2026分布式 AI 洞察报告：网络运营商下一个增长前沿

FUTURIOM

FUTUREOFCLOUDTECH

NetworkingInfrastructureforAlLeadershipBrief

Sponsoredby:

EQUINIX

DistributedAl:TheNextGrowthFrontierforNetworkOperators

Highlights:

·Artificialintelligenceistransformingnetworksintostrategicassetsthatconnectdistributedcompute,data,andinferenceworkloadsacrosscloud,datacenter,andedgeenvironments.

·AsAlbecomesmoredistributed,itwilldrivetheneedforlow-latencynetworking,opticalinterconnection,edgeinfrastructure,built-insecurity,andsovereignAlarchitecturesthatcanhostcomputeandotherinfrastructureclosertousersandenterprisedata.

·ThegrowthofAlservicesandinfrastructureisalsocreatingmorecomplexhybridcloudanddistributedAlenvironments.

·NetworkoperationsleadersmustadapttomakesurenetworksshouldsupportAl一

technically,commercially,andoperationally—whilenavigatingconstraintssuchasdigitalsovereignty,returnoninvestment,andreadinessofexistinginfrastructure.

·Networkoperatorsandcolocationprovidershaveanopportunitytodrivenewrevenue

servicesbyenablingfastprovisioningofsecureconnectivitytoglobalinfrastructuretoenableAlservicesandinfrastructure.

·BasedonananalysisofAldeploymentdataandcasestudies,Futuriomidentifiesthree

strategicrolesforoperatorsintheAlera:Alenabler,Alserviceprovider,andAl-powerednetworkoperator.

TechPrimer:AgenticOperationsforInfrastructure

1.Intro:NewOpportunitiesforDistributedAI

Systems

Artificialintelligenceischangingtheneedsandarchitecturesofnetworkinginfrastructure.AsAI

workloadsevolvefromcentralizedmodeltrainingtowarddistributedinferenceandagenticsystems,networkconnectivitywillneedtorespondquicklytoAI-drivenapplications,ratherthanjustprovidingpassivetransportsystems.

AIapplicationsincreasinglyrequirelow-latencyconnectivitybetweenclouds,datacenters,edge

infrastructure,enterpriseenvironments,anddistributedGPUclusters.Thistransitioniscreating

structuralchangesinhowoperatorsthinkaboutconnectivity,interconnection,andservicedelivery.

Newclassesofnetworkinginfrastructureareemerging.Thisincludesultra-high-capacityoptical

transport,AIinterconnectionfabrics,edgeinferenceconnectivity,andsovereignAIdeployment

models.Butitreachesbeyondthat.ManyenterprisesregardtheirproprietarydataandAIsystemsastheir“crownjewels,”andtheyareeagertolockdownownership,security,andcontrolovertheirowndata.Atthesametime,geopoliticaldemandsareincreasingtheneedfordigitalsovereignty.

Globalnetworkoperatorsarealwaysseekingopportunitiestobemorethanjusttransportpipes—

andhereinliesagrandopportunity.TheycanplaytheroleoftrustedprovidersofcriticalAI

infrastructure.WithenterpriseinfrastructurearchitectsfrequentlycitingnetworkinfrastructureasabottlenecktoconnectingAIsystems,operatorscaneffectivelyhelpcustomersovercomethis

bottleneckwithmoredynamicandresponsivebandwidthandcomputeinfrastructure.

FuturiombelievesoperatorsmustnowevaluatewheretheyparticipateinthedistributedAIvalue

chain.SomewillfocusonenablingAIthroughconnectivityandinterconnection.Otherswillpursue

sovereignAIhostingandAIinferenceservices.ManywillincreasinglydeployAIinternallytoautomateoperationsandimprovenetworkefficiency.

InthisLeadershipBrief,we’lldiscussthechangeandopportunitythatAIisbringingtonetworkoperations,aswellasthreesuccessfulrolesthatnetworkoperatorscanplayintheAImarket:AIenabler,AIserviceprovider,andAI-powerednetworkoperator.

