2026年智能工业运营展望（英）

IncollaborationwithAccenture

IndustriesintheIntelligentAge

IntelligentIndustrial

OperationsOutlook2026

WHITEPAPERAPRIL2026

Images:Midjourney,GettyImages

Contents

Foreword3

Executivesummary4

Introduction5

1

Emergenceofintelligentecosystems6

1.1Eightkeyforcesdrivingstrategicimperatives6

1.2Intelligentecosystemswilldefinethenextera8

2

Factory|Core13

2.1Planning14

2.2Production16

2.3Quality19

2.4Maintenance22

2.5Internallogistics24

3

Company|Extended27

3.1Procurement27

3.2Manufacturingengineering30

3.3Productdevelopment33

3.4Supplierandengineeringquality36

4

Supplychainnetwork|Ecosystem39

4.1Supplychainandnetworkplanning39

4.2Externallogistics42

4.3Customerintegration44

4.4Suppliercollaboration47

5

Leadershipandgovernanceinintelligentoperations49

5.1IntelligentOperationsBoardroom49

5.2Cybersecuritybydesign50

6

Wayforward:leadershipimperatives52

Conclusion54

Contributors55

Endnotes57

IntelligentIndustrialOperationsOutlook20262

IntelligentIndustrialOperationsOutlook20263

April2026

IntelligentIndustrialOperationsOutlook2026

Foreword

KivaAllgood

ManagingDirector,

WorldEconomicForum

Industrialoperationsarecrossingahistoricthreshold,onewhereintelligencebecomestheorganizing

principleofhowtheworlddesigns,makesand

moves.Fordecades,progresswasdefinedby

automation,integrationandscale.Today,anew

paradigmisemergingwhereoperationalsystems

perceivecontext,anticipatechangeandcoordinatesemi-autonomouslyacrossfactories,enterprisesandglobalvaluenetworks.

ThisoutlookreporthasbeendevelopedbytheWorldEconomicForumincollaborationwithAccentureandispartoftheForum's

IndustriesintheIntelligentAge

WhitePaperSeries

.Informedbymultipledialoguesacrossindustry,technologyandacademia,itreflectsasharedperspectiveonhowthisshiftisreshaping

theindustriallandscape.

Whatdistinguishesthismomentistheconvergenceoffrontiertechnologiesintoanewoperational

fabric.Advancedanalytics,artificialintelligence(AI),digitaltwinsandcyber-physicalsystemsareno

longerdeployedinisolation;together,theyenable

environmentsthatlearnfromeveryinteraction,

reconfigureinthefaceofdisruptionandcontinuouslyevolvethroughexecution.

ChristianSouche

ManagingDirector,Accenture

Intelligencehasmovedbeyondbeinganoverlaytobecominganintegralpartofoperationalsystems,enablingorganizationstorespondfastertochangeandmakebetterdecisionsacrossthevalue

chain.Thistransformationisnotpurelytechnical;

itraisesnewquestionsaroundtrust,securityand

sustainability.Asautonomyexpands,leadersmust

determinehowintelligencescalesupresponsibly

andhowtheyshouldstrengthengovernance,

reshapeoperatingmodelsandpreparetheworkforcetocollaboratewithsystemsthatincreasinglyact,

reasonandcoordinatealongsidethem.

Wehopethisreportwillhelpindustrialleaders

tonavigatetheshifttowardsintelligent,adaptiveoperations,aswellastoframestrategicchoices,setinvestmentprioritiesandbuildcapabilities.

Theopportunityaheadisprofound:tobuild

industrialsystemsthatarenotonlymoreadaptivebutfundamentallymorecapablethaninany

previousgeneration.

Executivesummary

Industrialoperationsareenteringadecisive

decadeshapedbystructuralshocksand

acceleratingfrontiertechnologies.Geopolitical

shifts,climatevolatility,workforceshortagesand

heightenedcyberriskaredisruptingtraditional

operatingmodels,whileadvancesinAI,

automation,simulation,roboticsand

hyperconnectedinfrastructureareredefiningwhatindustrialsystemscanachieve.Theseforces

areacceleratingtheshifttowardsintelligent

industrialoperationsthatlearncontinuously,adaptautonomouslyandoperateinsyncacrossfactories,enterprisesandmulti-tiernetworks.

