizedworkflows,andmonetizedaccessviaseats.Pricingpowersatwiththeapplicationlayer,whichownedthecustomerrelationship.Thatlegacyarchitecturenolongerholds.

Today,premiumismigratingtowardanoutcome-drivenarchitecture,organizedaroundthreecontrolpoints.Theoutcomelayerevaluatessoftwarebycompletedworkratherthanfeaturebreadthorseatcount.Theorchestrationandagentlayerfunctionsastheoperating

systemforenterpriseaction,governinghowworkroutesandwherereliabilityismaintained.Underpinningboth,thedataandcontext

layerdetermineswhetherAIbecomesgenericorindispensable:proprietaryworkflowhistoryandinstitutionalknowledgecarrythe

differentiationasmodelsbecomecommoditized.Trainingandinferencearesplittingintodifferenteconomiccategories.Trainingistheup-frontcapitalevent,whileinferenceistheoperatingcost—runningcontinuouslyacrosseveryuserinteraction—andwhereAIeconomics

ultimatelyresolve.ItisalsowheretheUS-Chinacostdivideismostvisible:ChinesemodelsserveinferenceatafractionofUSfrontierpricing,andthegaphasbeenwidening.State-backedproviderscanpricetowardcost,whereprivatecapitalmustpricetorecoupit.

TheChinaCostDivide

Themodellayeritselfisnolongerasingle-

geographystory.AlongsidetheUSlabsanchoringmostenterprisedeployments,Chinesedevelopershavealsopushedthefrontier’sedge.Established

platformssuchasAlibaba,ByteDance,Tencent,

Baidu,andXiaomihaveemergedalongsidefocusedlabsDeepSeek,Moonshot,MiniMax,andZhipu.

Severalopen-weightmodelsnowrankatornearthetopofglobalopen-modelleaders,servedatafractionoftheper-tokencost.BecauseinferenceiswhereAIeconomicsultimatelyresolve,thatcoststructurebearsdirectlyonhowthebuildout’s

computedemand—andcapital—getpriced

.18

ByOpenRouter’stracking,Chinesemodels’shareoftokenconsumptiononitsplatformhasclimbedfromlowsingledigitsinlate2024toroughly

halfbyearly2026.

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Buttokenvolumedoesnot

necessarilyequatetorevenue—asthemodellayercommoditizes,valuemigratesuptothedataand

outcomelayers—wheretheeconomicsconcentrate.

HARNESSINGAIFORTHEREALECONOMY11

CybersecurityasConnectiveTissue

Securityhasexpandedwitheverycomputinginfrastructureshift—fromdisconnectedsystemstotheinternet,fromon-premisetoSaaS,andnowtoAI.Eachtransitionmadethe“attacksurface”broaderandtheconsequencesoffailurelarger,andproducedsecurityleadersbuilt

specificallyforthenewarchitecture.TheAIshiftisthemostexpansionaryyet.Enterprisesmustmoveproprietarydataandoperational

contextoutoftheirownenvironmentsandintoexternalmodels,reversingdecadesofefforttokeepthatdatainsidethecompany’sownsystems.ThisshiftmakessecurityapreconditionforAIdeploymentratherthanacostlinewithinit,andthemarketispricingitaccordingly.

ThepatternthatdefinedcloudsecurityadecadeagoisnowvisibleinAIsecurityatcompressedspeed.ThecompaniesthatwilldominateAIsecurityinthe2030sarebeingfoundednow.ForinstitutionspositioningaroundtheAIeconomy,cybersecurityisnotjustavertical;ithasbecometheconnectivetissuefordeployment.

II.TheIndustrialAISoftwareLayer

AparallelrestructuringisunderwayinindustrialAIsoftware,theoperationallayerwhereincumbentsareembeddingAIintothetoolsthatdesign,simulate,andrunphysicaloperations.Itislessvisiblethanthesoftwaresell-off,butthescaleisgreater,astheoverlayisnotsector-specific.

