德勤 -人工智能、人口结构变化与应变能力：为下一轮劳动力变革做好准备 AI,demographic shifts,and agility Preparing for the next workforce evolution

Deloitte.Insights

Al,demographicshifts,andagility:Preparingforthenextworkforceevolution

ADeloittesurveyrevealshowAlandhumancollaborationcanhelpclosetalentgaps,speedupskilling,andtransferknowledgeasdemographicchangesreshapethe

workforce

ByKyleForrest,BradKreit,RoxanaCorduneanu,AbhaKulkarni,SueCantrell

Al,DEMOGRAPHICSHIFTS,ANDAGILITY:PREPARINGFORTHENEXTWORKFORCEEVOLUTION·PG1

Article•16-minread•25August2025•DeloitteCenterforIntegratedResearch

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Theworkforceappearstobeundergoingasignificant

transformation.Fewerpeopleareenteringthejobmarket;1one

recentstudyfoundthatthenumberofhighschoolgraduatesintheUnitedStateswasexpectedtopeakin2025andthendecline

throughoutthenextdecade,primarilyduetoalong-termdropinbirthrates.2Meanwhile,asignificantnumberofexperienced

workersarereachingretirementage,withestimatessuggestingthatby2030,1in6peoplegloballywillbeovertheageof60.3

Thesedemographicshiftsareshrinkingthepoolofavailabletalentinmatureeconomies,leadingtopotentiallaborshortagesanda

wideningskillsandexperiencegapthatcouldmakeitdifficultfororganizations,especiallyinconstruction,hospitality,andother

industries,tofindandretainthetalenttheyneedtodrivegrowth.4

Atthesametime,advancesinartificialintelligencearereshaping

howsomeworkgetsdone.Routinetasksarebeingautomated,andthetraditionalstructureofworkisevolvinginrealtime.Deloitte’sTMTpredictionsteamanticipatesthatby2027,50%offirmsthatcurrentlyusegenerativeAIwillatleastbepilotingagenticAI,whichcouldcreateopportunitiestoincreasetheproductivityofindividualworkersbutalsoraisequestionsabouthowtooptimizehumanandmachineteams.5

Howcanorganizationsprepareforandrespondtothepressuresofashrinkinglaborsupplyandrapidtechnologicalchange?Manyare

alreadyexploringwaystoaugmenthumanandmachine

collaborationintheworkplaceasapotentialsolution.Buttohelp

unlockthisvalue,organizationsshouldunderstandhowtechnologyweavesintothefabricofworkandwheretheopportunitiesandriskslie.

Forexample,organizationscanuseAItobridgeknowledgeand

experiencegaps,upskillworkers,andenablenew,value-added

capabilities—butwhichactivitiesshouldnotbeautomated?Whichshouldremainclearlymanagedanddrivenbyhumans,andhow

shouldorganizationsmakethesedecisions?

TobetterunderstandhoworganizationscoulduseAItoaugmentthechangingshapeoftheworkforce,Deloittesurveyedmorethan

11,000workersacross17countries,exploringhowtheyuseAIandemergingtechnologiestheirpreferredcollaborationstrategies,andhowtheybuildskills(seemethodology).

OursurveyhighlightsfourkeyopportunitiesfororganizationstointegrateAIandhumancapitaltoaddressworkforcechallenges:

enablinghuman–machineteaming,experimentingwithagentic

technologywhilekeepinghumansontheloopinworkflows,usingAItostrengthenskilldevelopment,andimprovingknowledgeand

wisdomtransferthroughAItools.Fororganizations,identifying

whichtasksmaybenefitmostfromautomation—andwhichtasks

benefitfromhumaninvolvement—couldbeanimportantfactorindesigningworkinthecomingyears.Byidentifyingwhereworkers

currentlyfindvalueinAIandwherecollaborationwithcolleaguesismostbeneficial,organizationscanoptimizetheirtechnology

investmentstohelpdriveshort-termefficiencyandproductivity

gainswhilebuildingtheskillsandtalentpipelineneededforthelongterm6.

