2024年第二季度生成式人工智能報告

Nowdecidesnext:

GettingrealaboutGenerativeAI

Deloitte’sStateofGenerativeAIintheEnterpriseQuartertworeport

April2024

/us/state-of-generative-ai

Tableofcontents

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Foreword

+

Introduction

+

Now:Keyfindings

1Valuecreation

2Scalingup

3Buildingtrust

4Evolvingtheworkforce

+

Next:Lookingahead

+

Authorship&Acknowledgments

+

AbouttheDeloitteAIInstitute

AbouttheDeloitteCenterforIntegratedResearch

AbouttheDeloitteCenterforTechnology,Media&Telecommunications

+

Methodology

2

Introduction

Foreword

WehavetraveledalongwaysincetheGenerativeAIspaceracekickedoffinNovember2022—andyet,weknowwearestillatthebeginningofthislongandexcitingtransformation.Everyday,we

talkwithclientsabouthowmuchthereistofocusoninthemoment,howexplosivethepaceofchangeis,andhowchallengingitcanbeamidtheexcitementtotakealonger-termview.

“Weareinthefirstinningofa

thousand-inninggameandthere’ssomuchtobefiguredout.”

-Chiefanalyticsofficerinfinancialservices

Weseeorganizationsstartingtoachievebenefitsandmovetowardanearfuturewherethis

earlystageofGenerativeAItoolsiswidelydispersedanddrivingnewvalue.Buttherearealsosomehardrealitiestodealwithasbusinessleaderslooktoscaleandrealizethepotentialofthispowerfultechnology.

TheStateofGenerativeAIintheEnterprise:GettingrealaboutGenerativeAIcapturesanewsnapshotofthistransformativetimefromtheperspectivesofnearly2,000businessandtechnologyleaders,allfromorganizationsthatareactivelydeployingandscalingGenerativeAItoday.Echoingour

3

manyclients,fromtheseexecutiveswehearthatwhileexcitementpersistsitmaybeatitspeakasleaderscomeupagainstculturalchallenges,questionsabouthowtomanagetheirworkforces,andissueswithtrustthat—atleastfornow—standinthewayofunlockingGenerativeAI’sfullvalue.

Alltold,itisexcitingthatGenerativeAI’spotentialisbeginningtoweaveitswaydeeperintothe

foundationsofhoworganizationsoperateandwecontinuetolearnmoreaboutemergingleadingpractices.Amidthosedevelopments,wealsocontinuetoseethatachievingvaluewithGenerativeAIconnectshandinhandwithkeepinghumansatthecenter.

Learnmoreabouttheseriesandsignupforupdatesat

/us/state-of-generative-ai

.

NitinMittal,CostiPerricos,KateSchmidt,BrennaSnidermanandDavidJarvis

Introduction

GettingrealaboutGenerativeAI

Istheinfatuationphaseover?QuartertwoofDeloitte’sglobalquarterlysurveyfoundmanyorganizations

beginningtogetdowntotheseriousworkofmakingGenerativeAI’svastpotentialareality.

Thisreportpresentsfindingsfromthesecondin

Deloitte’songoingseriesofquarterlyglobalsurveysonGenerativeAIintheenterprise.Togainadditionalcontextforourwavetworesearch,wealso

conductedaseriesofin-depthinterviewswithseniorexecutivesfromabroadrangeofindustries.

Ourresearchshowsthatorganizationsareincreasinglyprioritizingvaluecreationanddemandingtangible

resultsfromtheirGenerativeAIinitiatives.ThisrequiresthemtoscaleuptheirGenerativeAIdeployments—advancingbeyondexperimentation,pilotsandproofsofconcept.Transitioningtolarge-scaledeployments

willincreaseGenerativeAI’simpactonthebusiness

andexpanditsreachtoamuchlargersegmentoftheworkforce.Successfulscaling,inturn,presentsawiderangeofchallenges,encompassingeverythingfrom

strategy,processesandpeopletodataandtechnology.

