利用生成式人工智能增加就業(yè)和提高勞動(dòng)力生產(chǎn)率：場(chǎng)景、案例研究和行動(dòng)框架

IncollaborationwithPwC

LeveragingGenerativeAIforJobAugmentationandWorkforceProductivity:

Scenarios,CaseStudies

andaFrameworkforAction

INSIGHTREPORTNOVEMBER2024

2

Images:U

Contents

Foreword3

Executivesummary4

Introduction6

1GenAI’spotentialforpromotingjobaugmentationand7

workforceproductivity

2TheunwrittenfutureofGenAIintheworkforce11

3Insigthsfromearlyadopters16

4Frameworkforaction21

Conclusion27

Appendix:Scenariomethodology28

Acknowledgements29

Contributors30

Endnotes31

References32

Disclaimer

Thisdocumentispublishedbythe

WorldEconomicForumasacontributiontoaproject,insightareaorinteraction.

Thefindings,interpretationsand

conclusionsexpressedhereinarearesultofacollaborativeprocessfacilitatedand

endorsedbytheWorldEconomicForumbutwhoseresultsdonotnecessarily

representtheviewsoftheWorldEconomicForum,northeentiretyofitsMembers,

Partnersorotherstakeholders.

?2024WorldEconomicForum.Allrightsreserved.Nopartofthispublicationmaybereproducedortransmittedinanyformorbyanymeans,includingphotocopyingandrecording,orbyanyinformation

storageandretrievalsystem.

3

November2024

LeveragingGenerativeAIfor

JobAugmentationandWorkforceProductivity:

Scenarios,CaseStudiesandaFrameworkforAction

Foreword

PeterBrown

Partner,PwCUK;GlobalWorkforceLeader,PwC

TillLeopold

Head,Work,WagesandJobCreation,WorldEconomic

Forum

Generativeartificialintelligence(GenAI)is

transformingtheworldofwork.Accordingtothe

WorldEconomicForum’slatestFutureofJobs

survey,withinthenextfiveyears,employersexpectGenAIadvancementstoreshapeasubstantial

numberofjobs,potentiallyaffectingupto40%oftotalglobalworkinghours.

Asthecapabilitiesofthistransformativetechnologycontinuetoevolve,organizationsarewondering

howtheycanuseGenAItodrivejobaugmentationandworkforceproductivity,andtheactionsthey

cantaketoharnessitsfullpotential.

Tofindout,theWorldEconomicForumandPwCembarkedonanewpieceofresearchfocusingonhowearlyadoptersofGenAIareleveragingitacrosstheworkforce,theimpactitishavingandthelessonstheyhavelearnedalongtheway.

Basedoninterviewswithmorethan20

organizationsacrossawiderangeofindustriesand

geographies,wefoundthatsuccessfuldeploymentofGenAIdependsasmuch,ormore,onpeople

thanthetechnologyitself.Workersneedto

understand,trust,andadoptGenAI.Thisrequires

notonlytrainingandsupportbutalsoaculturalshiftwithintheorganizationtoembracenewwaysof

working.

Thisreportcoversinsightsfromtheearlyadopters

weinterviewed,aswellasfourdifferentscenariosforhowthedeploymentofGenAIinorganizationscouldplayout.Italsooffersanactionable

frameworkwhichorganizationscanusetoshapetheirGenAIworkforceapproach.

Wewouldliketothankalltheorganizationsandexpertswhogenerouslysharedtheirtimeand

experiencewithus.WehopethisreportwillbeausefulresourcefororganizationsacrosstheworldastheynavigatetheopportunitiesandchallengesthatGenAIbringsforjobaugmentationand

workforceproductivity.

4

Executivesummary

Generativeartificialintelligence(GenAI)has

thepotentialtodrivesignificantimprovementsinworkforceproductivityattheleveloftasks,organizationsandeconomies.Deliveringthosegainsdepends,amongotherthings,onthe

deploymentofGenAItoaugmentjobs,i.e.

topartiallyperformtasksinsuchawaythat

technologyeffectivelysupportsorenhanceshumancapabilitiesthroughhuman-machinecollaboration.Drawingonareviewofexistingresearch,scenarioanalysisandcasestudiesofearlyadopters,this

reportproposesaframeworkforactionthatfostersjobaugmentation.

