Cbinsights-企業(yè)人工智能路線圖：人工智能開發(fā)平臺格局如何轉(zhuǎn)變改變買家評估ROI、用例等的方式（英）

B號CBB號CBINSIGHTSWeminedCBInsightsdataandspokewith50+buyersofAIdevelopmentplatforms—includingDatabricks,HuggingFace,andScaleAI—tounderstandhowthey’redeployingAImodels,whatthey’repaying,andwhatthefutureholdsforthelandscape.NocompanywantstomissoutonAI.AscommercialapplicationsofAIscalerapidlyamidthegenerativeAIboom,enterprisesareracingtooverhaultheirinfrastructuretosupportthedeploymentandmanagementoftheseadvancedmodels.EnterprisebuyersareincreasinglyturningtoAIdevelopmentplatformsfortheirAIneeds.AIdevelopmentplatformsenableenterprisestomanagetheAIlifecycle—fromdatapreparation,training,andvalidationtomodeldeploymentandcontinuousmonitoring—throughasingleplatform.Thelandscapefeaturesamixofenterprisemachinelearning(ML)players(H2O.ai,DataRobot),bigtechproducts(GoogleCloudVertexAI,AmazonSageMakerandBedrock),aswellasemergingAIdevelopertools(Predibase,LightningAI).Source:CBInsights—AIdevelopmentplatformsmarketPlatformsarenowunderintensepressuretoadapttheirofferingsforthegenAIeraandcapturemoreenterpriseAIspend,enablingenterprisestoleveragethepoweroffoundationmodels.WeminedCBInsightsvaluation,headcount,and?nancingdata,aswellas50+buyerinterviews,tomaptheevolvinglandscapeandanalyzeitsfuture.1.TheAIdevelopmentplatformmarketlandscape2.HowenterprisebuyersareevaluatingtheROIoftheirAItoolspend3.ThefutureofenterpriseAIdevelopment4.Samplebuyercasestudiesbyindustry層號CBINSIGHTSTheEnterpriseAIRoadmap|2GenAIischangingtheAIdevelopmentlandscape4TheAIdevelopmentplatformmarket4LegacyMLcompanieslosesteam5CompaniesharnessgenAImomentum6Bigtechmusclesinalongsidenewstartups9Evaluatingreturnoninvestment(ROI)9Productivitygains9Costsavings10ThefutureofenterpriseAIdevelopment13Harnessingproprietarydatawillunlockdifferentiatedusecases15Bigtechcompanieshavemultipleadvantages17Enterprisesfacepressuretoexploreopen-sourcemodels18Task-speci?cmodelsgainadoption22ConsolidationiscomingasthegenerativeAIspacematures27SelectgenAIacquisitions,June2023–June202428EnterprisesbecomemoredisciplinedintheirAIspend29Customercasestudies30AIdevelopmentplatformusecasesummaries31層號CBINSIGHTSTheEnterpriseAIRoadmap|3AIdevelopmentplatformsarenotnew.Thelandscapefeaturesseveralplatformsfoundedintheearly2010s,whenenterpriseapplicationsformachinelearningstartedtobecomepopular.ButgenAIhasmarkedanewerainAIdevelopment.Increasinglysophisticatedmodelsareopeningupnewapplicationsthatenterprisesareeagertoharness,creatingopportunitiesforvendorsinthemarketwhilechallengingthemtoadaptfastenoughtosupportthelatestAItasks.Below,wede?nethemarketandtheplayersmovingin.AIdevelopmentplatformsofferone-stopshopsforenterprisesthatwanttodevelopandlaunchin-houseAIprojects.Somecompaniesinthespacecompetedirectly(e.g.,DataikuandDataRobotindatasciencework?ows),whileothersaremorespecialized(e.g.,Scale,whichfocusesondatapreparationbutalsooffersagenAIdevelopmentplatform).ManyenterprisesarecustomersofmultipleAIdevelopmentplatforms.Thebroadermachinelearningoperations(MLOps)landscapeisfragmented,containing130+companiesacross12categories.層號CBINSIGHTSTheEnterpriseAIRoadmap|4Source:CBInsightsresearch—MLOpsmarketmapEnterpriseMLdevelopmentplatforms,suchasDataRobot(foundedin2012)andDataiku(foundedin2013),arealreadyfeelingthepaininanovercrowdedmarket.DataikuraisedadownroundinDecember2022,whileDataRobothasgonethroughmultipleroundsoflayoffs.