OpenAI-企业如何使用+AI：基于+ChatGPT+的实证研究+How+Organizations+Use+AI

HowOrganizationsUseAI:EvidencefromChatGPT

AaronChatterji1DavidHoltz2,1NeelRakholia1

PrasannaTambe3,1GaweshaWeeratunga1

1OpenAI2ColumbiaBusinessSchool

3WhartonSchool,U.Pennsylvania

LastUpdated:August11,2026

Abstract

WestudyhoworganizationsusefrontiergenerativeAIbylinkingChatGPTEnter-

priseaccountrecordstousage,workerroles,taskclassifications,andpublic-company

financialdatathroughMarch2026.Theselinkeddataenableaprivacy-preserving

analysisofadoption,workerroles,andmessage-leveltasksatscale:forinstance,the

worker-levelsampleweanalyzeatthesix-monthadoptionhorizonincludesover1,500

organizationsandover17millionmessages.Wedocumentfourfactsaboutenterprise

AIadoptionanduse.First,ChatGPTEnterpriseusagehasgrownrapidlyduetoa

combinationofnewfirmadoptionandgrowingintensityamongexistingadopters.

Second,U.S.-basedpubliccompanyadoptionisconcentratedamonglarger,more

valuable,andmoreR&D-andSG&A-intensivefirms.Third,activeusewithinadopt-

ingfirmsspansjobfunctionsandsenioritylevels,withespeciallyhighusageintensity

amongearly-careerworkers.Fourth,ChatGPTEnterpriseusageencompassesabroad

rangeofknowledgeworktasks,includingwriting,technicalwork,communication,

andinformationsynthesis.Inaggregate,theseresultssuggestthatfirmsdifferwidely

inthespeed,breadthandpurposeoftheirenterpriseAIadoption,andthattheyare

stillactivelylearninghowtointegrateAIintoorganizationalworkflows.

JELCodes:O33,O30,L23,M15

Workingpaper,resultsaresubjecttochange.TheauthorsareespeciallygratefultoDavidDemingfor

feedbackandguidanceduringthedevelopmentofthiswork.WealsothankNicholasOtis,HarrisonSatcher,

CassandraDuchan-Solis,DrewJohnston,LauraBisesto,JoyceShi,EmmaKollek,JakeStamell,David

Zimmerman,ZachParent,BriceChallamel,SteveImm,RobFriedlander,JenniferRobinson,ErikBoxhoorn,

VinnieMonaco,MengJiaYang,PeterZhang,HendrikBuyle,ChrisLiao,NathalieGazzaneo,AdamCohen,

KevinWadman,IgnacioLopez-Gaffney,WesleyPasfield,andtheOpenAIAnalytics&Insightsteamfor

helpfulcommentsandassistance.WealsothankShaneGreenstein(discussant)andparticipantsintheNBER

2026SummerInstitutemeetingonDigitalEconomicsandArtificialIntelligence,aswellasattendeesofthe

2026WhartonAIandtheFutureofWorkConferenceforvaluablefeedback.DavidHoltzandPrasanna

TambecontributedtothisworkintheircapacityaspaidcontractorsforOpenAI.Contact:AaronChatterji,

ronnie@

;DavidHoltz,

david.holtz@

;NeelRakholia,

neelrakholia@

;

PrasannaTambe,

tambe@

;GaweshaWeeratunga,

gawesha@

.

2

1Introduction

GenerativeAIsystemscanperformagrowingrangeofeconomicallyvaluabletasks(Eloundouetal.

2024

;Patwardhanetal.

2025

),andindividualsuseconsumer-facinggenerativeAIchatbotsformanywork-relatedandpersonalactivities(Chatterjietal.

2025

;Handaetal.

2025

).However,lessisknownaboutfirmAIadoption:whichworkersaccountforobserveduse,howintensivelyactiveusersengagewithgenerativeAI,andforwhichtasks.UnderstandingthesepatternsisimportantforinterpretingrecentfindingsabouttheimpactofAIonproductivityandemployment(e.g.,Brynjolfssonetal.

2025a

;Brynjolfssonetal.

2025b

).MostevidenceonfirmAIadoptioncomesfromworkerandfirmsurveys(McElheranetal.