Twoofthemostcriticalchallengesforscalingare

buildingtrust(intermsofmakingGenerativeAI

bothmoretrustedandtrustworthy)andevolving

theworkforce(addressingGenerativeAI’spotentiallymassiveimpactonworkerskills,rolesandheadcount).

Herewe’lltakeanin-depthlookatallfourofthese

areas—value,scaling,trustandworkforce—tohelp

organizationsmoveforwardmoreeffectivelyontheirGenerativeAIjourneys.Futuresurveyreportswill

focusselectivelyonotherkeychallengestosuccessfulGenerativeAIscalingandvaluecreation.

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5

Introduction

GettingrealaboutGenerativeAI(cont’d)

Valuecreation

?Thepercentageoforganizationsreportingtheywerealreadyachievingtheirexpectedbenefitstoa“l(fā)arge”or“verylarge”extentis18%–36%,dependingonthetypeof

benefitbeingpursued.

?Organizationsthatreported“high”or“veryhigh”levelsofGenerativeAIexpertisearescalingGenerativeAImuchmoreaggressively—andareachievingtheirdesiredbenefitstoamuchgreaterdegreethanothers.

?OrganizationsprimarilyplantoreinvestthesavingsfromGenerativeAIintoinnovation(45%)andimprovingoperations(43%)—addressingthevalueequationfrombothsides.

Scalingup

?Leadersseescalingasessentialforcreatingvalue,increasingGenerativeAI’simpact

onthebusinessandexpandingthetechnology’suserbase.ThescalingphaseiswhenGenerativeAI’spotentialbenefitsareconvertedintoreal-worldvalue.It’salso,however,whenanorganization’spotentialconcernscanbecomereal-worldbarrierstosuccess.

?Commonareasofconcernincludedatasecurityandquality,explainabilityofGenerativeAIoutputs,andworkermistrustorlackoffamiliaritywithGenerativeAItools.

?WorkforceaccesstoapprovedGenerativeAItoolsandapplicationsremainsquitelow,withnearlyhalfofsurveyedorganizations(46%)reportingtheyprovidedapproved

GenerativeAIaccesstojustasmallportionoftheirworkforces(20%orless).However,mostworkerswithinternetaccesswillhaveaccesstopublicGenerativeAItoolsandcouldbeusingthemwithoutconsent.

AllstatisticsnotedinthisreportanditsgraphicsarederivedfromDeloitte’ssecondquarterlysurvey,conductedJanuary–February2024;TheStateofGenerativeAIintheEnterprise:Nowdecidesnext,areportseries.N(Total

leadersurveyresponses)=1,982.

GenerativeAIisanareaofartificialintelligenceandreferstoAIthatinresponsetoaquerycancreatetext,

images,videoandotherassets.GenerativeAIsystemscaninteractwithhumansandareoftenbuiltusinglargelanguagemodels(LLMs).Alsoreferredtoas“GenAI.”

Introduction

GettingrealaboutGenerativeAI(cont’d)

Buildingtrust

?Lackoftrustremainsamajorbarriertolarge-scale

GenerativeAIadoptionanddeployment.Twokey

aspectsoftrustweobservedare:(1)trustinthequalityandreliabilityofGenerativeAI’soutputand(2)trust

fromworkersthatthetechnologywillmaketheirjobseasierwithoutreplacingthem.

?TrustissueshavenotpreventedorganizationsfromrapidlyadoptingGenerativeAIforexperiments

andproofsofconcept,with60%reportingthey

areeffectivelybalancingrapidimplementationwithriskmanagement.Trustislikelytobecomeabiggerissue,however,asorganizationstransitiontolarge-scaledeployment.Manyreportedtheyarecurrentlyinvestingsignificanttimeandeffortintobuilding

guardrailsaroundGenerativeAI.

?Organizationsthatreported“high”or“veryhigh”levelsofexpertiserecognizetheimportanceofbuildingtrustinGenerativeAIacrossnumerousdimensions(e.g.,input/outputquality,transparency,workerempathy)andareimplementingprocessestoimproveittoamuchgreaterextentthanareotherorganizations.