Crucially,thislayerisenablingaconstantfeedbackloopwheretheworkproductitself(e.g.acarinproduction)communicatesreal-time

materialpropertiesbacktothemachinery.Thisenablesqualitycontrol,design,andprocessadjustmentssimultaneouslytoreducecostand

optimizeoutput.

Manufacturingoperators

aremovingfrom

scheduledmaintenance

topredictive.

Automotiveengineers

trainautonomousvehicle

modelsonsynthetic

datafromdigitaltwins.

Lifesciencesare

compressingdrug

discoveryandvirtualizing

trialdesign.

Energyutilitiesforecast

loadandoptimize

griddispatch.

Aerospaceintegrates design,testing,andmanufacturingintocontinuousplatforms.

02|THENEWINDUSTRIALECONOMY:WHEREAIMEETSTHEREALWORLD

SomeofthemostconsequentialplatformsareAI-nativeratherthanacquired.Palantir’sFoundryhasdeployedacrossmanufacturingatAirbus,energyatBP,anddefensefortheUSArmy’sProjectTITAN.Thecategoryisnowstandalone,notjustanincumbentacquisitiontarget.Major

industrialplayershavespentmorethan$110billionacquiringsoftwarecompaniesinthisspacesince2020,andthepaceisaccelerating.

20

TechandIndustrialsM&A($500mm+)continuetoseestrongYoYmomentum

$566bn

TechIndustrials

$334bn

$251bn

$200bn

$170bn

$115bn

$203bn$145bn

2023202420252026YTD

Source:DealogicasofJune3,2026.

02|THENEWINDUSTRIALECONOMY:WHEREAIMEETSTHEREALWORLD

DigitalTwinsastheFoundation

Underpinningthisoverlayisthedigitaltwin,avirtualrenderingofaphysical

asset,facility,orprocessbuilttohighfidelityagainstitsreal-worldcounterpart.In1970,NASAengineersusedaground-basedsimulatorofApollo13toisolatetheelectricalfaultthathadrupturedanoxygentank.Today,industrialoperatorsrunpersistentdigitaltwinsofentirefactories,modelingthecost,throughput,

andROIimplicationsofanychangebeforeit’smade.

FormulaOneoffersaclearproofofconcept.Racingteamsrundigitaltwinsoftheircars,simulatingthousandsoflapsbeforeracedayinarisk-free

environment,aimingtoclosethe“correlationgap”betweensimulationandreality.

Siemens’$5.1billionacquisitionofDotmaticsin2025sharpenstheindustriallogicfurther.

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Siemensalreadyownedmuchoftheequipmentthat

manufacturespharmaceuticalproducts;withDotmatics,itmovedupstreamintodesigningthem,usingAItosimulatedrugchemistry,compressdiscoverytimelines,andvirtualizethetrialprocessitself.Theacquisitionextends

digitaltwinarchitecturefromfactoryfloortolaboratorybench,andfromasingleindustryintothefirstend-to-endplatformspanningresearchthroughmanufacturingforlifesciences.

Recentstrategicactivityillustratesthisbroaderpattern.

Synopsys,Inc.’s$35billionacquisitionofAnsys(completedJuly2025),thelargestpure-softwareindustrialengineering

dealofthelastdecade,consolidatedsimulation,chipdesign,

andphysics-basedmodelingintoasingleplatformserving

semiconductors,aerospace,andautomotive.

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Emerson’s

roughly$17billionacquisitionofAspenTech,completedin

March2025withthepurchaseoftheremaining43%stake,

broughtprocesssimulation,assetperformancemanagement,

andindustrialAIsoftwareintoEmerson’sautomationportfolio

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Theseplatformsarebecomingthecontrolplane,andphysicaloperationsarereorganizingaroundthem.