2024

;Bicketal.

2026a

;Yotzovetal.

2026

;Bonneyetal.

2026

).Althoughsurveysprovidebroadcoverageandcancapturenon-use,adoptionbarriers,andorganizationalcontext,self-reportedusageistypicallylessdetailedandmaysufferfromimperfectrecallorreportingbiases.

ThispaperstudiesworkplaceAIadoptionusinginternaldatafromChatGPTEn-terprise,OpenAI’scentrallyadministeredworkplaceproduct.

2

Wefirstexaminefirmadoptionbydecomposingenterprisegrowthintowithin-andbetween-firmcomponentsandlinkingChatGPTEnterpriseaccountstopubliccompanyfinancialdata.Wethenstudywithin-firmheterogeneitybycombiningusagedatawithemployeejobtitleinfor-mationandmessage-leveltaskclassifications,whichtellsushowusageintensityandtaskadoptionvariesacrossworkergroupssixmonthsafterorganizationaladoption.

WedocumentfourstylizedfactsaboutenterpriseAIadoptionandusage.First,enter-priseAIusageisgrowingrapidly,reflectingbothincreaseduseamongexistingcustomersandthearrivalofnewadopters.AggregateoutputtokensproducedbyChatGPTEn-terprisecustomersgrewroughlysevenfoldbetweenJune2025andMarch2026,andby

2Overtime,OpenAI’scentrallyadministeredworkplaceofferinghasexpandedbeyondChatGPT toincludeadditionalproducts,suchasCodex.Forsimplicity,andbecauseChatGPTaccountsfortheoverwhelmingmajorityofobservedusageduringourstudyperiod,werefertothisofferingthroughoutas“ChatGPTEnterprise.”

3

nearlyfourfoldwithinaconsistentcohortoffirmsthatadoptedbetweenJanuary2024andJune2025.Thus,abouthalfofthegrowthintokenconsumptionoverthisperiodoccurredwithinalready-adoptingfirms.Second,amongU.S.-basedpubliccompanies,ChatGPTEnterpriseadoptersarelarger,morevaluable,andmoreR&D-andSG&A-intensivethannon-adopters.ThispatternsuggeststhatearlyenterpriseAIadoptionisassociatedwithgreaterpriorinvestmentinintangibleandorganizationalcapabilities.

Third,usagewithinadoptingfirmsisbroadlydistributedacrossjobtitleclassesandsenioritylevelsbutwithheterogeneousintensity.Forexample,marketingandcommu-nicationsworkerssendmoremessagesthanexecutives,andearly-careerworkerssendmanymoremessagesthanmoresenioremployees.Fourth,ChatGPTEnterpriseusespansmanydifferenttasksacrossworkersandorganizations,ratherthanbeingconcentratedinasingleworkflow.Themostcommonusecasesarewriting,communication,andinformationsynthesis,butusageisalsocommonintaskssuchasresearch,planning,dataanalysis,legalandregulatorywork,finance,andmanyotherapplications.ThisbreadthisconsistentwithgenerativeAIfunctioningasageneralpurposetechnologyforknowledgework(BresnahanandTrajtenberg

1995

;Bresnahan

2024

;Eloundouetal.

2024

).

Takentogether,thesefindingsportrayenterpriseAIadoptionasabroadbutunevenorganizationalphenomenon.Adoptionisconcentratedamongfirmswithgreaterscaleandintangibleinvestment,whileusewithinadoptingfirmsisdistributedacrossmanyworkergroupsandknowledgeworktasksbutvariessubstantiallyinintensity.Thisheterogeneityhighlightsthatthelong-runeconomicvalueofenterpriseAIadoptionwilldependonwhetherdispersedindividualusedevelopsintocomplementaryorganizationalcapabilities(BresnahanandGreenstein

1996

;Bresnahanetal.

2002

;Brynjolfssonetal.

2021

).

Theremainderofthepaperproceedsasfollows:wefirstreviewtherelatedliteratureanddescribethedataandmeasurement.Wethenfollowthestructureintroducedabove:Sections

4.1

and

4.2

examineadoptionandusageacrossfirms,whileSections

4.3

and

4.4

4

examinethedistributionandtaskstructureofusewithinadoptingorganizations.InSection

5

,weconclude.