Globalcontext

WhatsetsGenAIapartfrompreviousdevelopmentsinartificialintelligenceisitsabilitytowidenaccess

totheuseofAIandeliminatethebarrierof

specializedknowledge.GenAIhasthepotentialtocontributetoeconomicandproductivitygrowth

bycreatingefficienciesthroughfreeingupworkingtimespentonlower-valuetaskstoengageinhighervalue-addedactivities.Moreover,GenAIhasthe

potentialtoaugmenthumanworkersbyenhancingtheirskillsandcapabilities,therebyincreasingtheirproductivityandenablingnewanddiverseformsofvaluecreation.

However,GenAI’spotentialtoenhanceproductivity

mayvaryacrosscountries,industries,and

organizations.ToeffectivelydeployGenAIintheworkforce,organizationsmustalsoaddressa

rangeoffactorsincludingtrust,skills,cultureandthedemonstrationofbusinessvaluefromGenAIinvestments.

Scenarioanalysis

Withsuchafast-movingtechnology,itishardto

predicthoweventherelativelynear-termfuturewillplayout.Tohelpthinkthroughthepossibilities,it

isusefultothinkintermsofscenariosbasedon

twokeyuncertaintiesthatwillshapethenearfutureofGenAI-enabledjobaugmentation,productivity

andinnovation.Thefirstcoreuncertaintyrelates

totheleveloftrustinGenAI,whichreferstotheconfidencethatemployeesandorganizationshaveinGenAI-driventoolsandtheiroutputsaswell

asemployeetrustintheiremployers,technology

providers,andgovernments.Thesecondcore

uncertaintyrelatestowhethertheapplicabilityandqualityofGenAIwillcontinuetoimproveinthe

short-termorremainthesame.

Anycombinationofthesetwodimensionsis

possible,leadingtoverydifferentoutcomes.Aworldwheretrustislow—eitherbecauseGenAIdoesnotprogresssignificantlyfromtoday;or,

conversely,becauseofconcernoveritsfast

progressandpotentialforjobdisruption—is

onewhichmissesoutontheopportunitiesof

productivitygainsandjobaugmentation.Aworld

ofhightrustbutlimitedimprovementsinGenAI

containssignificantrisks;whileonewhereboth

trustandqualityandapplicabilityimproveintandemislikelytoseethebiggestgainsinworkforce

productivityandjobaugmentation.

Insightsfromearlyadopters

Thefournearfuturescenariosoutlinedprovide

ausefulbackgroundtoinsightsderivedfrom

interviewswithmorethan20earlyadopters

fromawiderangeofindustriesandregionsacrosstheworld.TheseorganizationsarepursuingGenAIpartlyoutofconfidenceinproductivitygains.TheyalsobelievethatGenAIwillimprovethequality

ofwork,andtheexperienceoftheiremployees.Adifferentmotivationisadesiretopre-emptthepotentialdisruptionoftheirbusiness.

TheorganizationsquickesttoadoptGenAIintheirworkforcearethosethatcouldbedescribedas

‘data-driven’.TheyemphasizetheneedtodevelopandtestGenAIsolutionsinsmallgroupsbefore

rollingthemouttotherestoftheorganization,

allowingforissuestobeidentifiedandaddressedbeforewiderimplementation.Theyalsoput

significantemphasisonriskmanagement,includingdesigningprocessesthathave‘humansinthe

loop’,forminginternalcommitteesorcouncilsthatestablishinternalrules,standards,andframeworksandassessusecasesandconsidersustainabilityimplicationsofusingGenAIatscale.

Toidentifythepotentialforworkforceproductivitygainsandjobaugmentation,earlyadopters

combinebothbottom-upandtop-down

approaches,withstrongsupportfromleadershipandrelianceontheinnovativecapabilitiesoftheirworkforce.Itisinday-to-daypracticewheremostusecasesareidentifiedanddeveloped.Accordingtothisperspective,themostpromisinguse

casesarethoseembracedandchampionedbyemployeesthemselves.

Frameworkforaction

Combininginsightsfromthescenariosand

lessonslearnedfromearlyadopters,thereportproposesanactionableframeworkforpromotingjobaugmentationandworkforceproductivity

growthwithGenAI.Focusingonfactorswithinanorganization’scontrol,itisdesignedtobeusefulbothtoorganizationsjuststartingoutontheir

GenAIworkforcedeploymentjourneyaswellasthoseseekingtoscaleexistingefforts.

5

EngageelementsfocusonfacilitatingthatGenAIworkforceapplicationsareeffectivelyadoptedandintegratedintoworkflowstogeneratethedesiredbenefits.Theseelementsinclude:Cultureand

changemanagement;Skillsdevelopmentandredeployment;andUsecasemanagement.