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Demographicchangesgetreal

ThedemographicrecompositionoftheworkforcemayhavebegunwiththeonsetoftheCOVID-19pandemicin2020,

whenworkforceparticipationratesdroppedsignificantlyandhaveyettofullyrecover.Oneanalysisestimatedthat,asof2024,fivemillionfewerpeoplewereworkingthanprojectedpriortothepandemic.7Thisshiftisdrivenbyincreased

retirementsandfewerentrantsintothelabormarket.AFederalReserveBankofAtlantaanalysisfoundthatnearlytwomillionAmericansreachedretirementagein2022,comparedtojust40,000Americansentering“primeworkingage,”

commonlydefinedasages25to54,thatyear.8AImaybecontributingtothelimitedentryofentry-levelworkersintothelabormarket,with67%ofrespondentsina2024DeloittesurveybelievingthatAIcouldreducetheavailabilityofentry-levelroles,makingitdifficultforthemtojointheworkforce.9

IntheUnitedStates,workforceparticipationisalreadyindeclineandisprojectedtodropfurtherfrom63%in2023to61%in2033asthepopulationcontinuestoageandretire.10Notonlycouldthesedemographicchangescontributetoworkerandskillshortages,buttheymayalsoputorganizationsatriskoflosinginstitutionalknowledgeandexperienceasmoretenuredworkersleavetheworkforce.

Whilethenumberofnewentrantstotheworkforcecontinuestodeclineinsomeregions,rapidgrowthisanticipatedinotherpartsoftheworld.By2030,oneprojectionestimatesthattwo-thirdsofnewentrantstotheworkforcewillresideinSub-SaharanAfrica,11andby2040,Africaisexpectedtohavethelargestworkforceglobally,surpassingIndiaandChina.12Althoughthesepopulationsmaycontributetoremotework,theyareunlikelytofillgapsinmatureeconomiesforjobs

thatrequireanon-the-groundpresence,likemanufacturing,construction,healthcare,andotherfront-lineroles.

Amismatchbetweenskillsandmarketdemandcouldbeexacerbatingthesedemographic-relatedhiringchallenges.A

Lightcastanalysisfoundthat9ofthe10mostin-demandrolesonlyrequireahighschooleducation.Still,aroundtwo-

thirdsofUShighschoolgraduatesimmediatelyenrollincollege,creatinganoversupplyofcandidatesforsomerolesandalackofcandidatesforothers.13CoupledwithAI’simpactonentry-levelopportunities,thismayhelpexplainwhyentry-levelworkersinfieldslikecomputersciencearestrugglingmoretofindjobsthaninpreviousyears.14Atthesametime,demandforworkersinskilledtradesisintensifying:Amanufacturingexecutiverecentlyestimatedthattheyreceiveonlyonequalifiedapplicantforevery20USjobopenings.15

Thisskillgapappearstobeleadingtosomeunexpectedoutcomes.Forexample,onehighschooljuniortoldTheWallStreetJournalthathefelt“likeI’manathletegettingallthisattentionfromalltheseproteams,”ascompaniesarealready

recruitinghimdespitebeingmorethanayearawayfromgraduation—notforsports,butbecauseheisenrolledina

weldingprogram,afieldfacingagrowingtalentshortage.16Thistrendnotonlyhighlightscurrentshortagesbutmayalsoforeshadowamuchlargershiftinhowearly-careerworkersarerethinkingtheirapproachtowork.

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Unlockingworkforcepotentialthroughbetterhuman–machinecollaboration

Asmoretaskscanpotentiallybedelegatedtoagentictechnology,

organizationswillhavetheopportunitytoredefinehuman

collaboration,teaming,andwork.Todoso,theymayneedtoadoptamoreholisticapproachthatintegrateshumanandmachine

workflowsintoaunifiedeffort,whilealsoimplementingtargeted

strategiestoaddresscriticalskillandexperiencegaps.Inthe

followingsections,weexploreopportunitiesfororganizationsto

embracethisholisticapproachtoaugmentthechangingshapeoftheworkforce.