2RelatedLiterature

Ourworkcontributestofourrelatedliteratures.First,weaddtotheliteratureonAIadoptionanddiffusionwithinfirms.Acentralinsightfromresearchongeneralpurposetechnologiesisthatinitialadoptiondoesnotimplyeffectivedeployment:realizingvaluerequiresexperimentation,complementaryinvestment,andorganizationalchange,souseoftendiffusesgraduallywithinfirms(BresnahanandTrajtenberg

1995

;BresnahanandGreenstein

1996

;Bresnahanetal.

2002

;Bresnahan

2024

;Brynjolfssonetal.

2021

;Mansfield

1963

;Fuentelsazetal.

2003

).Consistentwiththisview,recentstudiesofdigitaltechnologyadoptionandusefindthatorganizationscontinuetodiscoverapplicationsandimprovetheiruseafterobtainingaccess(McElheranetal.

2024

;Yotzovetal.

2026

;Bicketal.

2026a

;Bicketal.

2026b

;Brandetal.

2024

;Kimetal.

2026

;Massenkoffetal.

2026a

).

3

ThemostcloselyrelatedpapertooursisBonneyetal.(

2026

),whichdistinguishesfirmadoptionfromthesubsequentdeploymentofAIacrossbusinessfunctionsandworkertasks.WeadvancethisliteraturebyexaminingwhichfirmattributespredictenterpriseAIadoptionand,amongadoptersatacommonpointintheiradoptioncycles,measuringhowdeploymentisdistributedacrossworkersandtasks.

Second,ourpapercontributestoresearchthatmeasuresAIusagewithtelemetrydata.Onestrandusesdataonthecontentofhuman–AIinteractionstocharacterizethetasks,occupations,andmodesofinteractionrepresentedinobserveduse(Handaetal.

2025

;Appeletal.

2026

;Massenkoffetal.

2026b

;Chatterjietal.

2025

;Tomlinsonetal.

2025

).AsecondstrandusesAPIandproduct-activitydatatocharacterizedemandacrossapplicationsandorganizationalsettingsandtoexaminehowAIisincorporatedintoproductionworkflows(Demireretal.

2025

;Fradkin

2025

;Appeletal.

2025

;Daniottietal.

3Relatedstudiesconnectfirm-levelAIinvestmentandexposuretofirmgrowth,productinnovation,andmarketvalue(Babinaetal.

2024

;Eisfeldtetal.

2026

;Yuetal.

2026

).

5

2026

;ChenandStratton

2026

;Demireretal.

2026b

).Tworecentpapersareparticularlycloselyrelatedtoours.Countsetal.(

2026

)usetelemetryfromMicrosoft365Copilottocharacterizeaggregateworkplaceuseanddocumenthowitstaskcompositionvariesacrossoccupationsandindustries.Johnstonetal.(

2026

)useOpenAItelemetrydatatostudytheshiftfromconversationaltoagenticAI,includinghowCodexadoption,usageintensity,andtaskcompositionvaryacrossorganizationalsettings,workerroles,andlevelsofseniority.

Third,wecontributetoresearchonheterogeneouseffectsofAIacrossworkersandtasks.ThisliteraturedistinguishesbetweentheactivitiesforwhichAIistechnicallycapableandthesettingsinwhichthosecapabilitiestranslateintorealizeduseandbenefits.Earlyworktakesatask-basedapproachandestimatepotentialexposurebycomparingmodelcapabilitieswithoccupationaltaskdescriptions(Eloundouetal.

2024

).

4

Morerecently,Patwardhanetal.(

2025

)evaluatefrontiermodelsonexpert-constructedtasksspanning44occupationsandninesectors,providingevidenceaboutwheremodelscanproduceprofessional-qualitydeliverables.Experimentalstudies,inturn,showthatAI’srealizedeffectsdependontheworker,thetask,andhowAI-generatedoutputisevaluatedandimplemented(NoyandZhang

2023

;Brynjolfssonetal.

2025b

;Dell’Acquaetal.