Theframeworkhighlightsanumberofkeyelementsaroundtwocorethemes:EnableandEngage.TheEnableelementsfocusonestablishingfoundationsandguidingprinciplesandinclude:GenAIvision

andstrategy;Dataandtechnologyinfrastructure;andRegulatorycomplianceandgovernance.The

6

Introduction

Thisreportaimstounearththeexperienceofearlyadoptersofgenerativeartificialintelligence(GenAI)deploymentintheworkforcetoderivelessons

learnedandprovideanactionableframework

forpromotingjobaugmentationandenhancing

workforceproductivity.Itexaminesthekey

elementsthatorganizationsmusthaveinplace

tofacilitatetheseoutcomes.Researchinterviewsconductedforthisreportareglobalinscope,

encompassingawiderangeofgeographies,

industriesandorganizationsincludingcommercial,public-sectorandsocialentities.

TheemergenceofGenAIintheworkplacehas

createdsignificantinterest,fromtheboardroom

tothebreakroom.Section1examinesthese

expectations,hopesandconcerns,andoutlines

currentbarriersforindividualsandorganizationstoeffectivelyleveragethetechnologytoachievebetterpeopleandbusinessoutcomes.

Atpresent,thefutureofGenAIintheworkforce

remainsuncertainandundefined.Despiterapid

developments,thetechnologyisstillinitsinfancy,makingitimpossibletoextrapolatetheextentto

whichproductivitygainsandjobaugmentation

maybeachievedinthenearfuture.Acknowledgingtheunpredictablenatureofthefuture,Section

2considersfourscenariostoenablevarious

stakeholderstothinkthroughthemultiplewaysinwhichGenAIintheworkforcecouldevolve.

Section3presentsfindingsfrominterviewswith

morethan20earlyadoptingorganizationsthat

havegenerouslysharedtheirexperiences,lessonslearnedandexpectationsregardingtheemergingimpactofGenAIonproductivitygainsandjob

augmentationtoprovidevaluableinsightsintothepracticalimplicationsandpotentialreturnsofGenAIworkforcedeployment.

Section4buildsontheprevioussectionstoofferanactionableframeworkthatorganizationsmay

adaptfortheirownusetoaugmentjobsand

enhanceproductivitythroughGenAIadoption.

Theframeworkaimstoenableorganizationsto

harnessthepotentialofGenAIwhileadheringto

ethicalstandards,emerginglegalrequirements,

andconsideringthedevelopmentandwell-beingofemployeesusingthetechnology.

Thefindingssuggestthat,withtherightenabling

conditions,GenAIhasthepotentialtoaugment

jobsandenhanceproductivity.However,this

requiresorganizationstogothroughaphaseof

understandingthetechnology’svaluefortheir

specificneeds,identifyingappropriateusecases,andthoroughlytestingthesolutions.Moreover,

safeguardingthatworkersunderstand,trustand

adoptGenAIisessentialbeforeusecasescanbescaled;thus,inadditiontotrainingandsupport,aculturalshiftwithintheorganizationisalsocritical

toembracenewwaysofworking.Basedon

theinsightsfromtheinterviews,thesuccessful

deploymentofGenAIdependsasmuchormoreonpeoplethanonthetechnologyitself.

Thisreporthasbeendevelopedaspartof

The

JobsInitiative

,coordinatedbytheWorldEconomicForum,whichaimstobuildthejobsoftomorrow

andensuregoodjobsforallinthecontextof

ongoinglabourmarketdisruptions.Onekey

focusareafortheinitiativeispromotingstrategies

forleveragingGenAIforjobaugmentationand

workforceproductivitygrowth.Itisoneofa

seriesof

currentWorldEconomicForumreports

thatexplorethetransformativeroleofartificialintelligenceacrossindustriesandavarietyofkeythemes.

7

1GenAI’spotentialforpromotingjobaugmentationand

workforceproductivity

Thissectionprovidesanoverviewofthedebate

aboutgenerativeartificialintelligence(GenAI)in

theworkforceanditspotentialforpromotingjob

augmentationandproductivitygrowth.Italso

highlightscurrentexpectationsandassessments

surroundingGenAIaswellasbarrierstoitsmore

widespreadworkforceadoption,twoyearsafterthepubliclaunchofoneofthemostprominentlarge

languagemodels(LLMs).