Opportunity1:MostworkerswantamixofhumanandAIcollaboration

Inrecentyears,AItoolshaveevolvedfromsimplyautomatingtasks

toworkingmorecollaborativelywithhumansindecision-making

andcoachingroles.17Thistrendislikelytocontinue:

Deloitte’sTMT

Predictions2025

expectsthatby2027,halfofcompaniesusing

generativeAIwillhavelaunchedagenticAIapplicationscapableofperformingcomplexworkwithlimitedoversight.18Organizationsthatunderstandthesetechnologicalopportunitiesandapplythemtoaddressskillandexperiencegapsmayuncoverunexpectedbenefits—providedtheystriketherightbalancebetweenhumanandAI

collaboration.

Mostworkersinoursurveyexpressedapreferenceforcombining

technologicaltoolswithhumaninteractionaspartoftheirwork.

Whileworkersages18to44reportastrongerpreferencethanothersforusingonlyAItools,andolderworkersreportastronger

preferenceforhuman-onlycollaboration,thevastmajorityacrossallagegroupspreferanevenmix(figure1).Workersages65andolderseemtobethemostopentoblendingAItoolswithhuman

teamwork,buttheyreportlowerinterestinworkingonlywithAI,suggestingthatthiscohortistakingadvantageofemerging

technologywhilecontinuingtovaluehumaninteraction

Figure1

MostsurveyedworkerspreferanevenmixofhumancollaborationandAltoolsintheirwork

Idealwaytoworkbyagegroup

●Preferco-workercollaboration●Evenmixofco-workerandAlcollaboration○PreferAlcollaboration

67%

62%

57%59%59%57%

27%16%

23%15%

25%17%

21%

25%19%

22%18%

11%

18-2425-3435-4445-5455-6465+

Source:AnalysisfromDeloittesurveyof11,387fulltimeandpart-timeworkersconductedinFebruary2025across17countriesinEMEA,Americas,andAPAC.

Harnessingtheseopportunitiesmayrequireorganizationsto

reimaginehowtheythinkaboutteaming,collaboration,andAI.OneresearcherstudyingAI'simpactonhumancollaborationnotesthat,asthistechnologymatures,“AIsometimesfunctionsmorelikea

teammatethanatool."Thisshiftmaycallfororganizationsto

"reconsiderteamstructures,trainingprograms,andeventraditionalboundariesbetweenspecialties.”19

Someorganizationsarealreadystartingtoredefinetheseboundaries,includingattheexecutivelevel.PharmaceuticalcompanyModernarecentlymergeditshumanresourcesandinformationtechnology

executiverolesintoasinglechiefpeopleanddigitaltechnology

officerpositionaspartofitsbroaderdigitaltransformationand

growthstrategy.2⁰Modernaisalsoexploringwaystolinkmultiple

AIagentstoenhanceworkflowsbetweendigitaltoolsandhuman

workers—andevenusingdigitalagentstoproactivelyidentify

potentialsourcesoftensionbetweenseniorleaderssohuman

workerscanpreventconflictbeforeithappens.¹Theseapproaches

highlightthepotentialforintegratinghumancapitalandAIplanninginordertostrengthenorganizationalprocessesandgrowth.

Keytakeaways

Tofacilitatebetterhumanandmachinecollaboration,leaderscanconsider:

·DefiningguidelinesforcollaboratingwithAIandworkers.Analysisshowsthatmostworkers—acrossallagegroups—preferamixofhumanandAIcollaboration.Organizationsshouldconsiderestablishingclearframeworksreflecting

thesepreferencestomaximizeadoptionandvalue.