2026

;Cuietal.

2026

;Otisetal.

2026

).Wecomplementthisworkbydocumentingthedeploymentdecisionsthatbridgethegapbetweencapabilityandrealizedeffects:whichworkergroupsaccountforactiveuse,howintensivelyusersineachgroupengagewithAI,andwhichtasksaccountfortheiractivity.

Finally,ourpapercontributestoresearchontherelationshipbetweenAI,orga-nizationalstructure,andthedivisionoflabor.Knowledge-basedtheoriesofthefirmvieworganizationalhierarchiesasmechanismsforallocatingproblemsamongworkers,managers,andspecializedexperts(Garicano

2000

;GaricanoandRossi-Hansberg

2006

).

4Subsequentworkemphasizesthattechnicalexposureneednottranslatedirectlyintorealizedadoption,becauseworkersvaryincomparativeadvantageandinthecostsofusingandverifyingAIoutput(Lindenlaubetal.

2026

).

6

Technologiesthatchangethecostofacquiringorcommunicatingknowledgecanthereforechangewhereexpertiseislocatedandhowtasksaredividedwithinthefirm(Bloometal.

2014

).RecentresearchappliesthislogictoAIbyexamininghowitchangesthevalueofexpertiseandwhichsequencesofworkcanbedelegatedtoAI(AutorandThompson

2025

;Demireretal.

2026a

),andwithin-firmevidenceshowsthatintensiveAIusecanexpandtherangeoftasksworkersperform,acceleratelearning,andshiftworktowardsupervisingandevaluatingAI-generatedoutput(Huangetal.

2025

).ThepapermostcloselyrelatedtooursinitsorganizationalfocusisKimandKoning(

2026

),whichshowsthatAI-nativestartupsaresmaller,flatter,andmoreengineering-intensivethancomparablefirms.WhereasmuchofthisworkexaminesAI-nativeorganizationsandhighlytechnicalworkers,westudyhowAIisdeployedwithintheexistingstructuresofestablishedfirmsacrossawiderangeofindustries.Bycomparinguseacrossjobfunctions,senioritylevels,andmanagerialpositions,weprovideevidenceonwhereageneralpurposeAItechnologyenterstheorganizationalhierarchyandhowitsrolevariesacrossorganizationalcontexts.

3DataandMeasurement

Ouranalysisdrawsonfourrelatedbutdistinctsamples:anaggregateenterpriseusagesample,asmallersamplewithemployeejobtitleandfirmindustryinformation,afurthertime-limitedsubsetofthejobtitleandindustrysampleusedfortask-classificationanalysis,andapubliccompanysamplelinkedtotheCompustatdatabasefromS&PGlobalMarketIntelligence.

5

WedescribetheconstructionofeachsampleinthefollowingsubsectionsandsummarizetheirrelationshipsinFigure

1

.

5AllCompustatdataarecopyright©2019,S&PGlobalMarketIntelligence.Reproductionofanyinformation,dataormaterial,includingratings(“Content”)inanyformisprohibitedexceptwiththepriorwrittenpermissionoftherelevantparty.Suchparty,itsaffiliatesandsuppliers(“ContentProviders”)donotguaranteetheaccuracy,adequacy,completeness,timelinessoravailabilityofanyContentandarenotresponsibleforanyerrorsoromissions(negligentorotherwise),regardlessofthecause,orfortheresultsobtainedfromtheuseofsuchContent.InnoeventshallContentProvidersbeliableforanydamages,costs,expenses,legalfees,orlosses(includinglostincomeorlostprofitandopportunitycosts)inconnectionwithanyuseoftheContent.

7

ForouranalysisofChatGPTEnterpriseusagedata,weusede-identifieddataandreportresultsonlyinaggregate.Messagecontentisclassifiedusingautomatedsystems,andjobtitlemetadataismappedtobroadjobtitleclass,seniority,andpeoplemanagercategories.Noresearchermanuallyreviewedindividualenterprisecustomermessagesforthisstudy.Forourfinancialanalysisofpubliccompanies,wesecurelylinkaggregateorganizationalusagedatatopublic-companyfinancialinformationfromCompustat.