Evolvingtheworkforce

?Mostorganizations(75%)expectthetechnologytoaffecttheirtalentstrategieswithintwoyears;32%oforganizationsthatreported“veryhigh”levelsofGenerativeAIexpertisearealreadymakingchanges.

?Themostexpectedtalentstrategyimpactsareprocessredesign(48%)andupskillingorreskilling(47%).

?GenerativeAIisexpectedtoincreasethevalueof

sometechnology-centeredskills(suchasdataanalysis)aswellashuman-centeredskills(suchascriticalthinking,creativityandflexibility),whiledecreasingthevalueofotherskills.

?Intheshortterm,moreorganizationssaidtheyexpectthetechnologytoincreaseheadcount(39%)thanto

decreaseheadcount(22%)—perhapsduetoincreasedneedsforGenerativeAIanddataexpertise.

AbouttheStateof

GenerativeAIintheEnterprise:Wavetwosurveyresults

Thewavetwosurveycoveredinthisreportwasfieldedto1,982director-toC-suite-levelrespondentsacross

sixindustriesandsixcountriesbetweenJanuary

andFebruary2024.Industriesincluded:Consumer;Energy,Resources&Industrials;FinancialServices;

LifeSciences&HealthCare;Technology,Media&

Telecom;andGovernment&PublicServices.Our

Q2surveyfindingsareaugmentedwithover20executiveinterviews.Thissecondreportispartofayearlong

seriesbytheDeloitteAIInstitutetohelpleaders

inbusiness,technologyandthepublicsectortrack

therapidpaceofGenerativeAIchangeandadoption.

TheseriesisbasedonDeloitte’sStateofAIintheEnterprisereports,whichhavebeenreleasedannuallythepastfiveyears.

Learnmoreat/us/state-of-generative-ai.

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Now:Keyfindings

7

8

Now:Keyfindings

1Valuecreation

Proving,measuringandcommunicatingvalueiscrucial

toanorganization’sGenerativeAIjourney.Inoursurveyandinterviews,manyorganizationsreportedthey

wereincreasinglyemphasizingtheneedforGenerativeAIinitiativesandinvestmentstohaveclearvalue

objectivesanddelivertangibleresults,ratherthansimplybeingviewedasexperimentsorlearningexperiences.

AsoneexecutiveataFortune500manufacturingcompanynoted:“Wehaveaverystrictinternalrulethatifwedon’tseevaluefromourGenerativeAI

solutions,wewon’tdoitorwewon’tscaleit.”

Thatsaid,therearemanywaystodefineand

measurevalue—especiallyforatechnologywiththe

transformationalpotentialofGenerativeAI.Although

financialreturnoninvestment(ROI)isimportant,valuedriverssuchasinnovation,strategicpositioningand

competitivedifferentiationcanbeevenmoreimportant.

ValueobjectivesandprioritiesforGenerativeAIcan—

andshould—varybyorganization,industryandusecase.Wherethetechnology’spotentialimpactisstrategic

andtrulygame-changing,theneedandlatitudefor

experimentation,learningandinnovationaremuch

greater(withlessemphasisonimmediatepayback)thaninsituationswhereproductivityandcostsavingsaretheprimaryexpectedbenefits.

Moreover,GenerativeAIissonew—andadvancingsoquickly—thataccuratelyestimatingbenefitsismuch

harderthanforanestablishedtechnologywithaproventrackrecord.

“Anytechnologythat’salittleoverayearold,nobody’s

goingtohaveayear’sworthofdatatodoabackward-

lookingROI,”saidonetechcompanyexecutivewe

interviewed.“AndwiththefundamentalandfoundationalchangesGenerativeAIoffers,it’sveryhardtoevenofferaforward-looking[totalcostofoperating]orROIbecausethere’ssomanypossibilitiesofimpactandvariedways

tointegrateitintoyourbusiness.”

Therefore,manyforward-thinkingorganizationsareimplementingGenerativeAIwithoutspecificROItargetsastheyrealizetheycan’taffordtogetleftbehindinthiscriticalandfast-movingmarket.

Now:Keyfindings

GenerativeAI“experts”areachievingtheirdesiredbenefitstoamuchgreaterdegree.

