2025技术融合报告（英）

IncollaborationwithCapgemini

TechnologyConvergenceReport

INSIGHT REPORT

JUNE 2025

TechnologyConvergenceReport

PAGE

2

Images:GettyImages,BostonDynamics

Contents

Foreword 3

Executivesummary 4

The3CFramework 6

Combination:Thefoundationoftechnologicalsynergy 8

Convergence:Reshapingvaluechainsforhigherreturns 9

Compounding:Exponentialecosystemimpactsthrough 11

scaledadoption

Eightadvancedtechnologydomains

14

AIdomain

16

Omnicomputingdomain

21

Engineeringbiologydomain

25

Spatialintelligencedomain

30

Roboticsdomain

35

Advancedmaterialsdomain

39

Next-generationenergydomain

44

Quantumtechnologiesdomain

49

Conclusion

54

Contributors

55

Endnotes

58

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June2025 TechnologyConvergenceReport

Foreword

AimanEzzat

ChiefExecutiveOfficer,Capgemini

JeremyJurgensManagingDirector,CentrefortheFourthIndustrialRevolution,

WorldEconomicForum

CathyLi

Head,AI,DataandMetaverse;MemberoftheExecutiveCommittee,WorldEconomicForum

Wearelivingthroughapivotalmomentintechnologicalhistorywheremultiplefoundationaltechnologiesarematuring,combiningandacceleratinginparallel.Fromartificialintelligence(AI)andquantumcomputingtobiotechnologyandadvancedmaterials,thisconcurrentmovementoftechnologiesisreshapingindustriesandsolvingproblemsoncethoughtimpossible.Whetherthesteamengine,electricity,thecomputeroreventheinternet,technologicalprogresshastraditionallybeenframedthroughthelensofindividualbreakthroughs.However,today’scomplexities

necessitatemovingtoasystems-thinkingapproach.

Technologicalprogresshashistoricallybeenframedthroughthelensofindividualbreakthroughs,though,asW.BrianArthur

observedinTheNatureofTechnology,innovationsrarelyevolveinisolation.Rather,theyemergefromcombinationsofexistingtechnologiestocreatenewpossibilitiesthatthemselvesbecomebuildingblocksforfurtherinnovation.

Thissystems-basedunderstandingofinnovation,whenlayeredwiththeWorldEconomicForum’sglobalmultistakeholderperspectiveandCapgemini’spracticalappliedinsights,ledto

thedevelopmentofthe3CFramework.Thisframeworkcaptureshowtechnologiesevolvethroughstagesofcombination,convergenceandcompoundinginanetwork-basedviewthathelpsorganizationsidentifyandcapturevalueattechnologicalintersections.

Theinsightsinthisreportdrawfrombothqualitativeandquantitativesources.TheTechnologyConvergenceCommunity,composedofsubjectmatterexpertsfromtheForum’sglobalnetwork

ofbusiness,academia,civilsociety,publicsectorleaders,provideddomainexpertiseandcaseexamples.ThiswascomplementedbyCapgemini’sglobalsurveyof2,000seniorexecutivesacross

18countries,10industriesandfivecontinents,offeringacomprehensiveviewofconvergencepatternsandorganizationalreadiness.Together,theseinsightswerecross-referencedwithexamplesofindustrytransformationandreal-worldcasestudiestouncovertheimplicationsofconvergenceforthefutureofinnovation,

competitivenessandpolicyplanning.Aseconomic,societalandclimateurgenciesgrow,decision-makersmustadoptafull-spectrumapproachtoinnovationthatmovesbeyondsegmentedthinkingandembracesthethoughtfulcombinationofmultipletechnologicalcapabilities.Recognizinghowintersectionaltechnologiesgiveriseto

newindustries,businessmodelsandeconomicparadigmsisessentialnotonlyfornavigatingthisrapidlychangingenvironmentbutalsoforunlockingnewpathwaysofvaluecreation.Byilluminatingthesetechnologicalinterdependenciesandtheirbusinessimplications,thiscollaborationaimstoequipleaderswiththeforesightneededtonavigateconvergencestrategically.