TechPrimer:AgenticOperationsforInfrastructure

2.TheDistributedNeedsofAIInfrastructure

AIworkloadsarecreatingnewtrafficpatternsandinfrastructurerequirementsacrossthenetwork.LargeAItrainingclustersgenerateenormouseast-westtrafficbetweenGPUs,storagesystems,andcomputefabrics.Meanwhile,AIinferenceisincreasinglymovingtowarddistributedenvironmentsclosertousersandenterprisedatasources.

Thisshiftisunfoldinginseveraldimensions:

•AIapplicationsincreasinglyrequirereal-timeinferenceandlowlatency.

•Datagravitylimitsthepracticalityofcentralizedarchitectures.

•Sovereigntyandgovernancerequirementsfavorregionaldeployment.

•EnterpriseAIapplicationsincreasinglyoperateacrosshybridenvironments.

Theresultisgrowingdemandfordistributedinfrastructurearchitecturescombiningcloud,colocation,telecom,andedgeresourcesintointerconnectedAIplatforms.

Thisisacceleratingtheshifttowarddistributedinferencearchitectures,wherelatency-sensitiveAI

workloadsmustbeexecutedclosertousersanddatasourcesratherthanincentralizedenvironments.

DistributedInfrastructureMeansHybridInfrastructure

ThedistributednatureofthesenewAIplatformsmeansmorenetworksconnectingmorecloudsandenterpriseinfrastructure.Thesenetworksincreasinglydemandsoftware-drivenmanagement,APIs,andglobalconnectivitypointswithglobalcolocationpointsclosetoonrampstothemajorcloud

providers.

InoneexamplestudiedbyFuturiom,S&Pbuiltahybridmulticloudnetworkinfrastructurethatcouldintegratenetworkserviceworkflowsacrossthreecloudproviders.Inanother,aglobalfinancialfirmengagedwithanetwork-as-a-serviceproviderthatenabledaglobalnetwork,deliveredusingcloudinfrastructure.

Accordingtodatafrommorethan100hybridcloudcasestudiescompiledbyFuturiom,keybenefitsofhybridcloudinfrastructureincludeoperationalefficiency,security,costoptimization,fasterappdevelopment,andresiliency.Thedatabelowindicatesthecharacteristicsmostoftencitedin

enterpriseimplementationswehavetracked:

TechPrimer:AgenticOperationsforInfrastructure

KeyBenefitsofHybridCloudImplementations

OperationalefficiencySecurity

CostoptimizationFasterappdevelopmentBetterresiliency/failover Businessinsights CustomerExperienceMulticloudinfrastructure

60

FUTURIOM

FUTUREOFCLOUDTECH

Source:FuturiomCloudTrackerPro

It'sclearfromthemanydeploymentsthatwehavestudiedthathybridcloudinfrastructureisgainingmomentumintheAlerabecauseofawidearrayofbenefits.

Networkandinfrastructurearchitectsnolongerwanttheirinfrastructuretobenaileddown.Theywantadynamic,responsive,andresilientinfrastructurethatisalsoprivateandsecure.

SovereigntyandSecurity

Evenifacustomerisleveragingpubliccloudinfrastructureorpartnerassets,thatdoesn'tmeanthatsecurityisnotaconcern.InthemovetoAl,datasecurityandsovereigntyarebecomingparamount.

TheInternationalAssociationofPrivacyProfessionals(IAPP)reportedthatdataprotectionlawswereineffectin144countriesasofearly2025.Its2026updatesays179of240analyzedjurisdictionshave

data-protectionframeworks,coveringroughly80%oftheworld'spopulation.TheEUDataActbecameapplicablefromSeptember12,2025,andincludescloud-switchinganddata-transferprovisions,

reinforcingpressureoncloudproviderstosupportportability,dataaccess,andjurisdictionalcontrol.