Ineverycategory,organizationsthatratedthemselves

ashaving“high”or“veryhigh”levelsofGenerativeAI

expertisereportedmuchgreatersuccessatachievingtheirdesiredbenefits.Theiradvantagewasgreatestinstrategicandgrowth-relatedareassuchasimprovingproductsandservicesandencouraginginnovationandgrowth.

“l(fā)arge”or“verylarge”extentis18%–36%,dependingonthetypeofbenefitbeingpursued.

OrganizationsarestartingtodemandtangiblebusinessvaluefromGenerativeAI,andsomearebeginningtoachievereal-worldbenefits.

Asonepublicsectorexecutivetoldus,“Thebigselling

pointisifImakeaninvestmentanddosomethinglike

this,what’sthetangiblereturnandwhataresomeeasy

returns?Andthenwhataremorecomplicatedlonger-termreturnsthattakemoreinvestmentmoney?IfIcandosomeoftheeasieronesandbuildonthem,itcantranslateinto‘Ithinkthiswouldbeworthittoinvestalotmoremoney.’Ibelievealotofentitiesinoursectorareatthatpoint.”

TheorganizationswesurveyedexpectGenerativeAItodeliverabroadrangeofbenefits,withthemostcommonobjective—atleastintheshortterm—beingimproved

efficiencyandproductivity(56%),whichisconsistentwiththeresultsfromlastquarter’ssurvey.Thepercentageofrespondentswhosaidtheirorganizations’GenerativeAIinitiativeswerealreadyachievingexpectedbenefitstoa

Achievingbenefits

Ofthoseseekingthebenefit,thepercentageofrespondentsachievingthebenefittoalargeextentormore

Veryhighexpertise

Overall

63%

55%

54%

48%

48%

48%

40%

42%

36%

70%

22%

30

Detectfraud/managerisk

Shiftworkers fromlower-tohigher-leveltasks

28

%35

%27

%18

%36

%

%25

%29

%30%

Improveexisting

products

andservices

Increasespeed/ easeofdevnewsystems/software

Reducecosts

Uncovernewideasand insights

Increaserevenue

Encourageinnovationandgrowth

Improve

efficiencyandproductivity

Enhance

relationshipswithclients/customers

Figure1

Q:Whatareyouranticipatedbenefitsandtowhatextentareyouachievingthosebenefitstodate?(Jan./Feb.2024);N(Total)=1,982;N(veryhigh)=96

9

10

Now:Keyfindings

“Expert”organizationsarescalingGenerativeAImuchmoreaggressively.

GenerativeAIexpertorganizationsarelikelyhaving

moresuccessatcapturingbenefitsbecausetheyarescalingupmuchmoreaggressively,comparedtotheothercategories,whichprovidesalargerbasefor

generatingbenefits.

Accordingtooursurvey,organizationsreporting“very

high”levelsofGenerativeAIexpertisearedeployingAImuchmorerapidlyandextensivelythanothers.Infact,73%saidtheyareadoptingthetechnologyata“fast”

or“veryfast”pace(versusonly40%oforganizations

with“some”levelofexpertise).Theyarealsoscaling

GenerativeAIathigherratesacrossfunctionsandusingitmorewithinfunctions.Forexample,thosewith“very

high”expertisereported,onaverage,implementingatscalein1.4functions,outofeighttotalfunctions,whilethosewith“some”expertisearedoingsoinonly0.3functions.Further,38%ofthosewith“veryhigh”expertisereportedimplementingGenerativeAIatscaleinmarketing,salesandcustomerservice—

versusonly10%oforganizationswith“some”levelofexpertise.

Companiesthatreportexpertisearemovingquickly.