Thisreportexamineshowtheseshiftsplayout

acrossthevaluechain.Itoutlinestheshared

designlogicemergingacrossdiversefunctions,

ascapabilitiesprogressfromearlyexperimentationandassistedintelligence,throughscaled-up

human-machinecollaboration,towardsincreasinglyautonomous,self-orchestratingsystems.

Itintroducesafuture-readytransformationmodel(seeFigure4)thathelpsleadersunderstandhowfunctionswillevolveoverthenextdecade,andassessestheroleofdifferenttechnologiesin

drivingthisevolutionandtheirpointsofgreatestoperationalimpact(seeFigure5).

Todeliveronthisshift,leadersmustfocusonasmallsetofenablers:

–StrengthengovernanceforAI-drivendecisions.

–Embedcybersecurityfromtheoutset.

–Enabletheworkforcetocollaborateeffectivelywithintelligentsystems.

Asautonomyscalesupacrossoperations

andecosystems,leadersmustensurethese

systemscreatevalueresponsiblyandinlinewithstrategicpriorities.

1

FIGURE

Executivehighlights

13

Future-ready

operationalfunctions

Function-by-functionblueprintofhowintelligenceisbeing

embeddedacrosstheindustrialvaluechain,includingreal-worldcasestudies.

Transformationmodel+Technologyimpactprofile

Commonevolutionpatternsandtechnologyimpactovertimethatguidetheshifttowards

intelligent,interconnectedandvalue-drivenoperations.

Leadershiproadmap

Clearprioritiestohelpleaderssteer,sequenceandscale-upintelligenttransformation.

35+

Cross-cutting

transformationthemes

Shiftsthatexplainhow

intelligencetransforms

performanceandhoweachfunctionevolvesovertime.

IntelligentIndustrialOperationsOutlook20264

Introduction

InafulfilmentcentreoutsideLondon,hundreds

ofrobotsglideacrossagriddeliveringcratesto

AI-drivenarms.Whenagrippermisjudgesasoft

itemlikeapeach,thesystempauses,adjustsits

gripusingcognitivelearningfromthousandsofpriorpicksandcontinueswithoutdelay.Orderskeep

flowingandthenetworkgrowssmartereveryhour.1Thisisnotsciencefictionbuttoday’sreality,pointingatabroadershifthappeningthisverymoment.

Aneweraofindustrialintelligenceisbeginningtoreshapehowtheworlddesigns,makesandmovesgoods.AdvancesinAI,automation,connectivity,

simulationandacceleratedcomputingareelevatingindustrialoperationstonewstandardsofprecision,agilityandscale.Asthesecapabilitiesconverge,

theyareredefiningoperationalmodelsandopeningnewpossibilitiesforend-to-endvaluecreation

acrossindustrialecosystems.

Thistransformationisunfoldingamidgrowingglobaluncertainty,heighteningthestrategicimportance

ofbuildingoperationsthatcanwithstandshocks,

adaptquicklyandcompeteonresilienceand

adaptability.Increasingautonomyandreal-time

orchestrationarepushingorganizationstorethinkhowindustrialsystemsaredesignedtoperform

underconstantchangeacrosscomplexvalue

chains.Thisisunlockingasetofcoreambitionsthatextendwellbeyondefficiencyalone,includingsupplychainresilience,workforceempowerment,sharpercustomerfocusandmoresustainable

operationsatscale.

Acrossthesedimensions,outcomesare

increasinglyshapedbydesignchoicesmade

upfrontratherthanincrementaloptimizationover

time.Inthecaseofsustainability,forexample,moreefficientuseofenergy,materialsandresourcescanbeengineereddirectlyintooperations,embeddingresourceefficiencyasafoundationalcapability

ratherthanadownstreamadjustment.However,thispresentsadualmandateforindustry:to

captureAI-drivenperformanceimprovements

whileensuringtheresourcecostofenablingthemremainsjustified.2

Outcomesareincreasinglyshapedbydesignchoicesmadeupfrontratherthanincrementaloptimizationovertime.