Moredatasovereigntyappearstobeontheway.Forexample,ReutersreportedonJune1,2026,thattheEUispreparingcloudandAlrulesaimedatstrengtheningtechnologicalsovereigntyinstrategic

TechPrimer:AgenticOperationsforInfrastructure

sectorssuchasenergy,healthcare,andbanking.Thegraphicbelowshowstherelativedensityofdataregulation,accordingtolawfirmDLAPiper.

HeavyRobustModerateLimited

Relativeglobaldataregulationandenforcement.Source:DLAPiper

Networkprovidersnowneedtoprovidesecureprivateinfrastructureondemand,aswellasflexibilityinlocatingcomputeanddataassetsincompliancewithdatasovereigntylaws.Governmentsand

enterprisesincreasinglywantAlsystemsdeployedwithinspecificgeographic,legal,andoperationalboundaries.ThistrendisespeciallyimportantinEurope,aswellasinheavilyregulatedindustriessuchashealthcare,finance,anddefense.

SovereignAlchangestheeconomicsofinfrastructurebecauseitrequirescomputeandinferencetobeevenmoredistributedacrossregionalfacilitiesinsteadofconcentratingworkloadsentirelywithin

hyperscalecloudregions.

Thisnewenvironmentcreatesnewopportunitiesforinfrastructureprovidersthatcanconformtodatasovereigntyrequirements.

Companiespositionedtoprovidetheseservices:

·Telecommunicationsoperatorswithregionalinfrastructure

·Colocationproviderswithdistributeddatacenterfootprints

·Networkoperatorswithlow-latencymetroconnectivity

TechPrimer:AgenticOperationsforInfrastructure

•Infrastructureproviderswithtrustedoperationalmodels

ColocationproviderssuchasEquinix,aswellasmajortelecomproviders,areincreasinglypositioningthemselvesaroundthesetrendsbyemphasizinginterconnectionecosystems,AI-readydatacenters,andregionaldeploymentcapabilities.

Atthesametime,distributedAIarchitecturesareintroducingnewrequirementsforgovernance,

orchestration,andsecurityacrossincreasinglyfragmentedenvironments.Networkoperatorsarewellpositionedtoaddressthesechallenges,buildingontheirexistingroleindeliveringsecure

connectivity,trafficcontrol,andpolicyenforcementacrossdistributedinfrastructure.

AsAIenvironmentsbecomemorecomplex,thesecapabilitiesnaturallyextendtowardenablingend-to-endcontrol,security,andoperationalgovernanceacrossdistributedAIsystems.Thisincludes

managinghowdata,workloads,andinterconnectionsaredeployedandsecuredacrossregions,whilemaintainingcompliancewithsovereigntyrequirements.

Emerginginfrastructureframeworksprovidetheplatformfoundationforthesecapabilities,but

operatorsbringthedomainexpertisetotranslatethemintotailored,operationalservicesfor

enterprises.Together,thiscreatesamodelwheredistributedAIplatformsandnetworkprovidersjointlyenablesecure,compliant,andwell-governedAIdeploymentsatscale.

FuturiombelievessovereignAIanddatasecuritymaybecomethemostimportantdriversof

distributedinfrastructureinvestmentoverthenextseveralyears—whilealsocreatingagrowing

opportunityfornetworkoperatorstoextendtheirrolebeyondconnectivityintoenablingsecure,well-governeddistributedAIenvironments.

FlexibleandAutomatedOperations

AIisalsobecomingincreasinglyimportantinsidenetworkoperationsthemselves.

Moderninfrastructureenvironmentsarebecomingtoodistributedanddynamicfortraditional

operationalmodels.AIworkloadsgenerateunpredictabletrafficflows,dynamicresource

requirements,andincreasinglycomplexinterdependenciesacrosscloudandnetworkinfrastructure.

OperatorsareincreasinglyapplyingAIto:

•Detectanomalies

•Predictfailures

•Optimizerouting

•Improvesecurityresponse

TechPrimer:AgenticOperationsforInfrastructure

•Reducemeantimetorepair

•Improvecustomerexperiencevisibility

AccordingtoNVIDIA’srecenttelecomAIsurvey,90%ofoperatorsreportedthatusingAIinoperationshelpedincreaserevenueorreducedloss.