80%

73%

66%

64%

61%

62%

47%

48%

39%

40%

33%

34%

19%

Figure2

(Jan./Feb.2024)N(Total)=1,982;N(Veryhigh)=96;N(Some)=1,021

23%

Adoptingata

Providingmoreoftheir

Adoptingathigherlevels

Investingmorein

Investingmorein

Usingcode

Usingopen-source

fasterpace

workforceaccessto

acrossfunctions

hardware

cloudconsumption

generatorsmore

LLMsmore

AdoptingGenerativeAI

GenAI

ImplementingGenerative

Increasinghardware

Increasingcloud

CurrentlyusingGenerative

Currentlyusing

“fast”or“veryfast”

>40%ofworkforcehas

AIformarketing,sales

investmentbecauseof

investmentbecauseof

AIcodegenerator

opensourcelarge

accesstoGenerativeAItools/applications

andcustomerservice

GenerativeAIstrategy

GenerativeAIstrategy

languagemodels

Veryhighexpertise

Someexpertise

Now:Keyfindings

Insightsfromourexecutiveinterviewsaligncloselywithsurveyfindings,showingthatleadingorganizationsareaggressivelyscalinguptheirGenerativeAIeffortsbothhorizontally(acrossmultiplefunctionsordomains)

andvertically(withinasinglefunctionordomain).Thiscombinationofhorizontalandverticalscalingmayhelpachievevaluecreationmoreeffectively.

Asonechieftransformationofficerinmanufacturingnoted,“[Wehave]anapplicationthatisbeingincrediblysuccessful

andhassavedussignificantamountsofmoney…andthatwehavescaledverybroadlyacrossmanyofoursitesandcontinuetoscalefurtheracrossmoreequipmentacrossmoresites.”

Similarly,fromabroadmarketperspectiveweareseeinganincreasinglysharpdistinctionbetweenhorizontalusecasesthatcutacrossindustries(e.g.,officeproductivitysuitesandenterpriseresourceplanningsystemswith

integratedGenerativeAI)andverticalusecasesthat

areindustry-specificandnarrowlyfocusedbutmorestrategicallyimpactful(e.g.,GenerativeAItoolsforsemiconductordesignthatareusedonlybyasmallsubsetofworkersbuthaveaverylargeimpactonthebusiness).

11

Now:Keyfindings

OrganizationsprimarilyplantoreinvestthesavingsfromGenerativeAIintoinnovationandadditionaloperationsimprovements.

Amongtheoverallrespondentpool,organizationssaidtheyprimarilyplannedtoreinvestcost

andtimesavingsfromGenerativeAIintodriving

innovation(45%)andimprovingoperations(43%),

addressingthevalueequationfrombothsides.It’sinterestingtonotethatasignificantpercentage

oforganizations(27%)alsoplannedtoreinvestinscalingGenerativeAIadoption,creatingacycleofGenerativeAIreinvestmentandgrowth.

Organizationswith“veryhigh”GenerativeAI

expertiseareevenmorefocusedthanothersondrivinginnovation(51%).TheyarealsolessinclinedthanotherstoreinvestsavingsfromGenerativeAIintoimprovingoperationsandmoreinclinedtoprioritizedevelopingnewproductsandservices.

Therightreinvestmentapproachdependsonan

organization’sspecificneeds.Organizationscurrentlyfacingstrategicdisruptionortransformationfrom

GenerativeAIhaveagreaterimperativetofocuson

strategicobjectivessuchasinnovationandgrowth,andarelikelyalreadyworkingmoreaggressivelytodevelopstrongGenerativeAIcapabilities.

Bycontrast,organizationsinindustriesthatare

currentlynotbeingdisruptedbyGenerativeAIaremorelikelytofocusonbenefitssuchasindividual

workerproductivityandoperationsimprovement,areaswithlessofasenseofurgencyandless

toleranceforrisk.SuchorganizationscanstillbenefitgreatlyfromGenerativeAI—justinadifferentway.Theyalsohaveavaluableopportunitytowatch

andlearnfromtheexperiencesofotherindustriesthatarecurrentlybeingdisrupted—lessonsthatcouldservethemwellifandwhenGenerativeAIdisruptionreachestheirownindustry.

“ToenableGenAIvalueinourbusiness,weneedtochangeourmindsetanddevelopR&Dcapabilitiestorealizealong-termvisionenabledbyGenAI,”saidtheCEOofadigitalmediacompany.“Rightnow,[ourmindset]isshort-termandjustabouttangiblecashvalueforone-offusecases.”