Atthesametime,withtheriseofautonomous,

hyperconnectedoperations,digitaltrustemergesasacoredesignrequirement.Connectivitythatenablesreal-timeorchestrationalsoexpands

exposuretocyberrisk,requiringsecurity,integrityandtransparencytobebuiltbydesign.Together,

theseshiftssuggestthatthefutureofindustrial

operationswillbedefinednotonlybytechnologicalcapabilitybutbyhowthoughtfullyorganizations

applyittostrengthenperformance,resilience,sustainabilityandtheroleoftalent.

IntelligentIndustrialOperationsOutlook20265

Emergenceofintelligentecosystems

Compoundingstructuralshocksareforcingindustrialoperationstoshiftfromefficiency-ledmodelsto

adaptiveresilience.

Industrialoperationsareatadecisiveturning

point.Economicvolatility,climatepressures,

rapidtechnologicaladvancesandgeopolitical

fragmentationareintensifyingthestrainon

traditionalefficiency-ledmodelsofcompetitiveness.

Inthisevolvinglandscape,resilience,

adaptabilityandecosystem-levelcollaboration

arebecomingessentialcapabilitiesfornavigatingincreasinglycomplexandinterconnected

operatingenvironments.

1.1

Eightkeyforcesdrivingstrategicimperatives

InitsJune2025publication,

FromShockto

Strategy:BuildingValueChainsfortheNext30

Years

,theWorldEconomicForumidentifiedeightkeyforcesreshapingglobalmanufacturingand

steeringstrategicdecision-makingoverthenextthreedecades.Table1alignseachglobaldrivingforcewithacorrespondingstrategicimperative,illustratinghowindustrialleaderscantranslate

disruptionintolong-termadvantage.Together,

thesestrategicimperativesdefineanewindustrialparadigmthatisrootedindigitalresilience,adaptiveecosystemsandsustainablevaluecreationforthedecadesahead.

Theseforcesformthebroaderstrategiccontextforthetransformationsexploredthroughoutthisreport,shapinghowindustrialfunctionsevolveacross

theecosystem.

1

IntelligentIndustrialOperationsOutlook20266

IntelligentIndustrialOperationsOutlook20267

1

TABLE

Eightkeyforcesdrivingstrategicimperatives

Strategicimperative

Drivingforce

Strategicimperative

Drivingforce

Regionalized,adaptivenetworks

Accelerateddigitaltransformation

—ScaleupAI,robotics,quantum,IoTandcloudacrossoperations

—Useinteroperablesystemsand

digitalskillsforagilityandinnovation

—Developdiversified,digitally

Globalrelationsandtrade

Technologyevolution

enabledregionalsupplychains

—Transitionfromreactiveadaptationtoproactiveorchestrationtoremaincompetitiveamidmarket

fragmentation

Cybersecurity

Intelligentsecurityintegration

—Embedcybersecurity

acrossoperationallayers

—UseAI-drivendetectionand

automatedresponseforproactiveprotection

Workforce

andskills

Human-machinecollaboration

—Acceleratedigitalreskillinganddeployautomationtofillgaps

—Combinerobotics,AIknowledgesystemsandflexiblemodelsforsynergy

Digitalcompliance

—Automatemonitoringand

Regulatorycomplexity

reportingwithAIanddigitaltwins

—Usescenariosandgovernancetoolstoanticipateregulatory

change

Customer-centricagilityandtraceability

Consumer

behaviourandexpectations

—Usereal-timeinsightsforagileproductionandrapidresponse

—Embedtransparencyandtraceabilitytobuildtrust

Resilientandcircularoperations

Operationalinclusionandworkforceempowerment

Social—Embedinclusivepractices

Climate

disruption

equityacrossoperations

—Strengthenresiliencewithreal-timeanalytics

—Expanddigitalaccess,fairness

andempowermentfor

underrepresentedgroups

—Adoptcircularresourcestrategiestoreduceexposureandimpact

IntelligentIndustrialOperationsOutlook20268

1.2Intelligentecosystemswilldefinethenextera

Transformationtimeline:NOW–NEAR–NEXT

“NOW–NEAR–NEXT”horizons(seeFigure2)

thathelporganizationstounderstandemerging

capabilities,anticipateshiftsacrossthevalue

chainandassesshowtoday’schoicesmayshapetomorrow’soperatingmodels.