·RedesigningteamstoincludeAIasateammate.AIis

evolvingfromatooltoateammate.Thisshiftmayinvolverethinkingroles,training,andcross-functionalboundaries.OrganizationsshouldconsiderrestructuringteamdynamicstoenableAI-humanteamingacrossfunctionstoenhance

agilityandinnovation.

·DefiningtaskboundariesbetweenhumansandAI.AsAI

becomesmorecapable,it'simportanttodecidewhichtasksarebestdonebypeopleandwhichbyAI.UsingAIforfaster

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delivery,repetitivetasks,anddata-heavyworkcouldhelp

freeuptimeforhumanstoworkonstrategictasksthatneedjudgment,empathy,orcomplexproblem-solving.Clear

guidelinescanhelpworkerscollaboratewithpeersandAIeffectively.

Opportunity2:Humanoversightstillmatters,butAIwinsonspeed

EvenasworkersandorganizationsarelearningtointegrategenAIintotheirworkflows,advancesinagenticAIhavethepotentialto

increaseperformancebytakingonawidearrayoftaskswithlimitedhumanoversight.

Workerpreferenceswilllikelyevolvealongsidethesetools.22

Experimentingwithandinvestinginagentictechnologyoffersanopportunitytounderstandhowitmightcoevolvewithworker

expectations.Inthenearterm,Deloitte’sTMTPredictionssuggests

thatorganizationscanmaximizethevalueofagenticAIbykeepinghumans“ontheloop”inworkflowsinvolvingdigitalagents.23Thisapproachdiffersfromkeepinghumans“intheloop,”asitallows

themtooverseeandmanagedigitalagentssimilarlytohowtheymightmanageajunioremployee.

Organizationscanalsoassesstasksacrossaspectrumofautomation

toidentifywhichcanbedelegatedtotechnologyandwhichtasks

requirehumanoversight.24Thisperspectivecouldhelporganizationsprioritizetechnologyinvestmentsfortaskswell-suitedtoagenticAIwhiledirectinghumancapitalinvestmentstoareaswherehuman

oversightismostcritical.

Oursurveyhighlightsthetasksrespondentsseeasmostinneedofhumanoversight.WhileworkersacrossallagegroupsexpressedageneralpreferenceforcollaboratingwithbothAIandhuman

colleagues,notabledifferencesemergedbetweenagecohorts

regardingwhodeliversbetterqualityandspeed—humansorAI(figure2).

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Figure2

MostdemographicgroupssayhumansstilldeliverbetterworkqualitythanAl,butAlwinswhenitcomestospeed

●Co-workers●Al●Nopreference

Total

18-24

25-34

35-44

45-54

55-64

65+

Qualityofdeliverables

Problemsolving

Creativityandbrainstorming

Coreworktasks

Seekingfeedbackoradvice

Trainingorlearning

Summary(higherqualityofworkwhenworkingwith...)

Speedofdelivery

Problemsolving

Creativityandbrainstorming

Coreworktasks

Seekingfeedbackoradvice

Trainingorlearning

Summary(higherspeedof

workwhenworkingwith...)

Source:AnalysisfromDeloittesurveyof11,387fulltimeandpart-timeworkersconductedinFebruary2025across17countriesinEMEA,Americas,andAPAC.

D

Ingeneral,respondentsratedtheirworkqualityhigherwhen

workingwithhumancolleagues.Respondentsacrossallagegroupsreportedreceivinghigher-qualityfeedbackfromhumancolleaguescomparedtoAI.Asidefromtheyoungestworkers,mostpreferredpeercollaborationoverAIforcoreworktasks.Thesefindings

suggestthatwhileworkersrecognizethevalueofAItools,theystillseebenefitstohumancollaboration—especiallyforworkrequiringin-depthknowledge.

However,whenitcomestospeedofdelivery,thepictureshifts.