AgenticOperationsAreNext

Theevolutiondoesn’tstopatAI-assistedoperations.Themarketisquicklymovingtofullagenticoperations,whichdiffersfromtraditionalautomation.

Innetworkandcloudoperations,typicalautomationincludescommonscriptingandinfrastructureautomationtoolssuchasChef,Ansible,andTerraform.

Agenticoperationstakethingsastepfurtherandemploytheirownreasoning.Ifthesystemis

respondingtoyou,it’sachatbot.Ifit’srespondingforyoubymakingdecisions,callingtools,andretryingthings—that’sanagent.

3.AdoptionStrategies:ExamplesfromRecentCase

Studies

FuturiombelievesthenextevolutionofnetworkinginfrastructurewillfocusonhowfastitusesAItools,includingagenticoperations,tousereasoningandcontexttorespondtochangingneeds.Inotherwords,orchestratingnetworkswithAI-optimizedsoftwarewillbecomemoreimportantthanever.

FuturiomrecentlyexaminedasetofcompellingcasestudiesfromEquinixthatdemonstratethe

benefitsofmoreflexibleandresponsiveinfrastructuretoleverageAIapplications.Let’stakealookatafewofthemoreinterestingones.

Zayo:High-performanceNetworkBackbone

ZayochosetopartnerwithEquinixtodeliveranewsolutioncombiningZayo’s400G-enablednetworkbackbone,whichoffersfourtimesthecapacityof100G,withEquinix’sAI-optimizeddigital

infrastructureavailablein45+globalmetros.

ThisgivesenterprisesdirectaccesstoZayo’s19.1Mfiber-milenetworkforIP,Ethernet,and

Wavelengthnetworkingneeds.Today,Zayo’scoreWavelengthNetworkis100%400G-enabledacross

TechPrimer:AgenticOperationsforInfrastructure

NorthAmerica,helpingenterprisesmovemoredatafaster.Thiscanalsoaccelerateenterpriseconnectivitybyprovidingsimplifiedaccessatkeylocations.

Currently,16EquinixdatacentersarepartofZayo’sQuickConnectprogram,whichoffersfaster,moreseamlessaccesstohigh-capacitybandwidth.ThismeetsthegrowingdemandfromtheAImarketforelasticopticalconnectivityprovidedondemand.

MerckKGaA:HPCforLifeSciences

MerckKGaA,basedinDarmstadt,Germany,lastyearlaunchedastate-of-the-arthigh-performancecomputer(HPC)builtonLenovoThinkSystemserverswithindustry-leadingliquidcoolingtechnology.TheHPCishostedwithinanEquinixAI-readydatacenterinGermanyandhasbeendesignedto

accelerateinnovationacrossthethreebusinesssectorsofMerckKGaA:lifescience,healthcare,andelectronics.ThisinitiativeunderscoresthecommitmentofMerckKGaAtodigitalinnovationasakeyenablerofscientificdiscovery.

Onenovelelementofthisplatformisthatitcombinesprivateandpubliccloudinfrastructure.The

hybridclouddesignalsooffersflexible,rapidscalingtomeetvaryingcomputationaldemands.Usinghigh-performancecomputing,MerckKGaAaimstoenhanceproductdevelopmentinlifescience;

streamlinedrugdiscoveryprocessesinhealthcare;andoptimizethedevelopmentofnew,cutting-edgematerialsforthesemiconductorindustryinelectronics.Thisunifiedapproachleadstomorepreciseandtailoredsolutionsfortheuniquechallengesfacedineachsector,minimizing

fragmentationandfosteringcollaborationacrossteams.

Continental:ProcessingTBsofDataforAdvancedDriverSystems

Continental’sAdvancedDriverAssistanceSystems(ADAS)teamneededtoprocessmorethan150

terabytes(TB)ofdatatoinformdesigndecisionsthatwouldincreaseconnectedandautonomous

vehiclesafety.Continentalleveragedcarbon-neutralAIinfrastructure,includingPlatformEquinix,to

buildandinterconnectitsAI-drivenNVIDIADGXgraphicsprocessingunitclusterandIBMElastic

StorageSystem3000—reducingAItrainingtimetoaugmentsafetystandardsfromweekstodays.Thisapproach,featuringreal-timedataaccessforscalable,future-proofAI,boostedperformanceto

acceleratedeployment,enablemoreexperimentswithsecuredataprotection,andenhancedataprivacycontrols.

