创新无国界？技术扩散的地理学（英）-欧洲央行

EUROPEANCENTRALBANK

EUROSYSTEM

UrselBaumann,ZoeCullen,EsterFaia,AnnalisaFerrando,RicardoPerez-Truglia,JuditRariga

WorkingPaperSeries

Innovationwithoutborders?

Thegeographyoftechnologicaldiffusion

No3246

Disclaimer:ThispapershouldnotbereportedasrepresentingtheviewsoftheEuropeanCentralBank(ECB).TheviewsexpressedarethoseoftheauthorsanddonotnecessarilyreflectthoseoftheECB.

ECBWorkingPaperSeriesNo32461

Abstract

Howwelldoesinnovationdiffuseacrossgeographicboundaries?Toshedlightonthisquestion,wepresentalarge-scalefieldexperimentinvolving3,300firmsacrosstwelveEuropeanUnioncountries.Weelicitfirms’perceptionsoftheshareofsimilarfirmsintheirowncountrythathadinvestedinartificialintelligence(AI),aswellasthecorrespondingshareamongsimilarfirmsinGermany,France,andItaly.WerandomlyprovidehalfofthesamplewithaccurateinformationaboutbothdomesticandforeignAIinvestment.Weshowthatfirmssubstantiallyunderestimatecompetitors’currentAIinvestment,bothdomesticallyandabroad,andthattheyupdatetheirexpectationsaboutcompetitors’futureAIinvestmentinresponsetotheinformationtreatment.Thetreatmentalsocausesastatisticallysignificantincreaseinfirms’ownexpectedAIinvestmentrate.Wefindstrongstrategiccomplementaritieswithinborders:a1ppincreaseintheexpectedshareofdomesticpeersinvestinginAIraisesafirm’sownexpectedAIinvestmentrateby0.570pp.Thesecomplementaritiesareabsentacrossborders:theeffectofanincreaseintheexpectedshareofforeignpeersinvestinginAIonafirm’sownexpectedAIinvestmentrateisstatisticallyinsignificant.Overall,ourevidenceshowsthatinnovationdiffusionandstrategiccomplementaritiesinAIinvestmentaremuchstrongerdomesticallythaninternationally.

JELClassification:O33,D22,C93,L21.

Keywords:Innovationdiffusion,artificialintelligence,fieldexperiment,surveydata.

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Non-technicalsummary

Thediffusionofnewtechnologiesacrossfirmsisacentraldriverofproductivitygrowth.Despitetherapidexpansionofartificialintelligence(AI)asageneralpurposetechnology,itsadoptionremainsunevenacrossfirmsandcountries,includingwithinintegratedeconomicareassuchastheeuroarea.UnderstandingwhyAIinvestmentremainsconcentratedinsomefirmsandlocationswhilelagginginothersisessentialforbotheconomicresearchandpolicydesign.

Thispaperexamineswhethercompetitivepressurefrompeersinfluencesfirms’decisionstoinvestinAI,andwhetherthispressurediffersdependingonwhethercompetingfirmsarelocateddomesticallyorabroad.Toaddressthesequestions,wedesignedalarge-scalefieldexperimentintegratedintotheSurveyontheAccesstoFinanceofEnterprises(SAFE),aregularfirm-levelsurveyjointlyconductedbytheEuropeanCentralBankandtheEuropeanCommission.Theexperimentcoversapproximately3,300firmsacrosstwelveeuroareacountriesandwasimplementedinthefourthquarterof2025.

TheexperimentaldesignleveragesthefactthatfirmsformbeliefsabouttheextentofAIadoptionamongtheircompetitors,andthatthesebeliefsoftendeviatesubstantiallyfromreality.Initially,thesurveyelicitedeachfirm’sperceptionoftheshareofcomparabledomesticfirms-definedasfirmsofsimilarsizeandoperatinginthesamesector-thathadinvestedinAIbymid-2025.Italsocollectedestimatesofthecorrespondinginvestmentratesamongfirmsinthethreelargesteuroareaeconomies(Germany,France,andItaly).Subsequently,halfofthesurveyedfirmswererandomlyassignedtoreceiveaccurate,factualinformationabouttheseinvestmentrates,drawnfromthepreviousSAFEsurveyround.Afterreceivingtheinformation,firmswereaskedtoupdatetheirexpectationsaboutfutureAIinvestmentamongcompetitorsandtoreporttheshareoftheirownplannedinvestmenttheyintendedtoallocatetoAIoverthecomingtwelvemonths.

