未來職業(yè)技術(shù)與全球最大勞動(dòng)力體系的未來_第1頁
未來職業(yè)技術(shù)與全球最大勞動(dòng)力體系的未來_第2頁
未來職業(yè)技術(shù)與全球最大勞動(dòng)力體系的未來_第3頁
未來職業(yè)技術(shù)與全球最大勞動(dòng)力體系的未來_第4頁
未來職業(yè)技術(shù)與全球最大勞動(dòng)力體系的未來_第5頁
已閱讀5頁,還剩29頁未讀, 繼續(xù)免費(fèi)閱讀

下載本文檔

版權(quán)說明:本文檔由用戶提供并上傳,收益歸屬內(nèi)容提供方,若內(nèi)容存在侵權(quán),請進(jìn)行舉報(bào)或認(rèn)領(lǐng)

文檔簡介

JobsofTomorrow:

TechnologyandtheFutureoftheWorld’sLargestWorkforces

WHITEPAPEROCTOBER2025

Images:AdobeStockandGettyImages

Contents

Executivesummary3

Introduction4

1

Workforce-transformingtechnologies5

1.1Artificialintelligence5

1.2Roboticsandautonomoussystems5

1.3Energytechnology6

1.4Networksandsensingtechnologies6

2

Largeglobalworkforces7

2.1Agriculture9

2.2Manufacturing9

2.3Construction10

2.4Wholesaleandretailtrade10

2.5Transportandlogistics11

2.6Businessandmanagement12

2.7Healthcare12

3

Workforcetransformationsandfurtherwork

bytheGlobalFutureCouncil13

Conclusion14

Contributors15

Endnotes16

Disclaimer

Thisdocumentispublishedbythe

WorldEconomicForumasacontributiontoaproject,insightareaorinteraction.

Thefindings,interpretationsand

conclusionsexpressedhereinarearesultofacollaborativeprocessfacilitatedand

endorsedbytheWorldEconomicForumbutwhoseresultsdonotnecessarily

representtheviewsoftheWorldEconomicForum,northeentiretyofitsMembers,

Partnersorotherstakeholders.

?2025WorldEconomicForum.Allrightsreserved.Nopartofthispublicationmaybereproducedortransmittedinanyformorbyanymeans,includingphotocopyingandrecording,orbyanyinformation

storageandretrievalsystem.

JobsofTomorrow:TechnologyandtheFutureoftheWorld’sLargestWorkforces2

JobsofTomorrow:TechnologyandtheFutureoftheWorld’sLargestWorkforces3

Executivesummary

Technologyistransformingworkforces;

ensuringhigh-productivity,inclusivejobsrequiresdiverseactionsacrosstheworld’slargestjobfamilies.

Muchoftherecentdebateonthefutureofjobshasfocusedongenerativeartificialintelligence(genAI),largelanguagemodelsandtheirimpactonwhite-collardesk-basedoccupations,yettechnology-

drivenlabourmarketchangeistransforming

occupationsbeyondthisspace.Thiswhite

paperconsidersfourkeytechnologies:artificialintelligence(AI),robotics,energytechnology,andnetworksandsensingtechnologies.Itassessesthepotentialbenefitsandchallengesoftheir

acceleratingapplicationacrosssevenjobfamiliesthatcomprisetheworld’slargestworkforces:

agriculture,manufacturing,construction,wholesaleandretailtrade,transportandlogistics,businessandmanagement,andhealthcare.

Thewhitepaperfindsthatthepotentialbenefitsandchallengesdiffersignificantlyacrosstheseseven

workforces,aswellasaneconomy’sincomelevelandindustrialmake-up.Thismeansseveralaspectsarenecessarytoensuretechnologydevelopment

leadstohigher-productivityjobs,includingenablinggreaterinvestmentintechnologyandenhancing

diffusion,facilitatingefficientandsupportivemarketstructures,understandingemployers’strategic

workforcegoals,anddiscoveringthepotentialcapabilityofatechnology-enabledworkforce.