Executivesummary

Multiplefoundationaltechnologiesarematuringsimultaneously,creating

unprecedentedopportunitiesforthosewhounderstandtheircombinedpotential.

TheWorldEconomicForumhasdevelopedthe3CFramework,whichrevealsthepatternsdrivinginnovationtransformation.Itprovidesa

mapfornavigatingtoday’stechexplosion,wherebreakthroughsdon’tstandalonebutmerge

toreshapemarkets.

Technologiescombinetocreatecapabilitiesimpossiblethroughanysingleinnovation.

Valuechainsconverge,openingnewmarketpositionsandrevenuestreams.

Benefitscompoundasadoptionscales,acceleratingfurtherinnovationcycles.

TechnologyConvergenceReport 4

Inthecontextofthisframework,thisreportexamineshoweightpowerfultechnologydomains

–artificialintelligence(AI),omnicomputing,engineeringbiology,robotics,advancedmaterials,spatialintelligence,quantumandnext-generation(next-gen)energies–arecombiningtocreatevaluethatnosingleinnovationcoulddeliveralone.

Atotalof238technologysubcomponentswerematchedandfiltereddownto23combinationpatternswithestablishedapplicationsandprofoundrecentbreakthroughs.Theanalysisfocusedonmeaningfulintersectionsbetweentechnologicalsubcomponentsatdifferentmaturitystages.Thesecombinationswerechosenfortheirpotentialtoinfluenceinnovationtrajectoriesandhighlightstrategicopportunitiesacrossdomainsthroughconvergence.

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FIGURE1 Patternsoftechnologydomaincombinations–overview

Artificialintelligence

DistributededgeintelligencenetworksMulti-agentautonomy

Bio-inspiredprocessing

OmnicomputeDecentralizedintelligentsystemInternetofroboticthings(loRT)

EngineeringbiologyPrecisionbio-productionBiocomputationplatformCell-cultivationsystem

SpatialintelligenceSpatialprocessingImmersiveplatformDigitaltwinecosystems

Robotics

CognitiveroboticssystemsBio-inspiredroboticsSwarmroboticssystems

AdvancedmaterialsAdaptativematerialsmodellingBio-engineeredmaterialsEnergyoptimizationmaterials

Next-generationenergyIntelligentgridsystemRenewableenergystorageDecentralizedenergymarket

Quantum

Hybridquantum-classicalcomputingsystems

QuantumenhancedmeasurementQuantumcommunicationnetworks

Artificialintelligence Omnicompute Engineeringbiology Spatialintelligence

Robotics Advancedmaterials Next-genenergy Quantum

Thefutureliesinboldcombinations.Companiesthatstrategicallycombinetechnologiesatdifferentstagesofmaturityarepositionedtogain,especiallyascross-industryvaluechainsgiverisetoentirelynewproductcategoriesandbusinessmodels.

Byapplyingthe3Clens,organizationscanstart

identifyingthetechnologypairingsthatalignwiththeircorecapabilities,recognizingwhenshiftsinmaturitycreatenewmarketopenings,andinvestingstrategicallytounlockvalueasconvergenceaccelerates.

1

The3CFramework

Asystems-levelviewoftechnologyevolutionhelpsnavigatetransformationwaves–fromcombinatorialtocompounding–forstrategicandvaluecreation.

FIGURE2

The3CFramework’scirclesbuilduponeachother,creatingfeedbackloopsthatfurtherfueltechnologicaladvancementandmarketevolution

The3CFramework

Technologies

combine

Valuechains

converge

Compound benefitsemerge

Complementarycapabilitiescometogethertosolveakeyproblemorcreatenewsolutions

Functionalmergeofoverlappingcapabilities

Multiplicativeenhancementofcapabilitiesthatcancreateexponentialimpact

Marketadoptionincreaseswithhigh-priorityapplicationsstartingtobebuilt.