Byleveragingnaturallanguageprocessing

technology,GenAIenablesuserstointeractwithitasthoughtheywereconversingwithahuman,reducingbarrierstousageandtheneedfor

specializedtechnicalknowledge.SincethepubliclaunchofChatGPT3.5inNovember2022,and

severalotherprominentLLMsshortlythereafter,publicinterestinGenAIhassurged,raising

expectationsaboutitspotentialtotransformthegloballabourmarket.AccordingtotheWorld

EconomicForum’slatestFutureofJobssurvey,withinthenextfiveyears,employersexpecta

substantialnumberofjobstobereshapedduetoGenAIadvancements1,potentiallyaffectingupto40%oftotalglobalworkinghours.2

ThisfirstsectionofthereportwillreviewthecurrentstateofthedebateonGenAI’spotential,witha

particularfocusonjobaugmentation,workforce

productivitygrowthandbarrierstothetechnology’smorewidespreadworkforceadoption.

1.1

GenAIandjobaugmentation

LikeotherrecentadvancesinautomationandAI

technologies,theriseofGenAIhasledtoconcernsaboutpossiblejobdisplacement.Thisapprehensionispartlyrootedinthetechnicalpotentialofthe

technologyitselfandpartlyinskepticismabout

employers’andgovernments’abilitytosupport

individualsthroughAI-inducedjobdisruptions.3Onerecentsurveyindicatedthat47%ofemployeeswhohadusedGenAIexpressedconcernsthatitmay

affectthenatureoftheirworkinanegativeway.4

ResearchexaminingthepotentialimpactofGenAIonjobscommonlyoperatesonthepremisethat

jobrolesandoccupationsarecomposedof

varioustasks,someofwhichmaybesusceptibletovaryingdegreesofautomationbyGenAI.For

instance,tasksthatarerepetitiveorroutineare

moreexposedtoautomationthanthoserequiringsignificanthumaninteraction.WhileawiderangeoftasksmaybefullyautomatedbyGenAI,researchtodatehasfoundveryfewexamplesofjobsthat

couldbedisplacedinthiswayintheirentirety.5

Morefrequently,GenAImaypartiallyautomate

sometasksofajobrolebutsimultaneouslyimprovehumanworkers’abilitytoperformothertasks.In

linewithrecentresearch,thispaperreferstothisprocessasjobaugmentation(seeBox1andFig.1).6

AsGenAItechnologiesandlabourmarkets

continuetoevolve,itislikelythatsomejobrolesmaybecomemorefullyautomatedwhileothers

maybefurtheraugmentedinthefuture.Insimilarwaystoearlierindustrialtransformations,both

jobautomationandjobaugmentationmaybe

expectedtoleadtoadditionaljobcreation–bothdirectly,creatingwhollynewjobsinvariousfields,7andindirectlythroughmacroeconomicspillover

effectsfromincreasedproductivityandadditionaleconomicvaluecreation.Thefocusofthisreportisontheimmediatetermandinputtingintoplaceenablingconditionsforjobaugmentationnowandinthenextyears.

8

BOX1

FIGURE01

Automationandaugmentation

Thisreportdistinguishesbetweenthefollowingdefinitions:

JobautomationreferstotheuseofGenAItofullyperformtasksthatwerepreviouslyperformedbyhumansinagivenoccupation.1

JobaugmentationreferstotheuseofGenAItopartiallyperformtasksinsuchawaythattechnologyeffectivelysupportsorenhanceshumancapabilitiesthroughhuman-machine

collaboration.Jobaugmentationmaygobeyondtechnicalproductivityincreasetoalsoenhancejobqualityandworkerwell-being.2

1.Raisch,S.andS.Krakowski,“Artificial

IntelligenceandManagement:TheAutomation–AugmentationParadox”,Academyof

ManagementReview,vol.46,no.1,2021.

2.WorldEconomicForum,Augmented

Workforce:EmpoweringPeople,TransformingManufacturing,2022.

GenAI:Exampleofamoreexposedandlessexposedjob

SoftwareDevelopers(moreexposed)

HumanResourceManagers(lessexposed)

22.2%

28.7%

16.1%

43.2%

28%

Higherpotentialforautomation:

—Analysedatatoimproveoperations

—Analyseperformanceofsystemsorequipment

Higherpotentialforaugmentation:

61.7%

Higherpotentialforautomation:

—Determineresourceneedsofprojectsoroperations—Managebudgetsor?nances

Higherpotentialforaugmentation:

—Explainregulations,policiesorprocedures

—Trainothersoroperationalorworkprocedures

—Prepareinformationalorinstructionalmaterials

Lowerpotentialforautomationoraugmentation:

—Interviewpeopletoobtaininformation

—Coordinategroup,communityorpublicactivities

—Evaluatethecharacteristics,usefulnessorperformanceofproductsortechnologies

Lowerpotentialforautomationoraugmentation:

—Coordinatewithotherstoresolveproblems

—Communicatewithothersaboutbusinessstrategies

AugmentationLowerpotentialNon-languagetasks

Automation

Source

WorldEconomicForum,JobsofTomorrow:LargeLanguageModelsandJobs,2023.