Thisreportoutlinesaforward-lookingperspectiveontheevolutionofindustrialoperationsoverthenextdecadeandtheshiftsreshapinghowvalueiscreatedend-to-end.Ratherthanprescribingasinglepathway,itframesprogressthroughthree

FIGURE2Transformationtimeline

NOW(0–2years)

Earlyadoptionoffrontiertechnologies

NEAR(3–5years)

Expandinghuman–machinecollaboration

NEXT(5+years)

Asymbiotic,living,near-autonomousecosystemwherehuman–machinecollaborationreachesitsfull

transformativepotential

Thereportincorporatesinsightsfrominterviewswithindustryleadersacrossdiversesectorsandleadingglobalcompanies,alongwithpublicly

availableinformationandsecondaryresearch.

Itevaluatesmanufacturingcapabilitiesbasedonobservedbestpracticesandglobalcasestudies.

Threelayersand13functionsofindustrialoperations

Industrialoperationscanbeunderstoodthroughthreeinterconnectedlayersthatspanphysicalproductiontoglobalcoordination:

–Factory|Corelayer:production-adjacent

activitieswherephysicalassets,digitalsystemsandhumanoversightintegratetoconvert

materialsintofinishedproducts.

–Company|Extendedlayer:enterprise-

levelcapabilitiesthatdirect,coordinate

andcontinuouslyrefinehowmanufacturingoperates.

–Supplychainnetwork|Ecosystemlayer:broadernetworkthatsynchronizesflows

acrossallstakeholderstocoordinateandrespondinrealtime.

Collectively,thesethreeinterconnectedlayers

framehowoperationalfunctionscontributetovaluecreation,emphasizingthatoperationalperformanceisnowdrivenacrosstheenterpriseandbroader

ecosystem.Figure3illustratesthisinterconnectedview,showingoperationsasintegratednetworksratherthanisolatedfunctions.

IntelligentIndustrialOperationsOutlook20269

7.Manufacturingengineering

8.Productdevelopment

9.Supplier&engineeringquality

10.Supplychain&networkplanning

11.Externallogistics

12.Customerintegration

13.Suppliercollaboration

The13future-readyoperationalfunctionsconsideredinthisreportareasfollows:

1.Planning

2.Production

3.Quality

4.Maintenance

5.Internallogistics

6.Procurement

FIGURE3Threeinterconnectedlayersintegrate13operationalfunctions

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IntelligentIndustrialOperationsOutlook202610

Valuechainintegration

Howoperationalfunctionsevolvemattersas

muchashowfartheyprogress.Whenefficiency

orautomationarepursuedinisolation,progress

plateaus.Incontrast,functionsthatbuildautonomywhilealsodeepeningecosystemintegrationare

betterabletoscaleupandsustainimpact.

13operationalfunctionsevolve,evenas

eachfollowsitsowndistincttrajectory.Thefigureoffersaconsolidatedviewthatillustrateshow

durabletransformationdependsonadvancingacrossthetwodimensionsofautonomyandintegrationtogether.

ThetransformationmodelpresentedinFigure4

capturesthesharedpathwaysthroughwhichthese

FIGURE4

Transformationmodel

Integrated

Cross-enterprise

Transformationofoperationalfunctionstowardsfullyintegrated,self-managingoperations

10.Supplychain&networkplanning

11.Externallogistics

12.Customerintegration

11.Externallogistics

Autonomy

●NowNext

Interpretationofthegraph

1.Autonomy(x-axis):showshowanoperationalfunctioncanoperateintelligentlyandindependently,progressingfromhuman-leddecision-making(“assisted”)tohuman-AIcollaboration(“co-adaptive”),thenAI-orchestrated(“self-directing”)andfinallytoself-managingsystems.