Thefindingshighlightthreekeyresults.First,firmssystematicallyunderestimatetheextenttowhichtheircompetitorshaveinvestedinAI,bothdomesticallyandabroad.Onaverage,thegapbetweenactualinvestmentratesandfirms’priorbeliefsexceededtwentypercentagepointsandwasskewedtowardsunderestimationacrossnearlyallcountries.Moreover,firmstendedtomisperceivetheircountry’srelativepositionwithinEurope,systematicallyperceivingAIinvestmentasmoreconcentratedinthethreelargesteconomiesthanthedatasuggest.Thisdistortionpersistedevenwhentheirowncountry’sAIadoptionratewasabovetheeuroareaaverage.Second,providingaccurateinformationmeaningfullyshiftedfirms’beliefs.FirmsthatreceivedfactualsignalsrevisedtheirexpectationsregardingcompetitorAIinvestmentinamannerconsistentwithBayesianlearning.Themagnitudeofthesebeliefrevisionscorrelated

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directlywiththegapbetweentheinformationprovidedandfirms’priorbeliefs.Theestimatedweightthatfirmsplacedonthenewinformationalignswithfindingsfromsimilarinformation-provisionexperimentsconductedinothercontexts.Third,andmostimportantly,thepaperidentifieshowupdatedbeliefstranslateintochangesininvestmentplans.Usingarandomisedcontrolledtrialwefindthatprovidingaccurateinformationoncompetitors’pastAIinvestmentcausesfirmstorevisetheirexpectationsaboutfutureadoptionupward.Specifically,aone-percentage-pointincreaseintheexpectedshareofdomesticcompetitorsinvestinginAIraisesafirm’sownexpectedAIinvestmentratebyapproximately0.57percentagepoints.Bycontrast,revisedbeliefsaboutforeigncompetitorinvestmenthavenostatisticallysignificanteffectonfirms’ownAIinvestmentplans.Thisasymmetryholdsacrossvariousrobustnesschecksandsubsamples.

ThesefindingshaveimportantimplicationsforthegeographyofAIdiffusionandforEuropeaneconomicpolicy.First,theysuggestthatinformationalfrictions-suchasfirms’tendencytounderestimatepeeradoption-maycontributetounderinvestmentinAI,independentlyoffinancialconstraintsortechnologicalbarriers.Second,thesharpasymmetrybetweendomesticandforeigncompetitivepressureimpliesthat,evenwithintheSingleMarket,cross-borderspilloversininnovationremainlimited.Althoughfirmsobserveandupdatebeliefsaboutforeigncompetitors,thesebeliefsdonotappeartodrivechangesinbehaviour.Third,theresultshelpexplainwhyregionaldisparitiesinAIadoptionmaypersist:iffirmsrespondprimarilytotheactionsofdomesticpeers,gapsbetweenhigh-adoptionandlow-adoptioncountriesarelikelytobeself-reinforcing.

Fromapolicyperspective,ourfindingssuggestthatfinancialincentivesalonemaynotsufficetoaccelerateAIdiffusionacrosstheeuroarea.Complementarymeasures,suchasinformationcampaignstoimprovefirms’awarenessofpeeradoptionandthebroaderspreadofnewtechnologies,couldrepresentcost-effectivetoolstostimulateinvestment,particularlyincountriesorsectorswhereadoptionlags.Morebroadly,theresultshighlightthelimitationsofcross-bordercompetitivepressureasadriverofconvergenceininnovation,underscoringthecontinuedimportanceofdomesticbusinessenvironmentsandthedepthofintegrationofEuropeanmarketsforknowledgeandinnovation.

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1Introduction

TheriseofArtificialIntelligenceandtheexpansionoftheknowledgeeconomycanhaveprofound

consequencesforgrowth.Thismakesitvitaltounderstandtheunderlyingdeterminantsof

innovationanditsdiffusioninspace.Strategiccomplementarities-theideathatthemarginal

benefitofoneinnovationactivityincreaseswhenanotherispresent-areakeyforcesinceAI

isageneral-purposetechnologythatrarelygeneratesvalueinisolation.Itseffectiveadoption

dependsonlearningcomplementaritieswithotheradopters;furthermorepressurefromcompetitorsactsasastrategiccatalystforcingfirmstoinnovate.Thoseinsightshaveshapedinfluential

workontechnologydiffusion,fromtheadoptionofhybridcorninresponsetolocalcompetitivepressures(