3.1ChatGPTEnterpriseUsageData

Ourprimarydatasourceisanorganization-weekpanelofChatGPTEnterpriseadoptionandusage,constructedfromorganizationswhoseChatGPTEnterpriseadoptiondatesrangefromJanuary1,2024toMarch31,2026.Thedatacaptureadoptionofapaid,centrallyadministeredChatGPTEnterpriseworkspace,ratherthanusethroughpersonalaccounts,theAPI,orothersubscriptionplans.Weobserveeachorganization’senterpriseaccountidentifier,adoptiondate,andproductusageovertime.

OrganizationsenterthepanelintheweektheyadoptChatGPTEnterpriseandtheyremaininthepanelwhiletheirworkspaceisactive.Organization-weekswithanactiveworkspacebutnoobservedproductactivityareretainedwithzeromeasuredusage.Foreachorganization-week,wemeasuremessagessent,activeusers,andgeneratedoutputtokens,includingtokensgeneratedthroughbothChatGPTandCodex.Weeksareindexedrelativetoeachorganization’sadoptiondate.ThisaggregateChatGPTEnterpriseusagesampleisusedtomeasureadoptionandproductuseovertime.

3.2JobTitles,FirmIndustries,andTaskClassifications

Foranalysesofusagebyworkercharacteristics,wealsoconstructasampleofChatGPTEnterpriseorganizationsforwhichweobservebothfirmindustryandhigh-qualityem-ployeejobtitleinformation.StartingfromtheChatGPTEnterpriseusagesampledescribedabove,weretainorganizationsthatcanbeassignedtoabroadindustrycategoryusingNAICSclassifications.Wefurtherrequirethatatleastsomeuseractivitywithintheorga-

8

nizationcanbelinkedtoanon-emptyadministrativejobtitle.

6

Becausethecorrespondinganalysesmeasureusage6months(26weeks)afteradoption,weadditionallyrequireanobserved,activeorganization-weekatthathorizon.Theresultingworkercharacteristicssamplecontains1,764organizationsand17,446,551messages.

Withinthissample,wenormalizetheavailablejobtitlestringsandclassifythemintobroadjobtitleclasses,senioritylevels,andpeoplemanagercategories.

7

Theseuser-titleandfirm-industrymeasuresarethenlinkedtoChatGPTEnterpriseusageandaggregatedbyorganization,week,andworkercategory.Appendix

C

describesthenormalization,classification,andvalidationofourjobtitlemeasures.Importantly,jobtitlecoveragewithinincludedorganizationsisincomplete.Activeuserswithoutusablejobtitleinformationremaininorganization-levelusagetotalsanddenominatorsbutareclassifiedasmissingorunclassifiedinanalysesofheterogeneoususebyworkertype.

Wealsoseparatelyconstructataskclassificationsubsampleofthisdataset.WeclassifyChatGPTEnterprisemessagesintoataxonomyofworktasksusingamessage-levelclassifierthatisavailablebeginningonOctober30,2025.Appendix

D

providesinformationaboutthetasktaxonomyproducedbythisclassifier.Thetaskclassificationsampleisrestrictedtoorganizationsthatsatisfytheworkercharacteristicssamplerequirementsaboveandhavetaskclassificationdataavailableattheweek26horizon.Thisproducesatask-classificationsampleof973organizationsand8,696,657classifiedmessages.Weusethistaskclassificationsampleforbothanalysisoftheoveralltaskdistributionandforanalysesofthetaskdistributionsbyjobtitleclass,senioritylevel,peoplemanagerstatus,andindustry.

6Jobtitleinformationisobservedatasinglepointintimeandmaythereforenotcapturechangesinworkers’rolesoverthefullstudyperiod.

7Ourmaintextanalysesfocusonjobtitleclassandseniority;resultsforpeoplemanagerstatusappearinAppendix

B

.

9

3.3PublicCompanySampleandSummaryStatistics

ForanalysesofU.S.publiccompanycharacteristicsandfinancialoutcomes,webeginwithU.S.publicfirmsinCompustatandidentifyChatGPTEnterpriseadoptersbymappingChatGPTEnterpriseaccountstopublic-companyidentifiersusingacombinedcuratedandLLM-assistedaccount-to-tickercrosswalk.