Zetaris:ALakehouseforAgenticAI

Zetarisprovidesalocation-agnosticmodernlakehouseforAI,seamlesslyconnectingtodatawhetheritresidesattheedge,inadatacenter,orinthecloud.Throughitsinnovativelakehouseplatform,

ZetarisaimstoacceleratethedevelopmentofAIapplications,includingagenticAI.Traditional

infrastructurestrugglestosupportitsrapidlyexpandingcustomerbase,diversedatasources,andresource-intensivequerytechnologies.

TechPrimer:AgenticOperationsforInfrastructure

Equinix'sdistributedAIinfrastructuresolution,whichcombineshigh-performancedatacenterswith

low-latencyinterconnection,enabledZetaristoprovidereal-timedataandAIcapabilitiesinasecureandscalableenvironment.Theinnovativeapproachhasresultedinperformanceimprovementsofsixtimesfasteratone-thirdofthecost.

“LeveragingEquinix’sglobalfootprintanddenseecosystemsofcloudandnetworksallowsusto

deliverreal-timedataandAIcapabilitiesinasecureenvironmentandscaleaccordingtoourcustomerneeds,helpingcustomerstransformoperations,boostproductivity,andenhancecustomer

engagement,”saidVinaySamuel,theFounderandCEOofZetaris.

“LeveragingEquinix’sglobalfootprintanddenseecosystemsofcloudand

networksallowsustodeliverreal-timedataandAIcapabilitiesinasecure

environmentandscaleaccordingtoourcustomerneeds,helpingcustomers

transformoperations,boostproductivity,andenhancecustomer

engagement.”

--VinaySamuel,theFounderandCEOofZetaris.

4.StrategicRolesforNetworkInfrastructureinthe

AIEcosystem

Aswehaveshownwithsomeofthecasestudiesabove,thenetworkisastrategicassetforbuildingAIanddata-heavyapplications.ThetransitiontowarddistributedAIinfrastructurecreatesamajor

opportunityfornetworkingprovidersbecauseAIcannotscaleefficientlywithoutintelligent,programmable,anddistributedconnectivityinfrastructure.

Let’sexploresomeofthewaysthiscanhappen.

KeyNeedsoftheNewDistributedSystem

Themoderndistributedglobalnetworkneedsthesekeycharacteristics:

1)Itshouldbesimpletoenableon-demand,usingsoftwareandAPI-basedprovisioning;

2)ItneedstobeconnectedtosecurePOPscompliantwiththehighestsecurityanddatasovereigntystandards;

3)Itneedstodeliverhighperformanceatthelowestpossiblecost;

TechPrimer:AgenticOperationsforInfrastructure

4)Itshouldprovideflexibleservicescharacteristics,suchasburstingorbandwidth-on-demand.

Legacyservicebusinessmodelssuchasleasedlinesandlong,fixedcontractsarenolongerideal.

Networkoperatorsneedtodeliverinfrastructuremodelsthatcanprovideconsistentapplication

performanceandsecuritycontrolsglobally,whilealsomakingiteasiertoconnecttomultiplecloudprovidersandexternalpartnersthroughregionalonramps.

FuturiomseesthreemajorstrategicrolesemergingfornetworkoperatorsandnetworkserviceprovidersinthedistributedAIecosystem.Let’sdiscusseachone.

AIEnabler

TosafelysupportnewneedssuchasagenticAI,enterprisesneedreliable,secureinfrastructuretosupportconnectivitytotrainingdataandinferenceworkloadsacrosspublicclouds,privatedata

centers,andedgeenvironments.Eachusecase,service,orapplicationmayrequireuniqueperformanceandsovereigntyconstraints.