TheGlobalFutureCouncilonJobsandFrontierTechnologiesisamultidisciplinaryexpertgroupexploringhowtechnologicalprogresscancreatehigherproductivityjobsandprepareaglobal

workforcetoperformthem.Inaccordancewithitsmandate,thiswhitepaperidentifieskey

areaswherestakeholderactionsaremostlikelytobeimpactful.Theremainderofthecouncil’stermwillseektoidentifyspecificactionsthat

economies,industries,technologydevelopers,employersandotherkeystakeholderscan

taketoenableahigh-productivity,inclusivefutureofjobsthatbenefitsbusinesses,

workersandenhancesglobalopportunity.

JobsofTomorrow:TechnologyandtheFutureoftheWorld’sLargestWorkforces4

Decisionsmadenowandinthe

comingyears

willdetermine

thefutureimpactsoftechnology

development.

Introduction

Fourtechnologieswilltransformmajorworkforces,creatingopportunitiesbutalsorisksthatdemandurgentaction.

AccordingtotheWorldEconomicForum’sFuture

ofJobsReport2025,technologychangesare

expectedtobethebiggestdriveroflabourmarket

transformationinthecomingyears.1Theyhavethe

potentialtocreatehigher-wage,better-qualityjobs,

increaseglobalproductivityandexacerbateinequalitieswithinandacrossgeographies.Thedecisions

madenowandinthecomingyearswilldeterminethefutureimpactsoftechnologydevelopment.2

TheGlobalFutureCouncilonJobsandFrontierTechnologiesisamultidisciplinaryexpert

grouptaskedwithidentifyingwaystoharness

technologieswithlabourmarkettransformation

potentialtoinclusivelyprovidemoreproductivejobstotheglobalworkforce.

Whilemuchoftherecentdebateonthefutureofjobshasfocusedongenerativeartificialintelligence

(genAI),largelanguagemodelsandtheirimpactonwhite-collardesk-basedoccupations,technology-drivenlabourmarketchangeistransforming

occupationsbeyondthisspace.Toarriveat

amorecomprehensiveunderstandingofthe

changesunderway,thiswhitepaperassesses

thepotentialimpactsoftheapplicationoffour

workforce-transformingtechnologiesonsevenjobfamiliescomprisingtheworld’slargestworkforces.Itaimstoidentifythegreatestpotentialworkforceopportunitiesandchallenges.

FutureworkfromtheGlobalFutureCouncilonJobsandFrontierTechnologieswillseektounderstand

howtheseopportunitiescanberealised,andhowriskscanbemitigated–providingguidanceto

businessesandpolicy-makerstoenablehigherproductivityinworkplacesworldwide.

JobsofTomorrow:TechnologyandtheFutureoftheWorld’sLargestWorkforces5

ofemployersexpect

genAItotransformtheirorganizationby2030.

Workforce-transformingtechnologies

Artificialintelligence,robotics,energyandsensingtechnologiespromiseproductivitygainswhileintensifyingrisks.

TheGlobalFutureCouncilonJobsandFrontier

Technologiesdefinesworkforce-transforming

technologiesasrecenttechnologicaladvanceswith

thepotentialtorapidlytransformtheworkforce.Suchadvancementswouldprovideproductivityorcapabilitybooststohelpaddresssociety’skeychallenges,

andhavesubstantialorsystemicriskthatrequiresgovernanceand/orcomplianceenhancements.

Afterreviewingglobalemployers’expectations(setoutintheFutureofJobsReport2025),aggregatingthecouncil’sexperiencewithworkforce-

transformingtechnologiesandassessingthe

workforceimplicationsofemergingtechnologies,thecouncilidentifiedthefollowingfourfrontier

technologiesashavingthegreatestworkforcetransformationpotential.