層號CBINSIGHTSTheEnterpriseAIRoadmap|5Source:CBInsights—DataikuvaluationdataGenerativeAIisnowshakingupthemarket,asthetech“l(fā)eapfrogs”moretraditionalenterpriseAIdevelopment,asthisScalecustomerdescribes:層號CBINSIGHTSTheEnterpriseAIRoadmap|6scale“Therehasbeenaleapfroginthekindofprojectsthatpeopleareworkingoninternallyatenterprises.Alotof[traditionalAIdevelopment]hasbeenabsorbedbyOpenAI,Anthropic,AI21Labs,andothers.Theneedtodothisin-househaschangedinthelast12monthsorsoandshapedthewholecategoryinaninterestingwayrightnow,where[enterprises]arealltryingto?gureoutwheretheygettheirnextphaseofgrowth.Becausethat'snotcomingfromthetraditionalMLandAIdatapipelinesthattheywereexpectingtogrowexponentially.”ChiefProductO?cer,VC-backedsoftwarestartup層CBINSIGHTSCompanieslikeScale,HuggingFace,andDatabrickshavesprintedaheadintermsofheadcountgrowthandfundingasthey’vecapturedsomeofthemomentumaroundgenerativeAI.層號CBINSIGHTSTheEnterpriseAIRoadmap|7Source:CBInsights—HeadcountdataMeanwhile,Databricksisalsoactivelyacquiringtoexpanditsproductfeatures—includingbuyingLLMOpsstartupMosaicMLfor$1.3BinJune2023anddatamanagementstartupTabularfor$1B+ayearlater.Source:CBInsights—Databricksacquisitioninsights層號CBINSIGHTSTheEnterpriseAIRoadmap|8BigtechcompaniesarealsobuildingouttheirproductsuitesforthegenAIera.GooglehasexpandeditsVertexAIdevelopmentplatformtogiveaccesstoitsGeminimodelsandotherthird-party/openmodels,whileAmazonWebServices(AWS)announcedtheAmazonBedrockmanagedserviceforgenAIdevelopmentinApril2023.Inaddition,anewerclassofLLM-focuseddevelopmentplatformshasemerged,includingsmall&task-speci?cplatformsPredibaseandGlaiveaswellasuni?edplatformslikeAdaptiveMLandChalk.Weinterviewed50+enterprisecustomersofAIdevelopmentplatforms,withusecasesrangingfrompredictivemaintenancetocoderproductivity,tounderstandhowthey’reevaluatingROI.Twokeyfactorsemerge:productivitygainsandcostsavings.Buyerslookatconcretemetricstomeasureproductivitygains,suchasincreasesinoutput(e.g.,featureslaunched),taskspeed,andoverallteame?ciency.ThisHuggingFacecustomerhighlightshowtheyquantifythevaluebyconsideringhowlongitwouldhavetakentoachievethesameresultswithouttheAItool.This"buildvs.buy"calculationshowsthetooldeliversproductivitybooststhatjustifytheir$500Kannualspend.層號CBINSIGHTSTheEnterpriseAIRoadmap|9comparabletosomanyotherinvestmentswe'vemadeovertheexecutionofthedifferentteams,soyes,absolutely[wehavespeci?cmetricstoquantifysuccess].IfweweretodoallofthisworkthatHuggingFaceisallowingustodo,howlongwouldithavetakenus?”Fortune500company層CBINSIGHTSCloselyrelatedtoproductivitygainsarethedirectcostsavingsenabledbyAItools.OneC3AIcustomerintheoil&gasindustryemphasizedthe"tremendousvalue"obtainedthroughusingtheplatform'spredictiveanalyticstoimproveequipmenterrorpredictionandreducemaintenancecycles.Fewerequipmentfailuresandproductioninterruptionstranslateintoharddollarsavings.層號CBINSIGHTSTheEnterpriseAIRoadmap|10ReadthefulltranscriptontheCBInsightsplatform.目c3.iCustomer:PrincipalofDataandAnalyticsatFortune500companySatisfaction:9/10“WehavegottentremendousvaluefromthesavingswehavemaintainedusingpredictiveanalyticsofC3AI.Ourmaintenancecyclehasgonedown.Wedon'ttakedownourplantthatoften,ourerrorsandstuffinpredictingwhenanequipmentmightbeoffhasbecomebetter.I'veheardreallygoodfeedbackfromtheoperatorswhomyteaminteractswith.”