Steppingintothisrole,operatorscanfocusonenablingAIconnectivitythroughacombinationoftransport,interconnection,cloudnetworking,andedgeinfrastructure.Theyarepositionedas

providersofdynamic,securebandwidthtoconnectdataandapps.

ThesedemandsrequirethecapabilitytoprovideAIconnectivityas-a-servicetoenterprises,ondemand.Notonlydoesthisincludesecurenetworkingbutalsoadvancedfeaturessuchas

orchestration,costmanagement,andmonitoringaspartofasingle,managedAIgateway.

Tothisend,EquinixprovidestheDistributedAIHub,poweredbyEquinixFabricIntelligence,asingle,unifiedframeworkforenterprisestoconnect,secure,andsimplifytheirincreasinglycomplexand

distributedAIecosystems.

Thisincludes:

•Opticaltransport(enterprise,cloud,multicloud)

•AIinterconnection(enterprise,cloud,GPUclouds)

•Cloudonramps

•Edgeconnectivity(devices,industrial)

•Datamobilityservices(roaming,remotelocation)

Networkoperatorscanpositiontheseserviceswithrelativeeaseandlowriskbecausealloftheseservicesareinthecurrentservicesportfolio.Insomecases,what’sneededisabetterplatformforenablinganddeliveringtheseservicesondemandusinganetworkas-a-service(NaaS)model.

TechPrimer:AgenticOperationsforInfrastructure

Increasingly,thisrolecanextendbeyondtransporttoenabledistributedinferenceenvironments.Byprovidinghigh-performanceinterconnection,proximitytodatasources,andaccesstomulticloudandedgeinfrastructure,operatorscansupportemergingAIinferencefabricsthatunderpinreal-time

applicationsandagent-basedsystems.

AIServiceProvider

Networkoperatorsplayakeyroleinenterpriseservicesbybeingenablersofenterprisetechnology.ThisisanopportunitytopartnerwithAIservicesplatformstodelivernetwork-optimizedAIservices.

SomeoperatorswillmovehigherintothestackbydeliveringAIinfrastructureservicesdirectly.Theseservicesmayinclude:

•SovereignAIhosting

•RegionalAIinference

•ManagedGPUinfrastructure

•AIobservability

•TrustedAIinfrastructure

•AInetworkingservices

Thebottomlineisthatmoresophisticatedservicesprovidehighervalue,whichinturnimproves

margins.Andasanintegrated,layeredmodelofAIconnectivityandrelatedservicesdeliversmore

value,italsobecomesastickiercompetitiveadvantage.Ofcourse,thismayrequireinvestmentandthedevelopmentofoperationalsophistication.

Akeyemergingopportunityinthismodelispremiuminferenceservices.AsAIadoptionshiftsfromtrainingtolarge-scaleinferenceandagent-drivenworkloads,enterprisesincreasinglyrequirelow-latency,high-performanceproductionenvironmentsforAIexecution.

Premiuminferencedeploymentsrelyondistributedinfrastructurethatplacescomputeclosertousers,data,anddevices—particularlyasmorepower-efficientchipsenableinferenceattheedge.This

createsdemandfordeterministicperformance,fastresponsetimes,andhighlyreliableinterconnectionbetweendistributedAIcomponents.

PlatformssuchasEquinix,withdenseglobalinterconnectionandproximitytoclouds,data,andnetworks,provideanidealfoundationforoperatorstodeliverAIinferenceasahigh-value,

performance-optimizedservice.

TechPrimer:AgenticOperationsforInfrastructure

AIOperationsandAgenticAutomation

ThethirdrolefornetworkoperatorsinvolvesusingAIinternallytoimproveoperations.OperatorsareincreasinglyapplyingAIto:

•Networkautomation

•Predictivemaintenance

•Securityoperations

•Capacityoptimization

•Serviceassurance

•Customerexperiencemanagement

Thisapproachmaynotcreateentirelynewrevenuestreamsimmediately,butitcanmateriallyimproveoperationalefficiencyandresiliency.