Artificialintelligence

1.1

Thistechnologyincorporatesmachinelearninganddataprocessing,genAI,artificialgeneralintelligenceandagenticAI.Artificialintelligence(AI)hasbeen

especiallytopicalsincethereleaseandrapiduptakeofconsumer-focusedgenAImodels,and86%of

employersexpectitwilltransformtheirorganizationby2030.3Organizationshavelongharnessed

machinelearningtoenhanceworkforceefficiencyinareassuchasmaintenancescheduling,fraud

preventionandtailoredcustomerservices.4GenAI,meanwhile,becamecommonplaceaftertherelease

ofChatGPTinNovember2022.Manyorganizationscontinuetograpplewithhowthistechnologycan

bemosteffectiveandhowitcouldtransformtheirworkforceneeds.Someexpertsbelieveagentic

AIwillbethemosttransformativecomponentofthetechnology,withAIagentsdrawingongenAItechnologytoperformtasksindependentlywith

userdirectionandoversight.Whilethistechnologycarriespotentialtoenhanceworkerproductivity

orcapability,itcarriessubstantialrisksrelatedtoprivacy,reliabilityandeconomicvaluestructures.

1

Roboticsandautonomoussystems

1.2

TheconvergenceofAI,advancedhardwareandvisionsystemsisbeginningtoenablerobotsandautonomoussystemstoperformanexpanding

arrayoffunctions.ThesesystemsarealsoreferredtoasphysicalAI.Theapplicationofrobotsand

autonomoussystemshasbeensteadilygrowingaround5-7%annuallysince2020.5Withan

estimated40%costreductioninthelasttwo

years,6thisgrowthisexpectedtocontinue.RobotinstallationsareheavilyconcentratedinChina,

Japan,theUS,theRepublicofKoreaandGermany,collectivelyaccountingfor80%ofglobalrobot

installationsin2022.7PhysicalAIdevelopments

createanopportunityfornewrolesandenhancedworkerproductivity8–however,thisoutcomewilldependonchoicesmadeinthecomingyears.

1.3

Energytechnology

Overall,41%ofemployersexpectenergy

technologytotransformtheirorganizationsby2030.9Thisencompassesenergygeneration,storageanddistribution.Thesetransformationscanenhanceenergyefficiencyandcreatenewgenerationopportunities,andcouldleadto

significantchangesinworkforcecapability.

Changingenergydemandsalsoleadto

consumptionchanges,suchasincreasesin

theuseofelectricvehiclesanddemandfornewenergytopowerdatacentres.Thesechanges

couldalsobedisruptive,withsignificantchangesinthetypesofdemandedjobsandskillsrelatedtoenergyuse.

1.4

Networksandsensingtechnologies

Theintegrationofnetworksandsensing

technologiescreatesaplatformthatenables

greaterdevelopmentandeffectivenessofothertechnologies,includingAI,roboticsandenergytechnologies.Asnetworktechnologiesadvance,theirimpactdiffersbyregionandincomelevel.Currently,internetaccessvarieswidelyacrossregions,from91%inEuropeto38%inAfrica.

Theregionalworkforceimpactofnetwork

technologydevelopmentwilldependonwhetheritexacerbatesaccessibilitydiscrepanciesor

enhancesaccessforlessconnectedareas.

Thistechnologicaldevelopmentwillcreate

opportunitiestoenhancethecapabilityofworkerswhilecreatingrisks,includingdisruptionand

privacyconcerns.Developmentsinsensing

technologiesenhancetheroleofnetworksas

wellasothertechnologieslikephysicalAI.Recentadvancesincludeaffordablehigh-resolution

cameras,lightdetectionandranging(LiDAR)

andnext-generationtactilesensors,whichallow

interpretationofcomplexenvironmentsinrealtime.

JobsofTomorrow:TechnologyandtheFutureoftheWorld’sLargestWorkforces6

Largeglobalworkforces

Sevenmajorjobfamiliesfacedistinct

technologicaltransformation,withvariedglobalimpacts.

Thiswhitepaperfocusesonsevenjobfamilies

thatcomprisetheworld’slargestworkforcesandwhereimpactsarelikelytobegreatest:agriculture,manufacturing,construction,businessand

management,wholesaleandretailtrade,transportandlogistics,andhealthcare.Collectively,these

workforcesmakeupalmost80%oftheworld’s

workers,withdifferingconcentrationsacross

economiesatdifferentincomelevels,asshowninFigures1and2.Thefollowingsectiondiscussescharacteristicsoftheseworkforcesandassessestheopportunitiesandchallengescreatedbytheacceleratedapplicationofthefourworkforce-

transformingtechnologiesidentifiedinChapter1.