8

WethendrawarandomsamplefromtheresultingsetofChatGPTEnterpriseaccountswithpublic-companyidentifiers.

9

Wedefinenon-adoptersaspublicfirmswithnoChatGPTEnterpriseticker-bridgematch.

10

Theresultingfinancialpanelincludesfirmandfiscal-yearidentifiersaswellastheCompustatvariablesreportedinTable

A1

.

11

WelinkweeklyChatGPTEnterpriseactivitytothispanelbyassigningeachusageweektotheCompustatfiscalyearinwhichitfallsandaggregatingusagetotheticker-yearlevel.Forusage-intensityanalyses,wemeasureweeklymessagesperemployee,weeklyoutputtokensperemployee,andweeklyactiveusers(WAU)peremployee.Thefirsttwomeasurescaptureusagevolumerelativetofirmsize,whileWAUcapturesthebreadthofparticipationintheChatGPTEnterpriseworkspace.

Thisprocedureyieldsausage-linkedpanelof521ticker-yearobservationsfor417public-companytickers.

12

Oftheseusage-linkedticker-years,509observations,covering

8Thepublic-companyanalysesarelimitedtoU.S.firmsbecausetheCompustatdatausedherearerestrictedtoU.S.publiccompanies.

9WedrawarandomsampletolimitdisclosureofcommerciallysensitiveinformationaboutOpenAI’senterprisebusiness.

10Weclassifyasnon-adoptersfirmsthatwecannotmatchtoaChatGPTEnterpriseaccount;thisclas-sificationdoesnotimplythattheyusenoAIproducts.Thesefirmsmayuseenterpriselanguage-modelproductsfromotherprovidersoraccessChatGPToutsideanenterpriseworkspace.IfsuchuseiscorrelatedwithfirmcharacteristicsinthesamedirectionasChatGPTEnterpriseadoption,thismeasurementerrorcouldattenuateestimateddifferencesbetweenadoptersandnon-adopters.WedoexcludepublicfirmsthatmatchOpenAIcustomerrecordsforotherproducts(likeChatGPTBusiness)butnotaChatGPTEnterpriseaccount,whichavoidstheuseofknownOpenAIcustomersasuntreatedcontrols.

11Importantly,thispubliccompanysampledoesnotrequirejobtitle,industry,ortaskclassificationcoverage.ItisthereforedistinctfromthesamplesdescribedinSection

3.2

,althoughbothbeginwiththeChatGPTEnterpriseusagepanel.

12Weretainausage-matchedtickeronlywhenatleastoneobservedweekofChatGPTEnterpriseusagefallswithinanobservedCompustatfiscal-yearwindow.Of534usage-matcheddomesticpublic-companytickers,117donotmeetthiscondition:50havenoobservedCompustatfiscal-yearwindow,and67haveChatGPTEnterpriseusageonlyafterthelastavailableCompustatfiscal-yearwindow.

10

410tickers,havepositiveannualChatGPTEnterprisemessagevolume.Thenon-adoptercomparisongroupcontains11,784public-companytickers.ThesecountsdescribeU.S.-basedpublic-companyadoptersforwhichweobservematchedChatGPTEnterpriseusage;samplesizesinregressiontablesmaydifferbecausethesetofCompustatvariablesrequiredasnon-missingcovariatesvariesacrossspecifications.

4FourFactsaboutEnterpriseAIUsage

Usingthedatasetsdescribedabove,wedocumentfourfactsaboutthegrowthandcompositionofChatGPTEnterpriseuse.First,aggregateusehasgrownrapidly,includingwithincohortsoforganizationsthatadoptedatdifferenttimes.Second,earlyadoptionisconcentratedamonglarger,moreproductivefirmswithgreaterpriorinvestmentinintangibleandorganizationalcomplements.Third,useisbroadlydistributedacrossjobfunctionsandsenioritylevels,butitsintensityvariessystematicallyacrossworkergroups.Finally,ChatGPTEnterpriseusespansabroadrangeofknowledgeworktasks,whiletaskmixvariesacrossindustries,jobfunctions,andlevelsofseniority.