●Predictivemaintenanceforequipmentintheoilandgasindustry,consideringfactorslikegeographiclocationandmaintenanceintervals○Decreasedmaintenancecycleanddowntime,leadingtocostsavings○Integratedandanalyzeddifferenttypesofdata(e.g.,weatherdata)forimprovedaccuracyinpredictingwhenequipmentmightfail○Reducedpersonnelrequirementsformaintenance●UsestheentiresuiteofC3AI,withinstancesinEurope,NorthAmerica,andAsia層號CBINSIGHTSTheEnterpriseAIRoadmap|11●Multi-yearcontract●Concernsaboutrisinginfrastructurecostsassociatedwithclouddeploymentanddatastorage●PlanstoexpandtheuseofC3AIforpredictivemaintenanceinotherareas,suchassmartmetering,renewables,andhydrogenplantsThisH2O.aicustomerbreaksdowntheROIcalculationfurther.Tothem,the$125KfortheH2OAICloud(HAIC)productisjusti?edbyestimating4weeksoftimesavedannuallyperdatascientist.Withateamof10datascientists,thisequatestoaround$500Kinsavings—a4xreturnontheinvestment.Thecustomernotesthesesavingsmaxouttheirbudgetforsuchtools,showingtheyarespendingatthelimitofwheretheyseeapositiveROI.層號CBINSIGHTSTheEnterpriseAIRoadmap|12H2o.aivalueisthere.Asfarasmybudgetsgo,Idon'thavemuchmoreofabudgetthanthe$125,000andthe$50,000that'sbeenallottedtome.I'mmaxedoutthereforanMLOpstoolandanAIacceleratortool.”Publiclytradedutilitycompany層CBINSIGHTSTraditionalAIandMLworkloadsunderpinawiderangeofenterpriseapplicationstoday,frompredictivemaintenanceinmanufacturingtodemandforecastinginretailtofrauddetectionin?nancialservices.Meanwhile,generativeAIisstillintheearlydaysofenterpriseadoption.ThemostcommongenAIusecases,cuttingacrossenterprises,asDellCOOJeffClarkesummarizedonthecompany’sMayearningscall,are:1.Contentcreation2.Customersupportassistance3.Naturallanguagesearch層號CBINSIGHTSTheEnterpriseAIRoadmap|134.Designanddatacreation5.Codegeneration6.DocumentautomationForsomecustomers,likethisC3AIbuyer,genAIremainsintherealmofhype.“Yes,IgetaskedamilliontimesaboutChatGPTandtheirpotentialintegration,butthat'snotsomethingthatIthinkwithinthepetrochemicalspacethatpeoplearegoingtojumponrightPubliclytradedchemicalcompany層CBINSIGHTSButmostinterviewsrevealacommontheme:therapidlyevolvinggenAImarketwillsigni?cantlyshapethefutureofAIdevelopmentplatforms.AsbusinessesplantodeveloptheirownAIapplications,theyarecloselymonitoringtheirvendors'genAIroadmapstoinformtheirdecision-making.Hereare6keytakeawaysaboutthefutureofthelandscape,basedonCBInsightsdataandbuyerinterviews.層號CBINSIGHTSTheEnterpriseAIRoadmap|14AImodelslikeOpenAI’sGPT-4dependonmassivequantitiesoftrainingdata.Enterprises’proprietarydata,structuredandunstructured,iskeytocustomizingmodelsfortheirownusecases,likesummarizationanddataanalysis.Simplywranglingenterprisedataasastartingpointtobeabletoleverageitfortheseusecasesisstillastickingpoint,perDellCOOJeffClarke:“Helpingcustomersunderstandtheirdata,howtopreparetheirdataforthoseusecasesiswhatwe'redoingtoday.”Meanwhile,enterprisesarebeingpushedtoinvestincleaninguptheirdataquality,tominimizethedownstreameffectsofpoor-qualitydataonAIperformance.OnecustomerofinfrastructureproviderandmodeldeveloperTogetherAIemphasizedtheimportanceofdatamanagement.together.aidatamanagementaspectofit.Thedataside,thequalityofthedata,thelocationofthedata,thestateofthedata,thecurationTechnologyconsultingandservicescompany層CBINSIGHTS層號CBINSIGHTSTheEnterpriseAIRoadmap|15LeadingclouddatamanagementcompanieslikeDatabricksandSnow?ake,whichhelpcompaniesconnecttheirsourcesofdataforprocessingandanalysis,aremovingtocapturemoreenterpriseAIclients.Bothrecentlymademovestosupportadditionaldataformats,liketheopen-sourceApacheIcebergtableformat,whichisimportantforenterpriseslookingtoleveragetheirowndataforAIapplications.NotablyinJune2024,DatabricksacquiredTabular,whichisbuiltonApacheIceberg,fornorthof$1B—bringingtogethertheleadingopen-sourcelakehouseformatsDeltaLake,whichDatabricksisbuilton,andIceberg.ThiswillenableDatabrickstoprovidebetterdatacompatibilityforitscustomers,allowingthemtoutilizetheirdataacrossdifferentformatsandreducedatasilos.Source:CBInsights—Databricksacquisitiondata層號CBINSIGHTSTheEnterpriseAIRoadmap|16BigtechcompanieshavemultipleadvantagesBigtechplayerslikeAmazon,Microsoft,Google,andIBMhaveinherentadvantagesintheAIdevelopmentlandscapeduetotheirscale,infrastructure,andexistingcustomerrelationships.Forexample,oneIBMcustomercitedIBM’saccesstoitsinternaldataandapprovaltoworkbehindits?rewalls,enablingfasterproofofconceptsandpilots,asbeingakeyreasonitwentwithIBMwatsonx:“You'reprobablylookingateasilymaybespending20%to30%morebybringinginaseparatevendor.”Similarly,Microsoft'sstrongdistributionchannelsanditsabilitytoreachknowledgeworkersthroughproductslikeCopilotgiveitacompetitiveedgewithenterprises.Onthedatamanagementside,platformslikeDatabricksallowuserstokeeptheirdataonbigtech’scloudplatformswhiletrainingmachinelearningmodels.scale“Allthoseplatforms,eachofthemhavetheirownniche.Databricks,ofcourse,runningtheopen-sourceMLonApacheend-to-endincludingyourdata.IfyourdataisonAWS,Azure,GCPGCP,orwherever,youcankeepthedatawhereitis,youcantrainyourmachinelearningmodelsonDatabricks.That'sahugeadvantage,especiallywithpeoplewhohavealotofdataonthehyperscalersalready.”ChiefProductO?cer,VC-backedsoftwarestartup層CBINSIGHTS層號CBINSIGHTSTheEnterpriseAIRoadmap|17AIstartupswillneedtoinnovatefasterandprovidedifferentiatedofferings.Forexample,thisVPsuggestsfasterinnovationwillbecrucialforcompanieslikeHuggingFacetostandoutasMicrosoft’sAzureexpandsitsmodelcatalog:“MostofourplatformisbuiltonAzure.Nowthatthemodelspeci?callygotothemforsomeofthisanddotheymovefasterthantheothers?”Publiclytradedmultinationalhealthinsurancecompany層CBINSIGHTSInotherwords,asbigtechcatchesupintermsofmodelrepositoriesandsupportedAItasks,wepredicttherestoftheecosystemwillneedtospecializeandformstrategicpartnershipstocompeteforenterprises'coreAIwork?ows.VendorswillfaceevenmorepressuretoproveROIinthislandscape.Ascompanieslookformorecost-effectiveand?exiblealternativestoproprietarymodelslikethosefromOpenAI,open-sourceAImodelsaregainingattention.層號CBINSIGHTSTheEnterpriseAIRoadmap|18Theperformancegapbetweenopen-sourceandproprietarymodelsisclosingfast,aswehighlightedearlierthisyear.Source:CBInsights—GenerativeAIPredictions2024reportMetahassincereleaseditsopen-sourceLlama370Bparametermodel,whichscoreshigherontheMMLU—atestthatevaluatesalanguagemodel’sknowledge—thanAnthropic’sproprietaryClaude3Sonnet(thesecond-mostadvancedmodelintheClaude3family).Companieswillcomeunder?nancialpressuretoconsiderhowtoleverageopen-sourcemodelsastheythinkmoreaboutthelonger-termROIoftheirAIinvestments.