2

FIGURE1

Jobfamilysizebyeconomyincomelevel

Upper-middle

High

Lower-middle

Low

Lower-middle

High

Upper-middle

Low

Upper-middle

Lower-

middle

High

AGRICULTURE

Upper-middle

Lower-middle

Low

CONSTRUCTION

Upper-middle

Lower-middle

High

OTHER

High

Upper-middle

Lower-middleLow

MANAGEMENT

MANUFACTURING

WHOLESALEANDRETAILTRADE

BUSINESSAND

High

Upper-middle

Lower-middle

TRANSPORTANDLOGISTICS

HEALTHCARE

High

Upper-

middle

...

JobsofTomorrow:TechnologyandtheFutureoftheWorld’sLargestWorkforces7

Source:InternationalLabourOrganization(ILO)(2023)ILOModelledEstimates(ILOESTdatabase)

JobsofTomorrow:TechnologyandtheFutureoftheWorld’sLargestWorkforces8

FIGURE2Workforcesbyjobfamilyandeconomyincomelevel

18%

14%

13%

12%

6%

Manufacturing

9%8%8%8%

3%

Construction

Wholesaleandretailtrade

14%

15%

13%

14%

14%

Transportandlogistics

3%

6%

7%

10%

7%

Businessandmanagement

3%

4%

7%

14%

7%

Healthcare

1%

1%

2%

8%

3%

Agriculture

57%

39%

20%

3%

26%

Other

14%

14%

24%

32%

22%

Upper-middle

LowLower-

HighWorld

middle

Economyincomelevel

Source:InternationalLabourOrganization(ILO).(2023).ILOModelledEstimates(ILOESTdatabase).

JobsofTomorrow:TechnologyandtheFutureoftheWorld’sLargestWorkforces9

2.1

Agriculture

Theagricultureworkforceisbyfartheworld’s

largest,makingupaquarteroftotalglobal

employment.Thisworkforceisfarmoreprominentinlower-incomeeconomies,comprising57%

ofworkersinlow-incomeeconomiesand39%ofworkersinlower-middle-incomeeconomies,comparedto20%ofworkersinupper-middle-incomeeconomiesandjust3%ofworkersinhigh-incomeeconomies.

Thefourworkforcetransformationtechnologiescouldreformthewaythisworkforceoperates.

Technologyisalreadytransformingdemandson

theagricultureworkforce,althoughitsimpact

variessignificantlybetweenregionsandactivities.Forexample,agriculturaldronesarebeingused

inSouthAmericatotransportcutbananabunchesfromsteephillsideplantations.Thistechnology

enablesdrasticincreasesinthenumberof

bunchesaworkercanharvest,withresulting

increasesinproductivityandimprovementsin

safety.Precisionagriculture,meanwhile,isbeingappliedtoavarietyofcroppingoperations.

Poweredbydrones,networktechnologyandAI-drivenanalytics,itallowsfarmerstomonitor

soilhealth,wateruseandcropconditions

inrealtime.Thisreducesrelianceonmanual

labourforroutinemonitoringandcreatesdemandfornewroles,suchasdroneoperators,data

analystsandagritechtechnicians.Automationandroboticsarealsoredefiningon-farm

labourbyreducingdependenceonseasonalandmanualworkers.Autonomoustractors,

roboticharvestersandautomatedirrigation

systemsarebeingdeployedacrossregions

suchasEuropeandNorthAmericatoaddresslabourshortagesandenhanceproductivity.

Thesetechnologieshavesignificantproductivity

potentialforfarmingoperationswiththeresourcestofundcapitalinvestmentandcouldsignificantlychangetheexpertiserequiredoftheworkforce

operatingthesesystems.Asignificantproportionofthisworkforce,however,aresmallholderfarmersinlower-incomecountrieswhereinvestment

capacityislikelytobelimited.Enablingglobal

benefitsoftechnology,therefore,requires

interventionstosupportglobaltechnological

diffusion,althoughthistoocomeswithrisksof

displacingemploymentforvulnerablepopulations.