Specifictechnologiescometogether

Whentechnologiesconverge,theydriveeach

other’sevolutionandmaturity.

Valuecreationisdrivenbyperformancemultiplication,

costoptimizationand/ornewmarketpotentialviamarketoverlap.

Valuechainsconverge

Integrationwithothertechsubdomains

–viaapplicationprogramminginterfaces(APIs),platforms–leadtonewsolutionsbeingbuilt.Plug-and-playcapabilitiesareseen.

Ecosystembeginstoalignwithpartnernetworks,acceleratingadoptionandcompetition.

Ecosystemsevolve

Upstreamimpactsaffectsupplieroperations,costs,practices,skilldemandsandinputneeds,influencingpricing,resourcesandeconomicconditions.

Asspecific

sub-domainsmatureandadvance,applicationcostsdecrease.

Newstandardsbegintobeestablished(dataformatandavailability,integrationframeworks,qualitymetrics,

tech-stackprotocols).Commercialreadiness(partnerships,

capitalflowandinvestment,scalable

businessmodel).

Networkeffectsandmarketexpansionpotentialdriveunitcosteconomiesandtop-linegrowth.

Actorssearchingforcompetitiveadvantagerespond

byinvestinginR&Dleadingtogenesisofnewsub- domainsand/orpushingexistingsub-domainsfurther

downthecustom-to-product-to-commoditymaturitylevel.

Thiscreatesnew

demandsfromexisting technologiesandtheir

sub-domains.

Growthincompetitionandadoptioncreatenewdemandsfromthemarket.

TechnologyConvergenceReport 7

Inarapidlyevolvingtechnologicallandscape,multipletechnologicaldevelopmentsoccurinparallel,eachwithvariabletrajectories,impactpotentialsandadoptiontimelines.Thiscomplexitycreatesafundamentalstrategicdilemma:whichtechnologicaldevelopmentsdeserveimmediateattentionandinvestment,andwhichremaintooimmatureorisolatedtodrivesignificantbusinessvalue?The3CFrameworkoffersadynamicmodelforcapturingtheinterplayofcomplementaryinnovationsandunderstandinghowtechnologycreatesvalue,throughthreeinterconnectedstages:

Combination:Theintegrationofcomplementarytechnologiesbasedontheirlevelofmaturity

Convergence:Whenthesetechnologicalcombinationsallowfirmstomigrateandparticipateinnewvaluechains,thusconvergingexistingvaluechainsandallowingnewentrants

–Compounding:Whenvaluechainconvergencedrivesexponentialadoptionandcostreduction,creatingecosystemimpactsandenablingfurthertechnologicalcombinationsdownstream

Thisaddresseshowstrategicvalueemergesfromthemomentumofintegration,adoptionandscale,andhelpsprovideclarityonwhichcombinationsofferthegreateststrategicopportunities,howtheymayilluminatenewbusinessmodels,andwhentheyarelikelytoscaleanddeliverreturns.

Bysystematicallyanalysingtechnologydevelopmentthroughthelensofcombination,convergenceandcompounding,organizationscanidentifyemergingopportunitiesfaster,positionforadvantagewithinevolvingvaluechains,andcapturevalueadjacenttoscalingtechnologicaltransformations,aligningimmediatebusinessobjectivesandlong-termmarketpositioning.

Combination

Thefoundationoftechnologicalsynergy

TechnologyConvergenceReport 8

ThecombinationofAIandquantumtechnologyinvolvestheconvergenceofML,quantumalgorithms

andquantumcomputingtocreatenewsolutions.

Attheheartoftechnologicalinnovation

liescombination:theintegrationofdiscretecomplementarytechnologiestocreatesomethingfundamentallynew.Tounderstandthisprocess,it’sessentialtoconsidergranularity,orthedegreetowhichtechnologiescanbeanalysedatthe

sub-componentlevel.