層號CBINSIGHTSTheEnterpriseAIRoadmap|19modelsoutthere?Whatisthetrade-offintermsofperformanceandcostandthingslikethat?’ThatchangeiscomingaswestartthinkingaboutROIforthese.”Publiclytradedmultinationalhealthinsurancecompany層CBINSIGHTSAtthesametime,open-sourcemodelshavetrade-offs,asthebelowTogetherAIcustomerhighlights—includingthecostsassociatedwithmanaginginfrastructure,ensuringdatasecurity,potentiallylowerperformancecomparedtoproprietarymodels,andtheneedfortechnicalexpertisetotrainanddeploythemeffectively.層號CBINSIGHTSTheEnterpriseAIRoadmap|20together.aigoingtohavespeci?cusecasesacrossspeci[Companiesare]nowgoingtointroducetheseopen-sourcemodels1)fromalmostapilotstandpoint2)toseewhatexactlyTechnologyconsultingandservicescompany層CBINSIGHTSMorebroadly,customersindicatethattheycareaboutmodelavailabilityandspeedtomarketaskeyneedswhenevaluatingAIdevelopmentplatforms.層號CBINSIGHTSTheEnterpriseAIRoadmap|21“Thespaceismovingsofast.Weneedthelatestandthegreateststuff.Weneedthereliability.Weneedthesecurity,privacy,allthosethingsontheenterpriseside.ButwiththeFortuneGlobal500subsidiary層CBINSIGHTSSmalllanguagemodels(SLMs)havefewerparametersandrequirelesscomputationalpowerthanLLMs,makingthemfastertotrainandcheapertoruncomparedtogenericmodels.Iftheyareonlybeingusedforaspeci?ctask,thentheirperformancemightbemorethanenoughforenterprises—insomecasestheycanevenoutperformLLMs.Microsoft’sPhi-3-smallmodel(7Bparameters),announcedinApril2024andtrainedon“high-quality”textbookdata,outperformsGPT-3.5Turbo(estimatedat20Bparameters)ontheMMLUbenchmark.Bytrainingonnarrowdatasets,smallmodelscanbehonedfortargetedapplications.Multiplebuyersindicatedtheopportunityfordomain-speci?cmodelsinourconversations.層號CBINSIGHTSTheEnterpriseAIRoadmap|22ReadthefulltranscriptontheCBInsightsplatform.VertexAICustomer:DirectorofSoftwareEngineeringatpubliclytradedtelecommunicationscompanySatisfaction:7.5/10“WhatIthinkwewillneedfromGoogleistohelpuscreatecustareveryspeci?ctodomain,andtheyarevery,verycomprehensiveinthatdomain,ratherthanbeinggenericlikemasterofallwedon'tneed,weneedexpertofone.Weneedthesekindsofexpertmodelsforthesespeci?cdomains.”●Machinelearningforpredictivemodeling(e.g.,salesforecasting)andpropensityscoring(e.g.,optimizingpaidmediacampaignsbyidentifyinghigh-ROIpersonasandcohorts)●LeveragingAIforcontactcenteroptimizationandIT/softwaredevelopment●UsingVertexAIaspartofalarger$100M,5-yearenterprisecontractwithGoogle●Overallspendisaround$6Mperyear,whichincludesVertexAI,ContactCenterAI(CCAI),BI,cloudcapabilities,andcomputecosts層號CBINSIGHTSTheEnterpriseAIRoadmap|23●Pricingisusage-basedandtoken-based,notseat-based●Needformoredomain-speci?c,comprehensivemodelsratherthangenericlargelanguagemodels●AnticipaterequiringGoogle'shelptocreatecustommodelstailoredtotheirspeci?cdomainsAnotheradvantageofsmallmodelsisthepotentialforenhanceddataprivacyandsecurity.Byhostingandtrainingmodelslocally,companiescanmaintaingreatercontroloversensitivedataandreducetheriskofdatabreachesorunauthorizedaccessassociatedwithrelyingonthird-partyservices.NascentAIdevelopmentplatformsPredibaseandGlaive—bothAI1002024winners—helpenterprisestrainanddeploysmallandtask-speci?cmodels.WhilePredibaseisexpandingitscustomerbase,Glaiveisstillintheearlierstagesofdevelopment,ashighlightedbyCBInsightsCommercialMaturityscores.