2.2

Integrated

mobilerobots,

AI-basedsortingandgenAI-guidedmanipulators

canenable

fasterdelivery,

increasethe

demandforskilledrolesandcreate

efficiencygains.

Manufacturing

Manufacturingrepresentstheworld’ssecond-

largestworkforce,makingup14%oftotalglobalemployment.Thisemploymentisparticularly

prominentinsomeAsiancountries,including

China,VietNam,andTaiwan,China,and

Europeancountries,includingCzechia,SloveniaandHungary.Thetypeofmanufacturingdiffers

substantiallybyindustryandregion.Textiles,

automobilesandpharmaceuticalsformdistinct

manufacturinghubsindifferentcountriesand

regionsaroundtheworld.Thesemanufacturing

hubsalsodiffersignificantlyindemographic

makeup.10Thesedifferenceshaveimplicationsforthetypesoftechnologyadoptionpossibleandthecurrentlevelsofinfrastructure.RoboticssystemsincorporatingAIareespeciallyrelevantforthe

manufacturingworkforce,withthepotentialto

significantlyenhancehumancapabilityalongsidethepossibilityofeliminatingsignificantamountsofworkthroughautomation.Thepathoftechnologydevelopmentandadoptionwilldeterminewhetherthistechnologyleadstorepetitivelow-valuetasksbeingreplacedbyhigher-valueactivitiesora

reductionintotalemployment.

Whileroboticshasbeenadoptedinmanufacturingprocessesforalongtime,physicalAIisincreasinglyenhancingthecapabilitiesofthesesystems.

Severalcutting-edgeusecasesillustratehowthis

technology,combinedwithrobotics,couldtransformthemanufacturingworkforce.11Forexample,AI-

enabledvisualqualitycontrolinspections,combinedwithautonomousrootcauseanalysisandprocess

mining,identifyfactorylineissuesmuchfaster

thancurrentqualitycontrolprocesses.Similarly,

integratedmobilerobots,AI-basedsortingand

genAI-guidedmanipulatorstofulfile-commerce

orderscanenablefasterdelivery,increasethe

demandforskilledrolesandcreateefficiencygains.12

TheseAIincorporationsintoexisting

manufacturingprocessescouldtransformjobs

intohigher-productivityroleswithhigherexpertiserequirements.Theamountofproductivity

enhancement,andwhetherthisisaccompanied

byanincreaseordecreaseindemandforworkers,willdependonseveralfactors,includingmethodsofadoption,investmentcapacityandexisting

manufacturinginfrastructure.

JobsofTomorrow:TechnologyandtheFutureoftheWorld’sLargestWorkforces10

oftheglobalworkforceismadeupwholesaleorretailsalesworkers.

2.3

Enabling

thebenefitsof

technological

development

inconstruction

willrequirenew

investment,the

incorporationof

thistechnology

intoneworexistingworkflowsand

afuture-proofedworkforce.

Construction

Around8%oftheworld’sworkersarepartoftheglobalconstructionworkforce.13Apeculiarityof

thisjobfamilyisthatittendstomakeupasmallerproportionofaworkforceaseconomiesmoveuptheincomespectrum,exceptforinlow-income

economies,whereitmakesuplessthan3%ofthetotalworkforce.Theconstructionworkforcealsocoversawiderangeofprojects,fromsmallresidentialbuildingstolarge-scaleinfrastructurelikebridgesandpowerplants.

Constructiontasksareoftenvariable,with

jobsitesconstantlychanging.Thismakesfull

automationmorecomplex;however,transformativetechnologiesarechangingthewaythisworkforceoperatesandtherequirementsofitsworkers.

Buildinginformationmodellingsystemsareamajorcomponentofmodernconstructionandinvolve

digitalplanningofconstructionoperations.AIis

increasinglybeingintegratedintothesesystems

toenhanceworkplanningandscheduling,

optimizefootprintuse,ensurecompliancewith

localregulationsandincorporatelocalcomfortandsafetyintobuildings.Theseenhancementsboost

workers’efficiencyandcapabilitiesbyimprovingthefunctionalityofbuildings.