Forexample–artificialintelligence(AI)isauniversaltermformanysubcomponentssuchasmachinelearning(ML),naturallanguageprocessing(NLP),largelanguagemodels(LLMs),neuralnetsandmore.WhenprogressinatechnologydomainlikeAIoccurs,itisoccurringatthesub-componentlevelastheyeachevolveatdifferentratespushingthetechnologydomainforward.Forinstance,

from2021tothepresent,massiveprogresshasoccurredintheNLP/LLMfieldwhichisoftencitedasanadvancementinAImoregenerally.Therealityismorenuanced;thedifferentsub-components

inthiscasegraphicsprocessingunits(GPUs)andLLMsmorespecifically–ofatechnologyhaveevolvedatdifferentratestocollectivelypushthetechnologydomainforward.

Moreimportantly,whentechnologiescombine,itisatthesub-componentlevel.ThecombinationofAIandquantumtechnologyinvolvestheconvergenceofML,quantumalgorithmsandquantum

computingtocreatenewsolutions.Quantumalgorithmsareusedtosimulatephenomena

(suchaselectronicstructures,rovibrationalspectra)attheatomisticlevel,whileAI/MLisusedforanalysesandsimulationsofmolecularphenomena(macromolecularstructures,intermolecularforces).Thus,quantumMLblendsmodelsacrossbothscales–atomisticandmoleculartoderivenewinsightsintohowmaterialsareconstructed,orhowtomodifythemtomakethemmoresuitablefor

real-worldapplications.

While,intheory,manytechnologiescanbecombined,notallcombinationsproducemeaningfuloutcomes.Anobservationfromthisworkisthat

themostvaluablecombinationstendtoinvolveaninterlockoftechnologiesatdifferentmaturitylevels–forexample,pairingexperimentalinnovationswithstable,scalableinfrastructure.Thesecombinationsstrikeabalancebetweennoveltyanddeploymentreadiness.

Allocatinglimitedresourcesacrossthesematuritylevelsrequiresadisciplinedapproachtotechnologyassessmentthatgoesbeyondtraditionalreturnoninvestment(ROI)calculations,requiringabalancedportfolioapproachthatconsidersfuturevalueandbusinessmodelinnovationpotential.

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Convergence

Reshapingvaluechainsforhigherreturns

forrepetitive,rule-basedtasks.Asthissegmentmatures,firmsfaceflatteningperformancegainsandshrinkingdifferentiationopportunitiesfromfurtheriteration.Theeconomicimperativetofindnewgrowthvectorsispushingcompaniestoexploreadjacentmarketsandplatforms.

Valuechainexpansionwithinexistingmarkets

Techcombinationenablesorganizationstoextendtheirfootprintacrossanexistingvaluechain,capturingadditionalmarginfromexistingcustomerrelationshipswhilelimitingcompetitiveexposure.

CASESTUDY1

BlueOceanRobotics

Ratherthanremainingconfinedtotraditionalhardwaremanufacturing,BlueOceanRoboticsadaptedtheirproductwithAIandspatialcomputingcapabilitiestoextendtheirofferingstoincludecollaborativesolutionarchitecturesandjointdevelopmentprocesseswiththeirpartners.1,2

Thisstrategicevolutionhastransformedthemfromacomponentsuppliertoa

full-serviceinnovationpartner,significantlyincreasingrevenuepercustomerwhiledeepeningstrategicrelationships.Byexpandingacrossthevaluechain,theynowcaptureservicerevenue,integrationfeesandongoingoptimizationvaluethathardware-onlyplayerscannotaccess.

Whiletechnologicalcombinationcreatescapabilityadvantage,convergencetranslatesthisadvantageintorevenuegrowthbyreshapingvaluechainsandopeningnewmarketopportunities.Fordecision-makers,convergencerepresentsthecriticalphasewheretechnologyinvestmentsbegingeneratingtangiblebusinessreturns.