Areastoreinvesttimeandcostsavings

Driving innovationopportunities

Developingnewproductsandservices

ScalingGenAIadoptionacrosstheorganization

Trainingand upskillingemployees

EnhancingITinfrastructure

Creatinga returnforshareholders

45%

43%

29%

28%

27%

28%

23%

20%

19%

16%

Improvingoperationsacrosstheorganization

Expandingourmarket

Improving

cybersecurityinfrastructure

Enhancingriskmanagementsystems

Exploringnew

businessmodels

Creatingnewjobs

Figure3

Q:Wheredoesyourcompanyplantoreinvestcostortimesavings

generatedthroughimplementationofGenAIcapabilities(selecttop3)?

(Jan./Feb.2024)N(Total)=1,982

12

13

2

Now:Keyfindings

Scalingup

Akeytovaluecreation,scalingincreasesGenerative

AI’simpactonthebusinessandexpandsitsuser

base—bothofwhichhaveastrongmultipliereffectonGenerativeAI’sbenefits.Yet,manyorganizationsfinditchallengingtomaketheleapfrompilotsandproofsofconcepttolarge-scaledeployment.

Scalingiscomplexandrequireseffortacrossavarietyofinterrelatedelementsspanningstrategy,process,people,dataandtechnology.AlthoughthechallengesassociatedwithscalingGenerativeAIarecommontomanydigital

transformationinitiatives,issuessuchasriskmanagementandgovernance,workforcetransformation,trustanddatamanagementtakeonevengreaterimportance.Whatworkedwellinthepastmightnotworkthesamewaywiththisnewtechnology.

Thescalingphaseiswhenpotentialbenefitsare

convertedintoreal-worldvalue.Itisalso,however,when

potentialissuesbecomereal-worldbarriers.AndwithGenerativeAI,manyofthosebarriersarestillbeingidentifiedandunderstood.

“Therearealwaysissuesthatemergethroughthe

adoptionandscalingtransitionthataren’texpected—

thequestionwehavetoconsiderishowhardaretheytoovercome,”saidachieftechnologyofficerweinterviewed.“Forexample,[oneofour]usecaseshadsometechnical,policyandcybersecurityissues,buttheywererelativelyeasytoovercome,sowescaled.Conversely,for[two

other]usecasesmoreissuesemergedlinkedtotheskillleveltoworkwiththeoutputsoftheAIsolution.These

havebeenhardertoaddress,soscalinghasbeenslower.”

Apublicsectorchiefinformationofficeroutlinedanotherapproach:“[Forus,successfulscalingis]buildingon

previoussuccessesandthentakingthoseinitiativestoanotherlevel.Expandingtootherareasofthe

organization,incorporatingmoredatasets,expandingtheuserbase(internalandexternal)toimproveuponexistingresults,andrefiningthecurrentsolutionformorevalue.

Thisphasedapproachgivesusasenseofassurancetheinvestmentisworthwhilebeforewecommitsignificantlymoreresources.”

Off-the-shelfGenerativeAIsolutionsforcommonuse

casessuchasofficeproductivityarearguablytheeasiesttodeployatscale,buttheystillrequiresubstantial

investment,effortandtraining.Foruniqueand/ormorestrategicGenerativeAIsolutionsandusecases,the

complexityandchallengesincreasebyleapsandbounds,alongwiththepotentialforgreaterreturns.

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Now:Keyfindings

WorkforceaccesstoapprovedGenAItoolsandapplicationsremainslow.

Nearlyhalfofourrespondents(46%)reportedtheyprovidedapprovedGenerativeAIaccesstojustasmallportionoftheirworkforces(20%orless).Organizationsreporting“veryhigh”levelsofGenerativeAIexpertisearefurtheralong,withnearlyhalf(48%)

providingapprovedGenerativeAIaccesstoatleast40%oftheirworkforces.Evenforthese“expert”organizations,workeraccesstoapprovedtoolsremainstheexception,nottherule.