ThecombinationofAIandroboticsinconstructionmachinerycouldalsotransformconstruction

roles.Oneexampleissemi-automatedbricklayingmachinery,whichcanlaybricksaccordingtothedesignandspecificationsinputbyconstruction

workers.Thissortoftechnologyreliesonworkers’masonryexpertisebutcanincreaseworkeroutputandreducerelianceonphysicalskills.

Onalargerscale,theentire84-metre-high

KawakamidaminMie,Japan,wascompletedin2023usingrobotics.14Thisincludedremote-controlledcraneoperations,brushingmachines

thatcalculatedthepressureandfrequency

requiredtosmoothconcretesurfacesandboxingmachinesthatcontrolledthesupportstructuresofwetconcrete–automaticallyadjustingpositionastheconcretedried.Thissortoftechnology

redirectstheconstructionworkforcetowards

planningandmonitoringoperationsratherthanactivelyparticipatingintheconstructionprocess.Thiscanenablecapability-buildinginareasthataredangeroustoaccess,whilealsoimproving

efficiency.However,achievingthisrequiresa

fundamentalworkforceskillshiftandentirelynewtrainingapproaches.

AfurtherexampleofcombiningAIandothertechnologiesisusingcomputervisionto

monitorequipmentfordamage,provide

real-timehazarddetection,ensurerapid

qualityassurancebycomparingexecuted

workwithblueprints,andsupportlogistics

planningbytrackingprojectprogressionandidentifyingdelays.Thiscouldhavesignificantimplicationsforthesafetyoftheconstructionworkforce,alongsideproductivitygains.

Anothertechnologicallyenabledshiftinthe

constructionworkforceistheincreasing

useofprefabricationinbuildingsandthe

developmentofrobotics,including3Dprintingtoproducethese.Whilethesearelikelytobelimitedtocertainsectionsoftheconstructionindustry,theywillchangethetypesofexpertisevaluedandshiftlabourdemandstowards

advancedtransportandlogisticssolutions.

Enablingthebenefitsoftechnologicaldevelopmentinconstructionwillrequirenewinvestment,

theincorporationofthistechnologyintonew

orexistingworkflowsandafuture-proofed

workforcetoharnesstheseadvancedsystems.

Wholesaleandretailtrade

2.4

Thisworkforceencompassespeoplewhoengageinwholesaleorretailsalesandtheservices

relatedtothem.Theymakeuparound13%

oftheglobalworkforce,holdingaconsistentproportionregardlessofcountryincomelevel,althoughregionaldiscrepanciesexist,withalargerproportionofworkersinLatinAmericaandtheCaribbean.15Thewholesaleandretailtradeworkforceisalargeurbanemployerandcanactasakeyentrypointforwomenand

youthinlow-andmiddle-incomecountries,whoareoverrepresented.

AI-enabledbusiness-to-business(B2B)apps

arechanginghowsmallandinformalretailers

restock.AcrossEgypt,Morocco,Kenya,RwandaandTanzania,smallretailshopsandhundredsofthousandsofinformalretailersnowrestockvia

B2Bapps.OrdersarescheduledwithAI-driven

demandforecastingandrouteoptimization,whichcutsstock-outsandwastedwholesalertrips.Thiscanenhancetheproductivityofbothwholesalersandretailers.Similarly,AIintegrationintoclick-and-collectprocessesischangingthisworkforcein

Africa,IndiaandLatinAmerica.

Thisintegrationautomatestheassigningoftasks

andlogistics,shiftingworkersfromtillstopicking,

packingandlast-milecoordination.Thisshift

enhancesthecapabilityofworkersandenables

rapiddeliverytimes–includingsame-dayandevenwithin-hoursdelivery.Dronesarealsoshiftingthe

workforcefromfrontlineretailtowardsoperations

andmaintenanceroles.InGhana,retaildrone

deliverywaspilotedin2022socustomersinremoteareascouldreceivesmalle-commerceorders

withinminutestoapick-uppoint.Thisisespeciallyvaluableforhigh-value,time-criticalitems.