Convergenceoccurswhencombinatorialcapabilitiesmergewitheconomicincentivestotranscendtraditionalindustryboundaries,dissolvingestablishedsilosandforginginterconnected

valuechains.

Marginexpansionopportunities:Newintegratedtechnologysolutionstypicallycommandpremiumpricingcomparedtomono-componenttechnologies,creatingpowerfulincentivestoexpandbeyondtraditionalvaluechainpositions.

Recurringrevenuepotential:Solutionsthatharnesstechnologicalcombination,inmostcases,enablesubscriptionandservice-basedmodelsthattransformone-timesalesintorepeatable,long-termrevenuestreams.

Customerrelationshipdepth:Combinedtechsolutionsaddressmorecomplexcustomerneeds,creatingdeeperengagementandhigherlifetimevalue.

Competitivedifferentiation:Providingcombinedtechnologysolutionsprovidessustainabledifferentiationthatpreservespricingpower.

Theroboticsmarketservesasaprominentexampleoftheformsofnewvaluecapture.Industrialrobots,onceacoredriverofautomation,nowdeliverdiminishingmarginalreturns.Mostoperatein

highlycontrolledenvironmentsandareoptimized

Newcategorycreationthroughcross-industryconvergence

Moretransformativevaluechainconvergencesoccurwhenentirelynewproductcategoriesaremadebycombiningtechnologiesinways

thatredefinemarketboundariesandaddresspreviouslyunsolvablechallenges.

CASESTUDY2

HumanoidrobotsinChina

Recentbreakthroughsinvision-language-actionmodels(VLA),spatialintelligencealgorithmsandcross-domainsystemsintegrationhaveunlockednewpossibilitiesforhumanoidrobotics.VLAmodelsandAIagentsnowenablerobotstointerpretmultimodalinstructions,learnfromdiverseinputsandmakeautonomousdecisionsincomplexsettings.Meanwhile,innovationsinspatialintelligencesuchasGaussiansplattingandspatialreasoningallowmachinestoperceiveandnavigatehumanenvironmentswithgreater

precisionandadaptability.Finally,technologiesfromadjacent

industriesincludingmobilitycontrol,sensorfusion,batterysystemsanduserinterfacedesignarebeingrecombinedtosupportthephysicalformandreal-worldfunctionalityofhumanoidrobots.

Inresponse,Chinesefirmsfromsectorssuchasconsumerelectronics,dronesandautonomousvehiclesarerepurposingtheirexistingcapabilitiestobuildhumanoidplatformsthatcanoperateinunstructured,everydayenvironmentslikehomes,hospitalsandwarehouses.

TABLE1 TransitionofcorecompetenciestohumanoidsforChinesefirms

Company

Corecapabilities

Humanoid-enablingcapabilities

Xiaomi

Consumerelectronicsminiaturization,batterysystems,userinterface(UI)/userinterface(UX)design

Physicaldesignandintegrationofhumanoidhardwarewithintuitivehuman-machineinterfaces,connectedtohomeecosystems

DJI

3

Droneflightcontrol,sensorfusion,autonomousnavigation

Navigationandreal-timeenvironmentalawarenessformobilerobotsandautonomoussystems

LiAuto

4

Vehicleautonomysystems,MindGPTAImodels

Multimodalreasoning,commandinterpretationandautonomyindynamicphysicalsettings

Baiduand

UBTech

5

AIexpertise,Apolloautonomousdrivingplatform

Humancommandinterpretationandcomplexenvironmentnavigationforgeneral-purposehumanoids

InChina,thiscross-industryconvergenceisdrivingremarkableeconomicefficiencies.Today,buildinganidenticalroboticarmintheUS(e.g.UniversalRobots’UR5e)costsapproximately2.2timesmorethaninChina,6largelyduetoChina’scloselynetintegratedmanufacturingecosystem.Astheworldmovestowardsincreasedautonomationwhererobotsmanufactureotherrobots,7thiscost

advantage,combinedwithcross-industrycapabilitysharing,isacceleratingthehumanoidmarketdevelopment–withprojectionsshowinghumanoidrobotshipmentsgrowingfrom18,000unitsin2025toover1millionby2030.8

Fororganizationsnavigatingconvergenceopportunities,severalcriticalquestionsmustguidetheirstrategicpositioningthinking:

Valuechainleverage:Whichpositionsprovidemaximumleverageoveremergingvaluechainswhilebuildingonexistingorganizationalstrengths?