Griliches

,

1960

,

1987

)totheroleoftradeandcross-borderknowledgeflowsinshapinginnovationandfirmdynamics(

KellerandYeaple

,

2013

).Morebroadly,thisliteraturesuggeststhatknowledgespilloversfromabroadmaybeespeciallyvaluableforgrowthbecausetheyaremorelikelytoembodygenuinelynovelideas.Yetthesameforeignspilloversmayexertweakerpressureonfirms’behaviorifforeigncompetitorsfacecultural,linguistic,orpracticalbarrierstoenteringlocalmarkets.Inpractice,then,thesamesignal—forexample,thatcompetitorsareinvestinginanewtechnology—mayleadfirmstoresponddifferentlydependingonwhetherthosecompetitorsaredomesticorforeign.

Webeginwithasimplemodelofstrategicinteractionunderincompleteinformationtoguideourresearchdesign.Buildingon

AngeletosandPavan

(

2004

),weadapttheirframeworktothecontextoftechnologyinvestmentandextendittoamulti-countrysetting.Firmschoosehowmuchtoinvestinanewtechnologywithoutfullyobservingitsunderlyingproductivity.Instead,theyformbeliefsfromnoisyinformationandfromtheirexpectationsaboutcompetitors’choices.Afirm’soptimalinvestmentthereforedependsnotonlyonitsownassessmentofthereturnstoAI,butalsoonwhatitexpectscompetitorstoinvest.Theseexpectationsmatterthroughtwomainchannels.First,thereisacompetitionchannel:ifcompetitorsinvestmore,afirmmayalsowanttoinvestmoretoavoidfallingbehind.Second,thereisalearningchannel:thebehaviorofsimilarfirmsmayrevealinformationabouttheunderlyingprofitabilityofthetechnology.

Themodelpredictsthatfirmsshouldrespondtoinformationaboutotherfirms’investmentdecisions,andthatthesizeofthisresponsemaydependcriticallyonwhetherthosefirmsaredomesticorforeign.Ifdomesticfirmsareclosercompetitorsthanforeignfirms,thecompetitionchannelimpliesthatafirmshouldrespondmorestronglytoinvestmentbydomesticfirmsthanforeignfirms.Ifproductivityismorecorrelatedamongdomesticfirmsthanamongforeignfirms,thelearningchannelyieldsthesameprediction:domesticinvestmentshouldbemoreinformativethanforeigninvestment.Thus,therelativeeffectsofinformationaboutdomesticandforeign

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investmentprovideatestofthetechnologicalandcompetitivefrictionsthatseparatemarketsacrossborders.

WestudyAIinvestmentanduse,animportantsettinginwhichfirms’investmentdecisionsarebothcostlyandconsequential.UsingAIeffectivelyoftenrequiresskillupgradingandorganizationalchange,butitcanalsoraiseproductivity,expandsales,andincreasefirmmarketvalue(

Babinaetal.

,

2024

).PolicymakersthereforeincreasinglyviewAIasakeydriverofgrowthandindustrialcompetitiveness.Ourempiricalsettingisalarge-scalefieldexperimentwithfirmsintwelveEuropeanUnion(EU)countries.Thissettingprovidesanaturallaboratoryforstudyingdomesticversusforeigncompetitivepressure.TheEuropeanSingleMarketwasexplicitlydesignedtoexposefirmstocross-bordercompetitionandtherebyfosterinnovationandgrowth.Atthesametime,AIdiffusionremainshighlyunevenacrosscountriesandfirms,suggestingthatimportantbarrierstodiffusionpersistevenwithinanintegratedeconomicarea.

Weembeddedourinformation-provisionexperimentintheSurveyontheAccesstoFinanceofEnterprises(SAFE),along-runningsurveyconductedbytheEuropeanCentralBankandtheEuropeanCommission.SAFEprovidesauniquelyharmonizedcross-countrysurveyinfrastructureforimplementingtheexperiment.Becauseourdesignrandomizestailoredinformationaboutdomesticandforeignfirms’investmentdecisions,weincludedaseriesofquestionsinanearliersurveywavetoconstructtheinformationthatwouldsubsequentlyberandomized.Moreprecisely,weusedatafromanearlierSAFEwavetocompute,foreachcountry-sector-sizecell,theshareoffirmsthathadinvestedinAIbyJune2025.Wethenusedthesedataintheinformation-provisionexperiment,whichwasimplementedintheexperimentalwave.