Energygenerationandstoragetechnologiesare

alsotransformingthewholesaleandretailtrade

workforce.InSouthAfrica,NigeriaandIndia,

wholesalersareimplementingrooftopsolarpanels

andbatteriestoavoidoutagesandreducediesel

use.Thisenablesjobstoshifttowardsenergysystemmonitoring,refrigerationmanagementandpredictivemaintenance,andstabilizeshoursforfrontlinestaff

whousedtobesenthomeduringpowercuts.

Thesetransformativetechnologyshiftscreate

opportunitiesfortechnicaloperatorstomaintain

systemslikeenergy,storageandrefrigeration,andtooperateroboticssuchasdrones.Data-enabledsupplychainandqualityfunctionsarealsoin

demand,withrolesininventoryplanning,demandanalysisandtraceability.Newworkerswillalso

berequiredforcustomeronboardingandretailersupportforB2Bapplications.Theseroleswilloftenbehigher-wagethantheexistingwholesaleand

retailtraderoles,howeverthisalsobringsrisksofdisplacementtotheworkforce,whiletheabilitytodevelopnewnecessaryskillswillbelimited

forsomeworkers.Returnswillaccruetothosewithtechnicalanddatacapability,whilesmallretailerscouldfacefeesanddatalock-inriskswithlargeplatformproviders.Skilldevelopmentwillbeessential,whilethedevelopmentof

datastandardsorsharedserviceswillplaya

roleindeterminingthedistributionalimpactof

transformativetechnologiesonthewholesaleandretailtradeworkforce.

2.5

oftheworld’sworkersareinthetransportandlogisticsworkforce.

Transportandlogistics

About7%oftheworld’sworkersareinthe

transportandlogisticsworkforce,withthisjobfamilymakingupanincreasingportionoftheworkforceaseconomiesmoveupinincomedistribution.Theseworkersareinvolvedinallaspectsoffreightandpeopletransport,as

wellashandlingandstoring.AIisincreasingly

transformingthisworkforce,includingthrough

agenticAIprocessesthatcanautomaticallyprocessorderformsandoptimizelogistics.Thisenhances

theproductivityofthetransportandlogistics

workforcebyensuringtimeanddistanceare

optimized,andincreasescapabilitybyenablingdeliveriestobemadewithshorterleadtimes.

Robotics,especiallydronesfordeliverycould

alsotransformthetransportandlogisticsworkforce.ThiscanbeseenincountriessuchastheUnited

ArabEmirates,wheredronedeliveryformspartofasmartcitiesplan,movingdemandawayfromroadvehicleoperatorstowardsback-endcon

溫馨提示

  • 1. 本站所有資源如無特殊說明,都需要本地電腦安裝OFFICE2007和PDF閱讀器。圖紙軟件為CAD,CAXA,PROE,UG,SolidWorks等.壓縮文件請下載最新的WinRAR軟件解壓。
  • 2. 本站的文檔不包含任何第三方提供的附件圖紙等,如果需要附件,請聯(lián)系上傳者。文件的所有權(quán)益歸上傳用戶所有。
  • 3. 本站RAR壓縮包中若帶圖紙,網(wǎng)頁內(nèi)容里面會(huì)有圖紙預(yù)覽,若沒有圖紙預(yù)覽就沒有圖紙。
  • 4. 未經(jīng)權(quán)益所有人同意不得將文件中的內(nèi)容挪作商業(yè)或盈利用途。
  • 5. 人人文庫網(wǎng)僅提供信息存儲(chǔ)空間,僅對用戶上傳內(nèi)容的表現(xiàn)方式做保護(hù)處理,對用戶上傳分享的文檔內(nèi)容本身不做任何修改或編輯,并不能對任何下載內(nèi)容負(fù)責(zé)。
  • 6. 下載文件中如有侵權(quán)或不適當(dāng)內(nèi)容,請與我們聯(lián)系,我們立即糾正。
  • 7. 本站不保證下載資源的準(zhǔn)確性、安全性和完整性, 同時(shí)也不承擔(dān)用戶因使用這些下載資源對自己和他人造成任何形式的傷害或損失。

最新文檔

評論

0/150

提交評論