TheM&Aconsequence:IndustrialAIsoftwareisnowan

acquisitiontargetcategoryonparwithenterprisedata

infrastructure,andsectorvaluationmultiplesarepricing

accordingly.Verticalintegrationistheunifyinglogic—eachacquirermovingupstreamorintoanadjacentlayertoownthefulltoolchainwithinitsdomainratherthanbuyingscaleacrossit—anditisemergingasanM&Acategoryinitsownright.Thefinancinginstrumentsthatworkfor

digitalinfrastructureextendtoindustrialAIsoftware.Thenextlayerofdeployment(humanoids,industrialrobots,autonomousfleets)ishardware.Thefinancingarchitectureforthatlayerdoesnotyetexist,butitwilllikelycomenext.

HARNESSINGAIFORTHEREALECONOMY12

02|THENEWINDUSTRIALECONOMY:WHEREAIMEETSTHEREALWORLD

HARNESSINGAIFORTHEREALECONOMY13

ThePhysicalAIStack—theBrainLayer

Unlikegenerativemodelstrainedontext,physicalAIrequiresmultimodaltrainingdata(video,forcefeedback,proprioception),historicallyscarceandexpensivetocollect.Thatscarcity

isbreaking.ThephysicalAIstackislayeredlikethesoftwarestack,butbuiltfromdifferent

components:AIbrainsonVision-Language-ModelandVision-Language-Actionfoundations,

simulationanddigitaltwinenvironmentsgeneratingsynthetictrainingdatathatreal-world

testingcannotmatchatscale,andpurpose-builthardware(lightweightactuators,adaptive

grippers,high-densitybatteries,specializededgecompute)thatprovidesmachinesthephysicalcapabilitytoworkalongsidehumans.Nvidia’sopen-sourceIsaacGROOTN1,launchedatthe

2025GPUTechnologyConference,exemplifiesthebrainlayer.

Aroundtheselayersanecosystemisassembling:chipmakers,cloudproviders,softwarefirms,sensorandcomponents,inadditiontospecializedconsultantsandintegrators.Companies

orchestratingmultiplelayersarepositioningtosetstandardsandcaptureoutsizedvalue.

Mobileye’searly-2026$900millionacquisitionofMenteeRoboticsisanexampleofthecross-layerconsolidationthefull-stackthesispredicts.

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WorldModelsastheEmergingFoundation

Thethree-layerstacknowhasanameinfrontierresearch:worldmodels.Worldmodelsrepresentcauseandconsequenceinphysicalandsocialsystems,acapabilityrequiredforhigh-valuedecisionslikecontrollingarobot,managingasupplychain,orcoordinating

enterpriseworkflow.Physicalworldmodelssimulategravity,friction,thermodynamics,andmaterialbehavior,unlockingrobotics,autonomous-system,andlogisticsapplications.Theyarebeingcommercializedatscaletoday,andrequirepurpose-builtsimulationenvironments,syntheticdatapipelines,andphysicsengines.

Socialorvirtualworldmodelssimulateinstitutionalandhumanbehavior,lettingfirmsrehearsecompetitivemoves,stress-testgovernancestructures,andmodelpolicyshocksbeforecommittingtoaction.Thesocialvariantsitsclosertothescenarioplanning

workinstitutionalallocatorsalreadydo,butitsinfrastructureisearlierandlessmature.Bothformspullonthesamecomputebase.

ConsensusforecastsforAIinfrastructure(compute,energy,andchips)tracktransformer-basedlanguagemodels.Worldmodels

complementlanguagemodelsratherthanreplacingthem.Iftheirtrajectoryholds,aggregatecomputerequirementsmayexceedwhatcurrentprojectionsanticipate,andthebuildoutthesisgainsasecondengine,alongsidelanguagemodels,thatthesizingworkhasnotyetpricedin.

“Afteradecadedefinedbysystemsthat

recognizepatternsandpredicttext,the

frontierofAIisshiftingtowardmodels

thatunderstandhowtheworldworks—aquietbutdecisivechangeinhowmachinesbecomeintelligent.”

GeorgeLee|Co-HeadoftheGoldmanSachsGlobalInstitute

02|THENEWINDUSTRIALECONOMY:WHEREAIMEETSTHEREALWORLD

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“Weareinthemiddleofani