09.Supplie

quality

12.Custom

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03.Quality

04.Maintenanc

06.Procurement

07.Manufactur

08.Productde

09.Supplier&

01.Plannin

13.Supplie

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engineering

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rcollaboration

Crossfunctional

quality

02.Produc

05.Internal

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logistics

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Functional

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01.Plann

02.Prod

08.Product

10.Suppplanning

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development

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05.Internal

06.Procur

07.Manufa

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Co-ad

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2.Valuechainintegration(y-axis):indicateshowwidelyanoperationalfunctionintegratesacrossthevaluechain,fromfunctionalsilos,acrossfunctionsandtomulti-enterprisecollaboration

IntelligentIndustrialOperationsOutlook202611

–Eachtechnologywasassessedacross

13operationalfunctionsandtimehorizons(NOW–NEAR–NEXT)usingaconsistent1-5impactscalerangingfromearlypilotsto

transformationalchange.

–Thechartnormalizesresultstohighlightwhenimpactisexpectedtoscaleup.

–Thischartdoesnotrepresentageneralmarketviewoftechnology.

Thefunctionalprogressiondescribedabovedoesnotoccurindependentlyoftechnologychoices.

Movementfromassistedtoself-managingand

fromsiloedtointegratedecosystemsdepends

onhowenablingtechnologiesareintroducedandsequenced.Thetechnologyimpactprofilethat

followstranslatesthisprogressionintoacapabilityview,showinghowkeytechnologiesshapethe

timingandbreadthofenterprisetransformation.

ThechartinFigure5visualizestheassessed

businessimpactofkeytechnologiesonindustrialoperationsacrosstimehorizonsbasedonfunctionlevelassessments,informedbythisstudy’sthemesandevolutionnarratives:

5

FIGURE

Technologyimpactprofile

Impactoftechnologies,alongNOW-NEAR-NEXTtimelinesCross-functionalapplicability

AutonomousOrchestratingFoundational

7 10 6 135 7 7 2 135 5

Edge/IoTPredictive&prescriptiveAIRoboticsandAMRs/AGVs

DigitaltwinsAR/VR&wearables(XR)

GenerativeAI Dataspaces&federatedAIDistributedledgertechnologyAgenticAI

PhysicalAI

Quantumсomputing

0%10%20%30%40%50%60%70%80%90%100%013

NOW(0-2years)●NEAR(3-5years).NEXT(5+years)

Interpretationofthegraph

1.Colouredbars:Theseindicatetheshareofexpectedimpactbyhorizon:NOW(0-2years),NEAR(3-5years),NEXT(5+years).Alargersegmentmeansmoreofthetechnologysimpactisexpectedtomaterializeinthathorizon.

2.Technologyblocks(foundational,orchestrating,autonomous):Theorderoftheseblocksindicatestheramp-upofcapabilityandreadinessgroupedintofoundational,orchestratingandautonomoustechnologies;ithighlightshowfoundationaltechnologiesenablemoreadvanced

capabilitiesovertimeandunlocklonger-termimpact.

3.Cross-functionalslider:Thisrepresentsthenumberofdistinctoperationalfunctions(outof13)forwhichatechnologycreatesmaterialrelevanceinatleastonetheme/usecaseforthatfunction.

7

IntelligentIndustrialOperationsOutlook202612

Keyinsightsforleaders

–Valuecompoundsthroughcapability

layering:Foundationalcapabilitiesenable

orchestrationatscale,andorchestration

enablesautonomy,sosystem-levelimpactcomesfrombuildinganintegratedcapabilitystackratherthanadoptingisolatedpoint

solutions.

–Timingofimpactmatters:Atechnology’sstrategicimportancedependsonwhenit

contributesalongthejourney,notonlyonitsimmediateorlocalbenefits.