Integrationeconomics:Wheredoestechnologyintegrationcreatesufficientvaluetojustifypremiumpricingandmarketdevelopmentinvestments?

Capabilityrequirements:Whatnewskills,partnershipsandorganizationalstructuresareneededtoexecuteeffectivelyinconvergedvaluechains?

Markettiming:Whenwilltechnologicalcombinationsolutionsreachsufficientscaletodeliversignificantreturnsonstrategicinvestmentsandjustifytheefforttomigrateintoneworadjacentvaluechains?

Organizationsseekingtoexcelatidentifyingandcapturingconvergenceopportunitiesmustmaintaindisciplinedfocusoneconomic

fundamentalswhilecontinuouslyevaluatinghowtechnologicalevolutioncreatesnewvaluechainpositioningoptions.Theyneedtorecognizethatsuccessfulconvergencestrategiesbeginwith

aclearunderstandingofcustomereconomicsandvaluecreationpotential,ratherthanover-focusingontechnologicalcombinationsalone.Bysystematicallyanalysinghowtechnologycombinationsreshapevaluechains,leaderscanidentifyemergingrevenuestreamsbeforecompetitorsrecognizethesameopportunities,positioningtheirorganizationstocapturedisproportionatevalue.

Thisisexemplifiedtodayinthehealthcareindustry,whereorganizationsarecombininggenomicsequencingtechnology(custom),AIdiagnosticmodels(product)andelectronichealthrecordsystems(commodity)tocreatepersonalizedtreatmentprotocols(Figure4).Solutionssuch

asUPMC’sEnhancedDetectionSystemforHealthcare-AssociatedTransmission(EDS-

HAT),whichcombinesMLwithwholegenomesequencingandEHRdata,aresavinghospitalsasmuchas$700,000overatwo-yearperiodthroughimprovedinfectioncontrol.9

Compounding

Exponentialecosystemimpactsthroughscaledadoption

Onceconvergencetakeshold,compoundingeffectsdriveexponentialadoptionandcostreductions.Thecompoundingstagetransformspromisingconvergenceplaysintomarket-definingforcesthroughscaleeconomics,networkeffectsandecosystemdynamics.Tworeinforcingmechanismsdrivecompoundingeffects:

1

Firm-levelscaleeconomics:Ascombinedtechsolutionsgainmarketadoption,organizationsbenefitfromtraditionalscaleeconomics,including:

Productionefficiencies:Unitcostsdeclineasfixeddevelopmentcostsarespreadacrosslargervolumes.Forexample,alogistics

companydeployingAI-enhancedroboticsmightslashdeliverycostsby25%asadoptionscales.

Learningeffects:Performanceimprovesasorganizationsaccumulateimplementationexperience.Inthesameexampleasabove,thelogisticalcompanyusingroboticsusesthedataitcollectstorefineitsAI,furtherboostingefficiency.

Businessmodelinnovation:Theabovechangesimpactthescalingcapabilitiesoftheearlyadopter,enablingnewpricinganddeliverymodels,notpossibleatlowervolumesorforotherecosystemactorstomatch–unlesstheyadoptthesametactics.

Ecosystemnetworkeffects:Beyondfirm-levelbenefits,compoundingcreatespowerfulecosystemdynamicsthatfurtheraccelerateadoptionandvaluecreation:

2

Standardsemergence:Assolutionsscale,defactostandardsemergethatreduceintegrationcosts.