4.1ChatGPTEnterpriseusagehasgrownrapidly

WefirststudythegrowthofChatGPTEnterpriseusage,bothoverallandwithinfixedadoptioncohorts.Usingtheorganization-weekpaneldescribedinSection

3.1

,Figure

3

plotstotaloutputtokensrelativetoJune2025,overallandseparatelybyquarter-yearadoptioncohorts.

13

AggregateoutputtokensincreasedsevenfoldbetweenJune2025andMarch2026.Thisgrowthwasnotdrivensolelybytheadditionofneworganizations:outputtokensalsoincreasedsubstantiallywithinexistingadoptioncohorts.AmongfirmsthathadadoptedbyJune2025,forexample,outputtokensincreasedroughlyfourfoldoverthe

13ChatGPTEnterpriseincreasinglyincludesaccesstoCodexaspartoftheproductbundle.Duringoursampleperiod,however,enterprisetokenoutputisoverwhelminglygeneratedbyChatGPTandrelatednon-agenticAItools.AppendixFigure

A1

showsthattheaggregategrowthdocumentedhereisdrivenprimarilybynon-Codexoutput.ForananalysisofCodexusagewithinorganizations,wereferthereadertoJohnstonetal.

2026

.

11

sameperiod.Thus,enterprisedemandcontinuedtodeepenafterorganizationsenteredtheproduct,alongsidecontinuedgrowthinthenumberofadopters.Wealsofindthatusageacceleratedinearly2026acrossalladoptioncohorts.Becauseorganizationsthatadoptedatdifferenttimesexperiencedthisaccelerationsimultaneously,theincreaseappearstoreflectdevelopmentsaffectingChatGPTEnterprisecustomersbroadlyratherthanonlythenormalexpansionofusefollowingadoption.

4.2EarlyenterpriseAIadoptersarelarger,morevaluable,andmoreheavilyinvestedinintangiblesandorganizationalcomplements

WenextexaminehowfirmsthatadoptChatGPTEnterprisedifferfromnon-adoptersandwhichfirmcharacteristicsareassociatedwithusageintensityamongadopters.

Figure

2

providesdescriptivestatisticsfromacomparisonof2024firmcharacter-isticsforChatGPTEnterpriseadoptersandnon-adoptersintheCompustatpublic-companysample.Acrossallmeasures,adoptersaresubstantiallylarger.Medianrevenueis$2,275.1Mforadoptersversus$209.6Mfornon-adopters.Mediantotalassetsare$4,394.2Mversus$667.6M,andmedianemploymentis2,934workersversus424workers.Adoptersalsohavelargercapitalstocks,greatermarketvaluations,andgreaterR&Dspending.Mediannetproperty,plant,andequipment(PP&E)assetsare$271.2Mforadopterscomparedwith$43.7Mfornon-adopters.Medianmarketvalueis$4,997.2Mversus$316.4M,andthemedianresearchanddevelopmentexpensesare$113.1Mamongadopters,comparedwith$9.9Mamongnon-adopters.ThesepatternsindicatethatearlyChatGPTEnterpriseadoptersarenotrepresentativeoftheaveragepublicfirm;theyarelarger,morecapitalized,morevaluable,andmoreR&D-intensive.

4.2.1Financialcharacteristics

TheseunadjusteddifferencesmotivatetheregressionanalysisinTable

1

,whichrelatesChatGPTEnterpriseadoptiontolaggedfinancialcharacteristicsmeasuredatthepublicfirm-yearlevel.Importantly,ourestimatesdescribeconditionalassociationsbetweenthesepre-adoptionfirmcharacteristicsandtheprobabilitythatapublicfirmisobservedasa

12

ChatGPTEnterpriseadopter,andshouldnotbeinterpretedcausally.

Acrossspecifications,firmswithhigherrevenueperemployeearemorelikelytoadoptChatGPTEnterprise.Aone-log-pointincreaseinlaggedrevenueperemployeeisassociatedwithroughly0.4to0.9percentagepointshigheradoptionprobability.Thisassociationremainspositiveandstatisticallysignificantafteraccountingforassetsperemployee,PP&Eperemployee,employm