1.2

GenAIandworkforceproductivitygrowth

GenAI’spotentialimpactonproductivityisoneofitsmostanticipatedbenefits,particularlybecauseoftheslowdowninproductivitygrowthinmany

economies.8Althoughcurrentforecastsvary

widely,ithasbeensuggestedthatGenAI’simpactonproductivitycouldaddtrillionstotheglobal

economyoverthenextdecade.9

WhatsetsGenAIapartfrompreviousdevelopmentsinAIisitsabilitytowidenaccesstotheuse

ofAIandeliminatethebarrierofspecialized

knowledge.GenAIhasthepotentialtocontributetoeconomicandproductivitygrowthbycreatingefficienciesthroughfreeingupworkingtime

spentonlower-valuetaskstoengageinhigher

value-addedactivities.Forinstance,automatinghelpdeskqueriesmayallowcustomerservice

workerstofocusonmorecomplexissuesthat

increasecustomersatisfaction.Onerecentstudy,surveyingmorethan100,000workersfrom11

GenAI-exposedoccupations,foundthatworkersestimatedChatGPTcouldreduceworkingtimes

9

by50%forone-thirdoftheirjobtasks.10As

respondentsinterviewedaspartoftheresearch

forthisreporthighlighted,torealizethesepotentialproductivitygainsitisimportanttocapturetime

savedasvalueatanorganizationallevel.

Moreover,GenAIhasthepotentialtoaugment

humanworkersbyenhancingtheirskillsand

capabilities,therebyincreasingtheirproductivityandenablingnewanddiverseformsofvalue

creation.11Forinstance,GenAImayaugment

humancapabilitiesincreativetasks,thoughit

doesnotcurrentlysurpasshumancreativityonitsown.12ResearchalsosuggeststhatGenAImay

helpnarrowproductivitygapsbetweenlower-andhigher-skilledworkers.13

GenAI’spotentialtoenhanceproductivitymayvaryacrosscountries,industriesandorganizations.Atacountrylevel,moredevelopedeconomiesmay

facehigherdisruptionriskduetoprevalenceof

knowledgework,buttheyarealsobetterequippedtoadoptGenAImorequicklyandatscale.14Manyofthesecountriesalsofaceadecreaseinlabour

supply,whichmayboostthedemandfornew

technologiessuchasGenAItoseekefficiency

improvements.15Emergingeconomiesmaysimilarlybenefitfromproductivitygrowthbyaddressing

infrastructureconstraintsandshortagesinbasicdigitalskills.EarlyresearchindicatesthatGenAI

maydisproportionallyboostproductivityforworkerswithlessexperienceorskill,therebyreducingentrybarrierstothedigitaleconomy.16

Atanindustrylevel,exposuretoGenAI-driven

taskautomationandaugmentationvarieswidely

acrosssectors,withnotallindustriesbeingequallyimpactedorstandingtobenefitfromGenAI.As

describedabove,previousresearchhasidentified

whichtasksaremostexposedtoLLMs,highlightingtheirhigherorlowerpotentialforautomationor

augmentation.Forexample,onerecentstudy

foundthatsoftwaredevelopersfromthreelarge

technologyfirmsincreasedthenumberoftasks

completedbyover26%usingGenAI.17Whentheseexposurelevelsareaggregatedattheindustrylevel,itbecomesevidentthattheimpactofGenAImay

varysignificantlyacrossindustries.Forinstance,

thetechnologyandfinancialsectorscouldface

substantialtaskautomation,whilethehealthcareandeducationsectorsmaybenefitmorefromtaskaugmentation.18

Importantly,asdiscussedinSection3ofthis

report,productivitygrowthisnottheonlydriverfororganizationstodeployGenAI.Manyalso

expectimprovedqualityofworkandbetterworkexperiencesfortheiremployees,increasing

employeeengagementandtalentretention.

1.3

CurrentbarrierstoscalingGenAIadoptionintheworkforce

Historically,slowandinconsistentadoptionof

AItechnologieshasrestrictedtheirimpactand

effectiveness.19Asofmid-2024,only12%of

workersreportthattheyuseGenAIatworkon

adailybasis.20CurrentbarrierstoGenAIuptake

encompassconcernsrelatedtotrust,skills

acquisition,changeincultureandunclearbusinessvalue.