Complementaryinnovation:Thirdpartiesdevelopcomplementaryproductsandservicesthatenhancecoresolutionvalue.

Supplychainmaturation:Specializedsuppliersemergetodelivercomponentsatlowercostsandhigherquality.

Regulatoryadaptation:Governanceframeworksevolvetoaccommodatenewtechnologies,reducingcomplianceuncertainty.

Strategyleaderswhorecognizetheseecosystemdynamicscanpositiontheirorganizationstocapturedisproportionatevaluebyestablishingpositions

thatbenefitfromcomplementaryinnovationsorbycreatingdependenciesthatleadtolong-termcompetitiveadvantage.

CASESTUDY3

Theelectricvehicleecosystem

Thecompoundingeffectsinelectricvehicle(EV)adoptionillustratethesedynamics.Initialadoptionfacedchallengesofhighvehiclecosts,limitedrangeandinadequatecharginginfrastructure.Asadoptionhasscaled,batterycostsdeclinedby90%overthepast15years,10chargingnetworksexpandedfromisolatedcorridorstocomprehensivecoverage,andregulatoryframeworksevolvedtosupportelectrificationthroughincentivesandstandards.

Organizationsthatrecognizedthesecompoundingdynamicsearlysecuredadvantageouspositionsinestablishingbatterymanufacturingscale,securingcriticalmineralsupplychainsanddevelopingproprietarychargingtechnologiesthatcreatedlastingcompetitiveadvantagesasthemarketmatured.

Forexecutivedecision-makers,thecompoundingphaserequiresstrategicpatiencecombined

withaggressiveexecution.Theymustmaintaininvestmentthroughearlyadoptionchallengeswhileconstantlyoptimizingforscaleasmarketsdevelop.Organizationsthatmasterthisbalanceachievewhatappeartobe“overnightsuccesses”thatactuallyresultfromyearsofstrategicpositioningforinevitablecompoundingeffects.

Compoundingshouldnotbeviewedasafinalstageofaprocessbutasacatalystforthenextwaveoftechnologicalcombinationsthatcreatesaself-reinforcingcycle.

Thecycleactivateswhencompoundingstandardizationsinspirefirmstoseeknewtechnologicalcombinations,otherwiseknownas“TheInnovator’sDilemma”.Earlyadoptersofconvergedtechnologieswhocapturedpremiummarginsfindtheircompetitiveadvantages

graduallyreducedastechnologiesbecomewidelyavailableatdecreasingcosts.Standardization

isbeneficialfortheecosystembutpresentsastrategicchallengeforindividualcompaniesseekingcontinueddifferentiation.

NVIDIAexemplifiesthiscycle.Asgeneral-purposeGPUsbecamestandardforAItraining,NVIDIArecognizedtheneedfornewcombinationstomaintainitsmarketadvantage.ThecompanyinvestedheavilyincombiningitshardwareexpertisewithspecializedAIsoftwareframeworks(CUDA,cuDNN)andapplication-specificintegratedcircuits.ThisstrategicpivottowardsnewcombinationsallowedNVIDIAtocapture

extraordinaryvalueasAIcompoundingaccelerated

–increasingitsmarketcapitalizationfromapproximately$300billiontoover$3trillioninjustthreeyears.Similarly,asLLMsreachcompoundingscaleandstandardizethroughapplicationprogramminginterface(API)access,companieslikeAnthropicandOpenAIarealreadypursuingnewcombinations–integratingLLMswithagentarchitectures,specializedreasoningcapabilitiesanddomain-specifictrainingtechniques–tocreatethenextwaveofdifferentiatedAIapplications.

FIGURE3 3CsinthecontextofAI–acontemporaryillustration

Firstcycle(mid-2010sto2021)

Secondcycle(current)

Technologiescombine

Cloudcomputinginfrastructurecombinedwithmachinelearningalgorithms.

Technologiescombine

Foundationalmodels(FMs)arebecomingcommodities.Todif