Theexperimentfirstelicitsfirms’priorbeliefsaboutdomesticinvestment:thatis,theshareofsimilarfirms—thoseinthesamesectorandsizeclassandfromthesamecountry—thathadinvestedinAI.Itthenelicitsfirms’priorbeliefsaboutforeigninvestment:thatis,theshareofsimilarfirmsinthesamesectorandsizeclassfromthethreelargestEUeconomies—Germany,France,andItaly,hereafterreferredtoasthebig-3—thathadinvestedinAI.Intheinformation-provisionstage,halfofthefirmsarerandomlyassignedtoacontrolgroupandreceivenoadditionalinformation.TheotherhalfareassignedtoatreatmentgroupandreceiveinformationabouttheshareofdomesticandforeignfirmsthathadinvestedinAI,asmeasuredbeforetheexperiment.Wethenelicitfirms’posteriorbeliefsaboutbothdomesticandforeigninvestmentrates.Finally,wemeasureeachfirm’sownexpectedAIinvestmentrate,definedastheshareoftotalinvestmentthatitexpectstoallocatetoAIoverthenexttwelvemonths.Thisdesignallowsustotracethefullchainfrominformationtobeliefstointendedbehavior.

Ourmainanalysissampleconsistsof3,316firmsthatcompletedourmoduleandarelocated

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inthefollowingtwelveEUcountries:Austria,Belgium,Finland,France,Germany,Greece,Ireland,Italy,theNetherlands,Portugal,Slovakia,andSpain.Thescaleofthesurveyprovidessubstantialstatisticalpowertodocumentfirms’perceptionsoftheirdomesticandforeignpeers,andtodistinguishtheeffectsofdomesticandforeignbeliefsonfirms’owninvestmentchoices.

WebeginbydocumentingsubstantialunevennessinAIinvestmentanduseacrossthesetwelveEUcountries.AsofJune2025,AIinvestmentismuchmoreprevalentinsomecountriesthaninothers.TheshareoffirmsinvestinginAIaveragesabout28%,butitrangesfrom20%inGreeceto48%inAustria.TheshareoffirmsinvestinginAIisslightlyloweramongthebig-3(25%)thanamongtheotherninecountries(29%).CurrentAIuseissimilarlyunevenacrosscountries.Firmsdiffersharplyintheirintensityofuse:30%reportnoAIuse,32%reportveryinfrequentuse,29%reportmoderateuse,andonly9%reportsignificantAIuse.Indeed,AIuseandinvestmentinthetwelveEUcountrieswestudyarebroadlycomparabletothoseintheUnitedStates,bothinoveralllevelsandintheunevennessofdiffusionacrossfirms(

Baslandze

etal.

,

2026

;

Bonneyetal.

,

2026

;

Yotzovetal.

,

2026

).

Wethenshowthatfirmsholdlargeandsystematicallybiasedbeliefsaboutcompetitors’AI

investment.Mostfirmsunderestimatebothdomesticandforeigncompetitors’AIinvestment,

oftenbysubstantialmargins.Onaverage,firmsunderestimatedomesticcompetitors’AIinvestmentby14ppandforeigncompetitors’AIinvestmentby7pp.Whiledomesticandforeignmisperceptionsarepositivelycorrelated,theyarefarfromperfectlycorrelated.Thisindicatesthateachcontains

substantialindependentvariationtoallowustoseparatelyidentifytheireffects.

Acountry-levelbreakdownrevealstwoadditionalpatterns.First,underestimationisespeciallysevereincountrieswhereactualAIinvestmentishigh,suggestingthatfirms’beliefsarecompressedrelativetothetruecross-countryvariation.Second,firmssystematicallyoverstatethebig-3’srelativeposition:theybelievethatbig-3firmsinvestmoreinAIthanfirmsintheirowncountry,eventhoughtheaverageinvestmentshareissimilarbetweenthebig-3andtheotherninecountries.Thesepatternssuggestabroadercenter-peripherymisconception,inwhichfirmsperceiveAIinvestmentasconcentratedinasmallsetoftechnologicallyadvancedeconomieseventhoughitismorewidelydispersedinpractice.