Trust

Trustisacrucialfactorthatmustbeconsidered

whenembracingnewtechnologies.GenAImodelsaresometimesreferredtoas“blackbox”systemsduetothecomplexityoftheiralgorithms,raisingconcernsabouttheoutcomestheygenerate

andtransparency.21Inlinewiththis,CEOssee

cybersecurity,spreadofmisinformation,legalorreputationaldamage,andincreasedlevelsofbiasasprimaryconcernsrelatedtotheadoptionof

GenAI.22Inadditiontobiasanddiscrimination,workersarespecificallyworriedaboutthelackofoversight,transparency,explainabilityandaccountability.23

TobuildtrustandfacilitatetheethicaluseofGenAI,thereisstrongdemandfortransparencyand

responsibledeployment.Increasingly,organizationsareimplementingresponsibleGenAIprinciples

tobuildtrustindecision-makingprocessesby

improvingexplainabilityandmitigatingrisks.Atbothnationalandsupranationallevels,someterritories

aretighteningregulationsonAItopromotetrust

andethicalusebysettingclearboundariesand

enforcingaccountability.Forexample,theEuropeanAIActincludesthe“human-in-the-loop”principle,

emphasizinghumanaccountabilityindecision

making.ThisprinciplemayhelptoincreasetrustinGenAIbyestablishingaccountabilityandrespectinghumanvalues.24

Atanindustrylevel,concernshavebeenraised

aboutacomparativelysmallnumberofindustry

playersholdingsignificantinfluenceoverthe

developmentofGenAIaswellasitsregulatory

environment.25Governmentregulationispartly

aimedatcreatingalevelplayingfieldwhereall

partiesfollowthesameregulationsandcriteria.

Nevertheless,inconsistentAIlawsworldwide

couldalsohavethereverseeffect,disadvantagingorganizationsthatareoperatinginthemoststrictlyregulatedjurisdictions.

10

Skills

Ataworkforcelevel,twooutoffiveemployers

reportthatalackofadequateAI-relatedskillsis

anobstacletotheintegrationofGenAIatwork.26

IncreaseddemandforGenAIskillsoutsideoftechrolesisevidentwhenexaminingtheshareofjob

postingsinnon-techrolesthatnowrequesttheseskills.27Yet,thereisaprevailingconcernamong

78%ofseniorexecutivesthattheircompanies

mayfailtotraintheiremployeesrapidlyenoughtokeeppacewithtechnologicaladvancementsinthecomingyears.28Thisconcernisreinforcedas37%ofmorethan56,000workersfrom50countries

andregionssurveyedbyPwChavenotused

GenAIapplicationsforworkinthepastyear,andanadditional25%haveonlydonesoonceortwice.

Eveninthehighlyexposedfinancialsectoralmostone-quarterofworkersreportednottohaveusedGenAIforwork.Inthetelecommunicationsector,whichshowedthehighestoveralluseofGenAI,19%ofworkershaveneverusedGenAIintheir

work.29

Culture

ThecultureofanorganizationisacrucialfactorintheadoptionofnewtechnologiessuchasGenAI.

Organizationsinterviewedforthisreportstresstheimportanceofchangemanagement:successful

introductionofGenAIdependsonexperimentsandfindingusecases.Thisrequiresastimulatingand

supportiveculture.Forexample,itisimportantto

cultivatemindsetssuchasafuture-positiveattitude,growthmindsetandagility,whicharecrucialfor

employeestoembraceGenAIintheworkplace.

Young(technology)companiesanddata-driven

organizationstendtoadoptnewtechnologyeasierandfasterbecausetheyarelesshamperedby

existing,establishedwaysofworkingandembodyadatacultureanddigitalliteracy.

Businessvalue

Certainenterprisesarereadilycommitting

substantialresourcestoGenAItechnologies,

withinvestmentsinGenAIprojectedtogrowby

60%overthenextthreeyears,reaching7.6%

ofITbudgetsby2027.30Othersexhibitgreater

reluctance,questioningtheassurednessofthe

returnstheseinvestmentsmaybring.CompaniesoftencitecostsasasignificantbarriertoGenAI

adoption,withanumberofthemunsureofthe

technology’spotentialbenefits.31Theuncertaintyisamplifiedbythelimitedevidenceavailableonthe

impactofGenAIonfi