Acrossseveraltasks—especiallyproblemsolving,creativity,and

training—respondentsfromyoungeragegroups(ages18to44)weremorelikelytosaythatAIhelpsthemdeliverfaster.Theyoungest

workers(ages18to24)ratedAIhigheronspeedinnearlyeverytasktype.ThesefindingsseemtoreinforcetheperceptionthatAItools

excelinefficiency,eveniftheydon'tyetmatchhumansinqualityornuance.

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ThisreflectsakeytensionattheheartofAIintegration:thetradeoffbetweenspeedandquality.WhileAIisvaluedforitsabilityto

deliverfasterresults,workersacrossgenerationsremaincautious

aboutusingitforworkrequiringhuman-centricskills.Monitoringhowthesepreferenceschangeovertimewillbekeyastechnology

evolves,particularlyasAI-nativeworkersenteringtheworkforce

mayhavestrongerpreferencesforusingthesetoolscomparedto

thosewhoenteredtheworkforcebeforetheadventofAI.25InvestinginAItechnologiesmaynotonlyenhancecurrentworkforce

productivity,butitcouldalsoattracttalenteagertobenefitfromthelatestadvances.26

Oursurveyfindingsalsosuggestthatthereisscopetobettertrain

anddevelopAItoolsandagentstohelpworkerswithcoretasks,

creativity,brainstorming,training,andseekingfeedbackoradvice.Respondents’preferencesforworkingwithAIwerealsoinfluencedbyseveralotherfactors,includingtheirpreparednessandperceptionofAI’sutility.WorkerswhofeltmorepreparedtouseAIatwork

weremorelikelytosaythatAIoutperformshumansinspeed.

Similarly,thosewhofoundAImorehelpfulintheirworkweremoreinclinedtorateAIhigherinbothqualityandspeed.ThesefindingsemphasizetheimportanceofinvestinginAIliteracyandskill

developmentprogramsaspartofaholisticapproachtotechnologyandtalentdevelopment.27

Keytakeaways

LeaderscanconsiderthefollowingactionstoprioritizehumanoversightofagenticAIasitbecomesmoreembeddedin

organizationalworkflows:

Establishingclearboundariesforautomationaround

tradeoffsbetweenefficiencyandquality.UpdatingAIusageguidelinestodistinguishbetweenactivitieswhereAIcanbeusedforspeedandefficiency,andthosethatrequire

deliberatehumanoversightorgovernance,canhelpcreatetheseboundaries.

MonitoringworkforcepreferencesaroundhumanandAI

collaboration.Surveysandfeedbackcanbeusefultoolsfortrackingworkerpreferences.Surveyedworkersratehumanshigheronquality,especiallyforcoretasks,butyounger

surveyedworkers(ages18to24)sayAIdeliversfaster

resultsinnearlyeveryarea.DefiningwhereandhowtouseAIforworkcouldbecomecriticalfororganizationsinthefuture,especiallyasdigitalnativesmajorlycomprisethe

workforce.

Keepinghumans“ontheloop”insteadofjust“intheloop.”

AsagenticAItakesonmorecomplextasksatwork,

organizationscouldshiftfromdirectcontroltosupervisory

oversightonthesetasks.TreatingAIlikeajuniorteam

member—monitored,guided,andcorrectedwhenneeded—canhelpenableefficiencywithoutsacrificingaccountability.

InvestinginAIliteracyandskilldevelopment.RespondentswhofeelmorepreparedtouseAIandunderstandits

capabilitiesandlimitationsrateithigherinbothspeedandquality.PrioritizingtrainingprogramsthatbuildAIfluencycanhelpincreaseadoptionandimpact.

Opportunity3:AIcanbeanupskillingengine—especiallyforentry-level

workers

Organizationsareincreasinglylinkingtogethermultipleagentic

systems,takingagentsdesignedtohandlespecifictasksand

combiningthemtocreatelargerworkflows.Thesenewworkflowscanhelpboostproductivityacrossjoblevelsandfreeuptimeforworkerstofocusonothertasks.