Ourexecutiveinterviewspointedtoanumberofreasonsforthisoveralllowpenetration

rate,mostlyrevolvingaroundriskversusreward—especiallydata-relatedrisks.Dothe

potentialrewardsofGenerativeAIjustifytherisks,andcantherisksbemitigated?In

particular,wefoundwidespreadconcernthatallowingworkerstousepubliclargelanguagemodels(LLMs)andGenerativeAItoolsmightleadtoproblemswithprotectionofintellectualpropertyandcustomerprivacy.

PercentageofworkforcewithaccesstoGenerativeAI

49%

46%

36%

29%28%27%

31%

16%16%14%

25%

23%24%

16%

w5%w3%1%3%4%

8%

6%7%

6%

2%

Upto20%20%–40%40%–60%60%–80%Morethan80%

Percentageoftheworkforce

Q:Howmuchofyouroverallworkforce,doyouestimate,haveaccesstoyourorganization’ssanctioned(approved)GenerativeAItools/applications?(Jan./Feb.2024)N(Total)=1,982,N(Veryhigh)=96,N(High)=606,N(Some)=1,021,N(Little)=257

76%

Overall

Littleexpertise

SomeexpertiseHighexpertise

Veryhighexpertise

Figure4

Now:Keyfindings

Otherconcernsthatcameupinourexecutiveinterviewsinclude:

?GenerativeAIoutputsthatcanbeunpredictableandsubjecttoinaccuracies(i.e.,“hallucinations”)—whichunderminetrust,particularlywhencombinedwithlackoftransparencyandexplainability

?PotentiallossofcontroloverwhatGenerativeAIappsarebeingusedwithintheorganizationandwhoisusingthem

?WorkerresistancetousingGenerativeAIduetolackoffamiliarityorconcernsaboutbeingreplaced

Giventhepotentialchallengesandrisks,acautious

approachtoallowingworkerstouseGenerativeAItoolsarguablymakessense.However,tightrestrictionson

GenerativeAIarebestviewedasatemporarystopgapmeasure—notaviablelong-termsolution.Logically,

anyworkerwithinternetaccesswillhaveaccesstopublicGenerativeAItoolsandcouldbeusingthemwithouttheiremployer’sconsent—potentiallyleaking

sensitivedataandintellectualpropertyintopublicLLMsinanentirelyuncontrolledway.Thisstatusislikelyto

continueintheabsenceofpracticalpoliciesforallowingandmanagingwidespreadGenerativeAIaccess.

Organizationsshouldbeactivelydevelopingsustainableprocessesandpoliciesforenablingubiquitousbut

responsibleGenerativeAIuseandmanagingthe

associatedrisksatscale.Widespreadbutcontrolled

accesstoGenerativeAIwillhelppeoplegetmore

comfortablewiththetechnologyandenablethemtounderstandwhatitcanandcannotdo—givingthemamorerealisticandinformedperspectivewhileopeningthedoortonewopportunitiesforGenerativeAIvaluecreationacrosstheenterprise.

15

“Ithasbeensurprisingtoseehowlowthebaristodosomething

quickanddirty—thisisboth

excitingandscary,butthebig

challengeistoscale—thisisa

wholenewballgame…butscalingishardwithoutcentralization.”

-DirectorofdatascienceandAIinthetechnologyindustry

16

3

Now:Keyfindings

Buildingtrust

Lackoftrustcontinuestobeoneofthebiggestbarrierstolarge-scaleadoptionanddeploymentofGenerativeAI.Inthiscontext,twokeyaspectsoftrustare:(1)trustinthequalityandreliabilityofGenerativeAI’soutput(supportedbyimprovedtransparencyandexplainability),and(2)trustfromworkersthatGenerativeAIwillmaketheirjobseasierandwon’treplacethem.

Regardingworkertrust,oneexecutiveweinterviewed

notedthat“oncepeoplestartseeingefficienciesand

thebenefitsthetoolshavetotheirwork,thatwilldriveadoptionandsustainedsuccess.”Inotherwords,greaterexposuretoGenerativeAItoolswillhelppeoplebecomemorecomfortablewiththetechnologyandunderstandhowitcanhelpthemdo