Theriseofagenticoperationsmakesreal-timeinferenceacorerequirementinsidenetworkoperationsthemselves.AIsystemsmustcontinuouslyanalyzetelemetry,predictfailures,andtriggeractions

acrossdistributedenvironments—shiftingfromofflineanalyticstolive,decision-drivenexecution.

Thisplacesnewdemandsoninfrastructure:Operatorsrequirelow-latency,highlyreliableinferencecapabilitiesclosetowheredataisgenerated,enablingfasterdecisionloops,moreautonomous

operations,andimprovedserviceperformanceatscale.

5.Conclusion:NetworkServicesMarketEvolution

TherushintoAIischangingindustriesinreal-time.Already,enterprisesoftwarecompanieshavehadtopivottoadapttheirmodelsasenterprisesexperimentwithusingAItooptimizeinternalworkflowsandprocesses,insomecasesreplacingexistingsoftwareplatforms.

Thetelecommunicationsandnetworkoperatormarketsarenodifferent.Majorglobal

telecommunicationscompaniesarecitingAIandtheevolutionintoagenticAIasafundamental

changeagentfortheirbusinessmodels.Inrecentpublicstatementsandearningscalls,executive

leadershiphasframedAIasatoolforcostcompression,workforcerestructurings,andautonomousnetworkoperations.

Afteranalyzingdeploymentpatternsofrecententerpriseandnetworkoperators,it’sclearthatadoptionpatternsaregravitatingtowardmorenimbleandresponsivenetworkinfrastructure.

Futuriomhasoutlinedsomekeyopportunitiesfortheindustrygoingforward.

TechPrimer:AgenticOperationsforInfrastructure

TelecommunicationsOperatorsandAIGrids

Telecommunicationsoperators,includingAT&T,T-Mobile,andComcast,areevaluatingdistributedAIarchitecturescombiningedgecomputeandAIinferencecapabilities.NVIDIAhasdescribedthese

emergingmodelsasAIgridscapableofdeliveringlocalizedinferenceclosertousersanddevices.

EnterpriseHybridAIDeployments

It’sclearthathybridcloudinfrastructureisgainingmomentum.WithdataasthefuelforAI-drivenapplications,enterprisesneedtoconnecttomoreresourcesthaneverbefore.

Futuriomresearchhasshownincreasinghybridcloudadoptionamongenterprises,including

AstraZeneca,BMW,DeutscheBank,Fidelity,andSalesforce.ManyAIdeploymentsincreasinglyrequirehybridarchitecturesspanningcloud,privateinfrastructure,andedgelocations.

Aswehaveindicated,networkoperatorsareinaprimepositiontoenableconnectivityforhybridcloudconnectivity.

IndustrialandEdgeAI

IndustrialAIdeploymentsinmanufacturing,logistics,andhealthcareincreasinglyrequirelocalized

inferenceratherthancentralizedcloudprocessing.Thisisacceleratingdemandforedgenetworking,low-latencytransport,anddistributedcomputeinfrastructure.

TheAIinfrastructureopportunityislarge,butoperatorsfaceimportantstrategictrade-offs.

Operatorsthatremainfocusedonlyonconnectivityriskbecomingincreasinglycommoditized.

However,operatorspursuingAIinfrastructureservicesfacehighercapitalintensityandoperationalcomplexity.

Themostsuccessfulstrategieswillneedtoinclude:

•Distributedinterconnection

•SovereignAIenablement

•Edgeinferencecapabilities

•AI-poweredoperations

•Programmableinfrastructure

•Cloud-nativenetworking

TechPrimer:AgenticOperationsforInfrastructure

ThenextphaseofAlgrowthwillnotbedefinedsolelybyGPUsandcomputeclusters.Itwillalsobedefinedbythequality,intelligence,andprogrammabilityofthenetworksconnectingAlsystems,enterprises,anduserstogether.

THENEWENTERPRISEMODEL:DECENTRALIZEDDATA&APPLICATIONS

INTEGRATEDORCHESTRATIONLAY