However,whileagentictechnologymayofferefficiencies,italso

raisesquestionsaroundskilldevelopment,especiallyforearly-careerworkers.Itwilllikelybeimportantfororganizationstoinvestnot

onlyintechnologybutalsoindevelopingarobusttalentpipeline.

Deloitte’s

2025HumanCapitalTrends

foundthattwo-thirdsof

surveyedhiringmanagersandexecutivesbelieveentry-levelhiresareunderprepared,withlackofexperiencebeingtheprimaryweakness.

OneriskoftreatingAIdevelopmentseparatelyfromhumancapitaldevelopmentisthatautomationmayreduceopportunitiesforon-

the-jobtraining.Automatingtaskstraditionallyperformedbyentry-levelworkers,suchastakinganddistributingmeetingnotes,may

createshort-termefficienciesbutmaylimiton-the-jobtrainingandothertoolsorganizationshavetraditionallyusedtoupskillearly-

careerworkers.28DeloitteresearchsuggeststhattheriseofAIcouldbecontributingtothedifficultyworkersfaceinfindingentry-leveljobs.29

Tomanagethisdynamic,organizationscanleverageAItoaccelerateskilldevelopmentforearly-careerworkers.Sixty-onepercentof

respondentstooursurveybelievethatAIcansupportupskilling

opportunitiesforentry-levelworkers,withrespondentsbetweentheagesof25and34yearsbeingthemostlikely(66%)toagree.

ResearchbytheNationalBureauofEconomicResearchshowsthatgenAIcanbeparticularlybeneficialforlower-skilledworkers,

offeringreal-timesupportandcoachingtohelpthemlearnfaster.30Italsosuggeststhatearly-careerworkersaremorelikelytoembraceAIasatoolforskilldevelopment.

Figure3

Alcanbebeneficialforupskillingentry-levelworkers

Percentageofrespondentswhoselected“agree”or"stronglyagree”tothestatement,"AIcanhelpupskillentry-levelworkers"

66%64%

64%

57%

54%

56%

18-2425-3435-4445-5455-6465+

Source:AnalysisfromDeloittesurveyof11,387fulltimeandpart-timeworkersconductedinFebruary2025across17countriesinEMEA,Americas,andAPAC.

Deloitte.

ThebenefitsofAIupskillingextendbeyondearly-careerworkers.Asourstudyrevealed,workersacrossallagecohorts,includingthose

nearingretirementage,prefercollaboratingwithamixofhumanco-workersandAI.Butwhile67%ofrespondentsovertheageof65,

inoursurvey,saytheypreferworkingwithbothAIandhumanco-workers,only42%agreethattheyarepreparedtouseAIatwork(comparedto54%ofworkersofallages),suggestingtheremaybeopportunitiestoimproveAIupskillingforthisagegroup.

Keytakeaways

trainingforworkers.Leadersshouldensureautomationdoesn'tdisplacecriticalon-the-joblearning,especiallyforentry-levelroles.

·Providingreal-timecoachingthroughAItools.Sixty-one

percentofsurveyedworkersbelieveAIcanhelpupskill

entry-leveltalent,especiallythosebetweentheagesof25and34.UsingAItodeliverreal-timefeedback,support,and

learningpathwayscanhelpacceleratetalentdevelopment,especiallyforearly-careerworkers.

TohelpworkersacrossallcareerstagesadaptandthriveinanAI-drivenworkplace,leaderscanconsiderthefollowingactions:

·Balancingautomationwithon-the-jobtrainingandlearningopportunities.Thiscanhelpworkers,especiallyearly-careerworkers,stillhaveopportunitiesforhands-onlearningandskilldevelopment.WhileagenticAIboostsefficiency,

automatingtaskslikenote-takingmaylimithands-on

·UpskillingworkersforAIcollaboration.UpskillingcanhelpworkersfeelmorepreparedtouseAIeffectivelyintheir

roles.Althoughahighpercentageofsurveyedworkersages

65andolderpreferworkingwithbothAIandhumans,only42%feelpreparedtouseAI,possiblyindicatinganeedforbuildingAIfluencyintenuredworkers.TailoringAItrainingcanhelpworkersstayproductiveandconfidentinevolvingroles.