層號CBINSIGHTSTheEnterpriseAIRoadmap|24Source:CBinsights—MosaicandCommercialMaturityscores層號CBINSIGHTSTheEnterpriseAIRoadmap|25ReadthefulltranscriptontheCBInsightsplatform..predibaseCustomer:QuantitativeStrategistat?nancialservicescompanySatisfaction:9/10Usecases:●Understandclients’tradingpatternsandhabits,usingstructured(numericalpricingandriskdata)andunstructuredclientdatatoprovideclientswithreal-timepredictionsonthe?nancialservicescompany’splatform●Aimingtoget1to2modelsintoproductiontodemonstratevalueandcovercontractcost●Predibaseproductforbuildingadvancedmachinelearningmodelsusingthecustomer’sdatasetsoutofthebox;APIsuitetointegratemodelswithtechstack●Wantedtominimizeriskpre-production,addedearlyterminationdatestocontract●Addedconsultancypackagetocontract,foraccesstoPredibaseexpertsafewhoursperweek層號CBINSIGHTSTheEnterpriseAIRoadmap|26●Undecidedonrenewal,dependentongettingmodelsintoproductionbyendofcontractthatmakemeasurablepredictionsandconcretelyaddbusinessvalue●SeesopportunityforPredibasetogrowbyprovidingmoreconsultancyservicestoguidelessexperiencedMLcustomersAcrossinterviews,buyershaveexpressedanexpectationofconsolidationacrossthespace.thesamething.There'ssomanyoutthererightnowthatdothesamethingtodothe?ne-tuning,theydotheproductionanalyzation,theinferencing…”Technologyconsultingcompany層CBINSIGHTS層號CBINSIGHTSTheEnterpriseAIRoadmap|27WhileoverallAIM&AactivitydroppedinQ1’24,thegenAIspacehasseenanuptickinM&Adealsrecently.SelectgenAIacquisitions,June2023–June2024MLtrainingdatacurationHuggingFace6/13/2024$7MModelvalidation&monitoringSnow?ake5/22/2024$42.3MVisualeffects(VFX)Autodesk5/21/2024$12.5MHardware&modeloptimizationNvidia4/24/2024$118MHardware&modeloptimizationNvidia4/24/2024$55MLLMsecurityProtectAI1/31/2024EnterpriseavatarsAdobe11/22/2023$13.9MAIdevelopmentDatabricks6/26/2023$37MLegalcasesearch&summarizationThomsonReuters6/26/2023$69MCBInsightscustomerscanusethissearchtotrackgenAIM&Adeals.GenerativeAIstartupsattheinfrastructurelayerareraisingdealsonaverageover$150Mduetothecapital-intensivenatureofdevelopingadvancedmodels.GiventhecostoftrainingmodelsandbringingonAItalent,startupsrunningoutofrunwaymayincreasinglylooktoexitopportunities.Microsofteffectivelyacqui-hiredIn?ectionAI,asthecompanydidn’tseeaviablepathtocommercializingitsconsumerchatbot,whileStabilityAIhasreportedlydiscussedasaleasitfacesmountinglosses.層號CBINSIGHTSTheEnterpriseAIRoadmap|28Meanwhile,HuggingFaceacquiredAIdatacurationstartupArgilla,whichhadraised$7Minfunding,for$10MinJune2024.Beyondteam-levelproductivitygainsandcostsavings,oneopenquestionaboutthecurrentrushofAIinvestmentiswhatimpactitwillhaveoncompanies’toplines?Salesforce,whichhasbeenleaningheavilyonitsAIgrowthstrategy,indicatedinitsFebruaryearningscallthatitdoesn'texpecttoseeamaterialimpactfromitsnewestgenAIproductsthis?scalyear.TheCRMleaderreporteddisappointingresultsinitsmostrecentquarteramidanenterprisesoftwarespendingpullback,thoughitmaintaineditsfull-yearrevenueguidance.Source:CBInsights—AIstrategiesfor11oftheworld’slargestcompaniesEnterpriseswilllikelybecomemoredisciplinedintheirAIspendingasROItakestimetomaterialize.Mentionsrelatedto“AI”and“revenue”havegrownnearly5xonearningscallsfromQ1’22toQ1’24.Forexample,JPMorganCFOJeremyBarnumtalkedaboutthe?rm’s“disciplined”appro