Weshowthatfirmsupdatetheirbeliefsinresponsetotheinformationtreatment.FirmsthatinitiallyunderestimatecompetitorAIinvestmentrevisetheirbeliefsupward,firmsthatoverestimaterevisedownward,andfirmswithaccuratepriorsupdatelittle.Consistentwithbaselineunderestimation,factualinformationraisesbothdomesticandforeignposteriorbeliefs,by4.3ppand3.3pprespectively.WeusetheexperimentaldatatoestimateasimpleBayesianlearningmodelofexpectationformation.Theimpliedlearningweightsare0.35fordomestic

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expectationsand0.36forforeignexpectations—meaningthatfirmsplaceroughlyone-thirdweightonthesignalandtwo-thirdsweightontheirpriorbeliefs.Thisevidenceindicatesthatrespondentspaidattentiontotheinformationandvieweditascredibleandrelevant.Wealsodocumentasymmetriccross-marketextrapolation:firmsuseforeigninvestmenttoforecastdomesticinvestment,butnotviceversa.Thissuggeststhatfirmsexpectdomesticmarketstopartlycatchuptothebig-3,butdonotexpectinvestmentintheirowncountrytoaffectinvestmentinthebig-3.

Theinformationinterventionchangednotonlyfirms’beliefsaboutcompetitors,butalsotheirownintendedAIinvestmentoverthenexttwelvemonths.Treatedfirmsexpecttoallocate10.13%oftheirinvestmenttoAI,comparedwith8.33%amongcontrolfirms.This1.8pptreatmenteffectisstatisticallysignificant(p-value<0.001).Weshowthatthetreatmenteffectisrobusttoalternativespecificationsandfalsificationtests.Forexample,thetreatmenthasnoeffectonpre-treatmentAIuseorpriorbeliefs.Moreover,aspredictedbyBayesianlearning,thetreatmenteffectsonfutureAIinvestmentareconcentratedamongfirmsthatinitiallyunderestimatedcompetitorAIinvestmentthemost.

TheabovetreatmenteffectscorrespondtothejointprovisionofinformationabouttheAIinvestmentofdomesticandforeignfirms.Todisentanglebetweenthedomesticandforeignchannels,weestimateaTwo-StageLeastSquares(2SLS)model.Following

CullenandPerez-

Truglia

(

2022

),thismodelusestheexogenousvariationindomesticandforeignposteriorbeliefsinducedbytherandomizationofinformation.Theestimatesshowasharpasymmetry,withthebehavioralresponseoperatingprimarilythroughbeliefsaboutdomesticcompetitors.Ontheonehand,firms’ownexpectedAIinvestmentraterespondsstronglytodomesticposteriorbeliefs:a1ppincreaseintheperceivedshareofdomesticcompetitorsinvestinginAIraisesthefirm’sownexpectedAIinvestmentrateby0.570pp.Thiseffectisstatisticallysignificant(p-value<0.001)andalsolargeinmagnitude:itimpliesanelasticityof1.6betweenowninvestmentandthebeliefaboutdomesticinvestment.Bycontrast,theeffectofa1ppincreaseinthebeliefinforeigninvestmentisclosertozeroandstatisticallyinsignificant.Moreover,wecanrejectthenullhypothesisthattheeffectsofdomesticandforeignbeliefsareequaltoeachother(p-value<0.001).

Ourmodelpointstotwochannelsthatcouldexplainthesharpdifferencebetweentheeffectsofdomesticandforeignbeliefs.Thefirstisacompetitionchannel.Accordingtothischannel,firmsrespondtodomesticpeers’AIinvestmentbecausetheyviewthosepeersasclosecompetitorsanddonotwanttofallbehind.Bycontrast,theyrespondlesstoforeignpeers’investmentiftheyarenotperceivedasdirectcompetitors.Thesecondisalearningchannel.

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Accordingtothischannel,firmsrespondtodomesticpeers’AIinvestmentbecausedomesticpeersoperateinsimilarcultural,institutional,andorganizationalenvironments.Thus,learningthatthesepeersareinvestinginAIsignalsthatthetechnologymaybemorevaluablethanthefirmpreviouslybelieved.Bycontrast,ifforeignpeersoperateinsufficientlydifferentenvironments,thentheirAIinvestmentwouldbelessinformativeaboutthevalueofAIforfirmsoutsidethoseforeignmarkets.

Becausethecompetitionandlearningchannelsarecloselyintertwined,disentanglingthemischallenging.Nevertheless,weprovidesuggestiveevidencethroughheterogeneityanalysis.Intuitively,thecompetitionchannelshouldvarywiththedegreeofcompetitioninthemarket.Intheextremecaseofaperfectmonopolist,afirmcouldstilllearnfromotherfirms’AIinvestmentdecisions,butthecompetitionchannelwouldbecompletelyabsent.Consistentwiththecompetitionchannel,wefindthattheeffectofbeliefsaboutdomesticpeersisstrongerwhenthedomesticmarketislessconcentratedandwhenthefirmislessexposedtoforeigncompetitors.