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RedesigningonboardingprogramstoencourageAIusefromdayone.TopreparenewhiresforAI-integratedworkflows,organizationsshouldembedAIliteracyintoonboarding.

StartingondayonecanhelpnormalizecollaborationwithAIandbuildlong-termdigitalcapability.

Opportunity4:AIcanaccelerate

knowledgetransferandmentorship

Someorganizationsarealreadysuccessfullyusingcurrent

technologiestohelpmatchworkersacrossjoblevelsandskill

profilestosupportupskilling.Forexample,globalfinancialservicescompanyHSBCusesadigitalplatformtomatchworkerstoprojectsandpeermentorsbasedontheircurrentskillsaswellasthosethey

wanttodevelop.Aveteranemployeewithexpertiseinaparticular

domaincanbealgorithmicallypairedwithayoungerworkerseekingthatskill,allowingtacitknowledgetransferthroughrealprojects.

Thisapproachencouragescross-generationalnetworkingandon-the-joblearning.HSBCreportsthattheseskill-basedopportunitieshavehelpedbreakdownsilos,engageexperiencedstaffasteachersandcoaches,andenableyoungerworkerstolearnfromseasonedexperts.31

Similarly,Salesforce’sCareerConnectAItoolempowersinternal

employeestoexplorepotentialcareerpathwaysbyevaluatingtheircurrentskillsetsandsurfacinginternalrolesandlearningprogramstheymaynothavepreviouslyconsidered.Forexample,one

employee—withoutanypriorsalesbackground—wasmatchedtoaroleinsalesenablementduetorelevantexperienceinchange

managementandcoaching.ThisAI-drivenrecommendationledtointernaltransitionandcareeradvancementthatmighthave

otherwisegoneunrealized.32

Asmoreworkerscontinuetoageoutoftheworkforceandretire,leveragingAItohelpnewerentrantsupskillandtakeonmore

complextaskswilllikelybeimportanttoaddressingpotentialskillshortages.

OursurveyfindingsalsohighlightsomelessobviousopportunitiestoinvestinAIforskilldevelopment.Forexample,60%ofrespondentsinoursurveysaythatAIcanhelpexperiencedworkersshare

knowledgeandskillswiththerestoftheorganization.While

workersundertheageof45aremorelikelytoseethispotential,amajorityofrespondentsacrossallagegroupsagreethatAIcanhelpfacilitateknowledge-sharingfromexperiencedworkers(figure4).

ThisinterestsuggestsworkersareexcitedaboutopportunitiestouseAItoolstosharewhattheyknowandlearnfromeachother.

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Figure4

Alcanhelpwithknowledgesharingandtransfer

Percentageofrespondentswhoselected“agree”or"stronglyagree”tothestatement,“AIcanbelpexperiencedworkersshareknowledge.”

64%

66%

63%

55%

53%

55%

18-24

25-34

35-44

45-54

55-64

65+

Source:Deloittesurveyanalysis.

Deloitte.

Insights

Role-basedresponsesshowmorevariationinrespondents'

perceptionsofAI'spotentialforknowledgetransfer.C-suite

executives(76%),officeworkers(65%),andbusinessowners(64%)aremostlikelytoagreethatAIcanhelpsupportknowledgetransferfrommoreexperiencedworkerstonewerones(figure5).However,

salesworkers(52%),tradeworkers(56%),machineoperators

(53%),andlaborers(48%)arelesslikelytoseeAIasplayingaroleinknowledgetransfer.Identifyingbarrierstokno