–Sequencingoutweighsselection:The

successoftransformationdependslesson

choosingindividual“breakthrough”technologiesandmoreonbuildingcapabilitiesintheright

ordersothatintelligencecanscaleupreliablyandsustainably.

–Impactscalesthroughbreadthofoperationstransformed:Impactgrowsastechnologies

progressfromoptimizingsinglefunctionstotransformingmultiple,endtoendoperationsacrosstheenterprise.

Readingguideforthefollowingchapters

Thenextthreechaptersexaminetheevolution

ofthe13operationalfunctionsintroducedin

Figures3and4acrosstheNOW–NEAR–NEXT

horizonthroughasetof35+cross-cutting

transformationthemes.Eachthemerepresentsa

transformationpathwaywithinafunction,illustratinghowoperationalapproachesevolveovertime

inresponsetoincreasingcomplexity,scaleandshiftingperformanceexpectations.

ThesetransformationpathwaysareexaminedatFactorylevelinChapter2,CompanylevelinChapter3andSupplychainlevelinChapter4.

Toillustratethepotentialimpactofeachtheme,keyperformanceindicators(KPIs)areincludedtoindicatehowperformancemayimproveascapabilitiesevolve.

BOX1

KPIimpactlegend

Foreachtheme,keymetricsandtheirexpectedprogressionovertimeareoutlinedasfollows:

IndicatesincreaseintheKPIvalue

IndicatesdecreaseintheKPIvalue

Representsmagnitudeofimprovement,regardlessofdirection–largerHarveyballsindicate

greaterimpact,whetherfromincreasingametric(e.g.throughput)orreducingit(e.g.downtime).Thisassessmentisqualitativeanddirectional,notapreciseorscientificmeasurement.

2

Factory|Core

Industrialintelligenceisreshaping

factoryoperations,enablingreal-timecoordinationofmachines,people

andmaterials.

DrivenbyadvancesinAI,automationand

connectivity,factoriesareenteringaneweraofintelligent,self-optimizingsystems.Overthenextdecade,operationswillshiftfromlineardiscretefunctionstoorchestratedecosystemswhere

machines,digitalsystemsandpeoplecollaboratecontinuouslyinrealtime.

Decisionswillincreasinglybemadeattheedge:algorithmsanticipatingdisruptions,reconfiguringworkflowsandsynchronizingmaterial,labourand

energyacrosstheentirenetwork.Theywilloptimizenotjustindividualsitesbutcollectiveperformance,whilereducinghigh-effort,repetitiveworkonthe

frontline.

Humanroleswillevolvetowardssupervising

autonomousprocesses,validatinginsightsand

steeringexceptions.Theresultisanewoperationalparadigm:adaptive,resilientandsustainable

factoriesthatcontinuouslyimproveandserveastheintelligencehubsofwiderproductionnetworks.

IntelligentIndustrialOperationsOutlook202613

IntelligentIndustrialOperationsOutlook202614

2.1

Planning

Constrainedbyvolatilityofdemand,inflexible

planningcyclesandfragmentedvisibility,today’splanningapproachesstruggletokeeppacewithrapidchange,leavingfactoriesslowtorespond.Thefutureisintelligentandresilientplanning

–anevolutiontowardsAIandsimulation-first

adaptivesystemsthatlearncontinuously,anticipatedisruptionsandsynchronizedecisionsacrossthevaluechain.

PLANNING

Autonomousandfederatedmulti-agentplanning

THEME1

NEXT(5+years)

NOW(0-2years)NEAR(35years)

AIagentsenableself-healingoperationsbyrebalancing

operationalsignals(e.g.

production,assets,workforce,

energyanddemand)within

factories,whileafederated

networkoffactoriessecurelyco-plansinrealtime,absorbing

shocksandadaptingtochangingdemand.3

Simulation-driven,reactive

—Simulation-basedplanningprovidescross-functionalvisibility.

—Operationalsignalsareusedtoadjustschedulesan