Takentogether,theresultspointtoanimportantlimitoncross-borderdiffusion.AnincreaseinperceivedAIinvestmentbyforeignfirmsdoesnotcausefirmstoincreasetheirownAIinvestment,suggestingthatforeigncompetitionmaybelesseffectivethandomesticcompetitioninencouragingtechnologyadoption,eveninanintegratedeconomicregionsuchasEurope.Thisfindinghelpsquantifyonechannelthroughwhichinnovationmayremaingeographicallyconcentrated:iffirmsrespondlesstoforeigncompetitors,regionalgapsinadoptionmaybehardertoclose.Inthissense,internationalknowledgespilloversappeartobesubjecttoaformofgravity:ideascantravelacrossborders,buttheirbehavioralimpactweakenswitheconomic,cultural,andinformationaldistance.Morebroadly,ourresultsspeaktotheextenttowhichtheEuropeanprojecthassucceededinexposingfirmstocross-bordercompetitivepressureandtherebyfosteringinnovation.

Ourstudyrelatesto,andcontributesto,severalstrandsofliterature.Mostimportantly,ourfindingsspeaktoworkoninternationalknowledgediffusionanditsgeographicfrictions(

Coe

andHelpman

,

1995

;

EatonandKortum

,

2002

;

Keller

,

2004

;

CominandHobijn

,

2010

;

Keller

andYeaple

,

2013

;

Kalyanietal.

,

2025

),aswellastoresearchontechnologyadoptionandfirms’exposuretoforeignfirmsandmarkets(

Pavcnik

,

2002

;

AmitiandKonings

,

2007

;

Atkinetal.

,

2017

;

Alfaro-Urenaetal.

,

2022

;

Bilginetal.

,

2024

).Wecontributetothisliteraturebyproviding,toourknowledge,thefirstexperimentalmeasurementofinnovationdiffusionwithinandacrossnationalborders.

Morebroadly,ourpaperrelatestothestudyofstrategiccomplementarities.Whilethis

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literatureismainlytheoretical,agrowingsetofempiricalstudieshasbeguntotestforstrategiccomplementaritiesinfirmbehavior(e.g.,

Bloometal.

,

2013

;

Lin

,

2023

;

Bilginetal.

,

2024

).Inparticular,ourstudybuildsonexperimentalworkby

Cullenetal.

(

2025

)and

Menkhoff

(

2025

),whostudytheeffectsofprovidingfirmswithinformationaboutpeeradoptionofadvancedtechnologies.Beyondtheinnovationcontext,anothernotableexampleis

Coibionetal.

(

2021

),whostudyhigher-orderbeliefsamongNewZealandfirms,suchasfirms’beliefsaboutotherfirms’inflationexpectations.OurpaperalsorelatestothegrowingliteratureonthedeterminantsandconsequencesofAIadoption(e.g.,

Zolasetal.

,

2021

;

Bencivellietal.

,

2025

).

Therestofthepaperisorganizedasfollows.Section

2

presentsthemulti-countrymodelofstrategiccomplementaritiesintechnologicaladoption.Section

3

describestheinstitutionalsettinganddata.Section

4

discussestheresearchdesign.Section

5

discussesAIinvestmentandfirms’misperceptionsaboutcompetitorAIinvestment.Section

6

documentstheeffectoftheinformationtreatmentonfirms’expectations.Section

7

presentstheeffectsoftheinformationonthefirm’sownexpectedAIinvestmentrate.Thelastsectionconcludes.

2Conceptualmodel

Tomotivatetheexperimentaldesignandthekeyhypotheses,weprovideasimpletwo-countrymodelofAIAdoptionwithlearningandstrategiccomplementarities.Firmshavetodecidewhethertoadoptatechnologythatfeaturesstrategiccomplementaritiesacrossfirms,whichmaycaptureaspectssuchasinnovationracesandnetworkorscaleexternalities(wherecertaininvestmentsaremoreproductivewhenmorefirmsadoptthem;see

CooperandJohn

(

1988

)).Firmshaveincompleteinformationaboutthefundamentals,namelythereturnorproductivityofthetechnology,butcanlearnfromtheirownsignals,frompublicsignals,andalsofromothers.Sociallearningisasecondformofstrategiccomplementaritiesacrossfirms.Thismodelisanextensio