IBMInstituteforBusinessValue|ResearchBrief

ScalingsupplychainresiliencewithAI

AgenticAIforautonomousoperations

A

HowIBMcanhelp

IBMhasbeenprovidingexpertisetohelporganizationswin

inthemarketplaceformorethanacentury.Clientscanrealize

thepotentialofAI,analytics,anddatausingIBM’sdeepindustry,functional,andtechnicalexpertise;enterprise-gradetechnologysolutions;andscience-basedresearchinnovations.Formore

informationaboutAIservicesfromIBMConsulting,visit

/services/artificial-intelligence

HowAccelalphacanhelp

Accelalphaimplements,integrates,andmanagesOracleCloud

Applications.Wehelpsolvebusinessproblemswithsupplychainandlogisticsprocesses,procurement,customers’buying

experience,andenterprise-widefinancialplanningandreporting.

Weprovidechangemanagementtostreamlinebusinessprocessessuchasordertocash,procuretopay,andfinancialconsolidation

andclose.Formoreinformation,visit

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ScalingsupplychainresiliencewithAI2

ScalingsupplychainresiliencewithAI3

Keytakeaways

AgenticAIissuperchargingsupplychainautomation,acceleratingprocessefficiencyfasterthanhumanlypossible,andtakinggrowthtothenextlevel.

AI-enabledsupplychainsdrivevalue.

OrganizationswithhigherAIinvestmentinsupplychainoperationsreport

revenuegrowth61%greaterthantheirpeers.

ExecutivesseeagenticAIasabusinessaccelerator.

62%ofsupplychainleaders

recognizethatAIagentsembedded

intooperationalworkflowsacceleratespeedtoaction,hasteningdecision-making,recommendations,and

communications.

AIautomationishappeningfasterthanyouthink.

70%ofexecutivesstatethatby2026,theiremployeeswillbeabletodrill

deeperintoanalyticstosupport

real-timeanalysisandoptimization

asAIagentsautomateoperational

processes,especiallyinprocurementanddynamicsourcing.

ProcessefficiencygetsanAIboost.

76%ofCSCOssaytheiroverallprocessefficiencywillbeimprovedbyAIagentsthatperformrepetitive,impact-basedtasksatafasterpacethanpeoplecan.

ScalingsupplychainresiliencewithAI4

Introduction

AI-poweredpredictability

andagility—forcemultipliersforsupplychainresilience

Whataresupplychainleadersworriedaboutin2025?Ournewsurveyshows

thatgeopoliticalrisks(61%)andglobaltradetensions(58%)aretheirtoptwo

challenges.Maybeit’snosurprisethattheyareconcernedaboutcontinuing

shockstotheirsupplychains.Eventsinthefirstfewmonthsof2025suggesttheseconcernsaboutdisruptiontotheglobaleconomyandtradearewell-founded.

Butwhatiftheseshockscouldbepreparedfor—withalevelofaccuracyandresilience—thatnotonlydeflectsdisruptionbutactuallycreates

acompetitiveedge?

Turninguncertaintyintoabusinessadvantage

WithAIsolutionsrunningoncloudandembeddedintoenterpriseresource

planning(ERP)platforms,supplychainexecutivesarebetterequippedthanevertoreplaceambiguitywithclarity.Andnext-waveagenticAIcapabilitiesareenablingamuchmoreproactiveoperationalposturethatcombinesgreatercostefficiencieswithmoreagilitytodrivebetterresults.OrganizationsthatseizetheagenticAI

opportunitynowcanmovebeyonddisruptionmanagementandrecastsupplychainoperationsasanengineforgrowth,differentiation,andinnovation.

ScalingsupplychainresiliencewithAI5

EmbeddingAIinto

supplychainoperationsdrivesbusinessvalue

TolearnhowAIisimpactingsupplychainoperations,theIBMInstitutefor

BusinessValue(IBV),inpartnershipwithOxfordEconomics,surveyedmore

than300globalChiefSupplyChainOfficers(CSCOs)andChiefOperationsOfficers(COOs)fromorganizationsimplementingAI-enabledautomation.

Thisresearchbriefshowshoworganizationsaremovingthroughacontinuumofprogressivelygreatercapabilities,builtonAI.

ItstartswithAIprocessautomationandmachinelearning;advancingto

generativeAIinsupplychainworkflows,deliveredbyassistants;and

evolvingintoagenticAI-enabledsupplychainsthatoperateautonomouslyandadaptdynamicallyinrealtimetoreal-worldevents.

ScalingsupplychainresiliencewithAI6

Perspective

Assupplychainoperationsoptimizeworkflows,automate

processes,andsupportgreatercollaborationbetweenAItools

andsupplychainprofessionals,theflywheelofinnovationbeginstospinfaster—infusingnewideas,streamliningbusiness

operationsandreinventingprocessestoenhancecustomer,

partner,andemployeeexperienceswhileharnessingnewrevenueandsupplychainperformanceopportunities.Infact,organizationswithhigherinvestmentinAIforsupplychainoperationsachieve

a61%revenuegrowthpremiumovertheirpeers.

FromAIassistantsto

agenticAI:TheevolutionofAI-poweredautonomy

AIjourneysbeginwithrules-basedsystems,enablingroboticprocessautomation

(RPA)tohandlerepetitivetasksandAIassistantstorespondtoqueries.Assistantsaremakingtheirmarkonbusinessproductivity—especiallyincustomerservice,coding,

andcontentcreation—buttheirquery-basedframeworkslimitcontributionstoworkflowautomationandautonomy.

Overhalfofsupplychain

leaders(53%)areenablingautonomousautomationofintelligentworkflowsvia

self-sufficientAIagents.

AgenticAIbreaksthroughtheselimitationsbyworkingproactivelyandautonomouslytoexecutecomplex,multistepprocesses.AtthecoreofagenticAIarelargelanguagemodelsandfit-for-purposesmalllanguagemodels.Forsupplychains,smalllanguagemodelsmightbespecifictointegratedplanning,globaltrademanagement,supplier

contractnegotiation,ordynamiclogistics.Pairingautonomywithaction,agenticAI

restructuresandoptimizesworkflows,eliminatesunnecessarysteps,andacceleratesdecision-makingtounparalleledlevels(seeFigure1).

SupplychainleadersaredeployingagenticAIrapidlytoattainthesebenefits.Currently,53%ofsupplychainexecutivesareenablingautonomousautomationofintelligent

workflowsviaself-sufficientAIagents,with22%developingtheirproofofconceptand31%alreadyexecutingandscalingproofsofconcept.

ScalingsupplychainresiliencewithAI7

Figure1

AIbenefitssupplychainoperationsatvariouslevelsofmaturity,butagenticAIhastransformativepotential

Typeofimpact

Supplychainexample

Basic

automation

Automatehigh-volume,repetitivetasks.

Integrateorderprocessing,invoicematching,and

shippingnoti?cations.

AI-enabledautomation

Augmentworkforcecapabilities.

Predictivelymonitor

equipmentperformancetopreventbreakdowns.

Interconnectedandintelligentworkflows

ScaleexpertiseandreachwithAIassistants.

IntegrateworkflowswithAIassistantstogivereal-time,personalizedresponsestotransactionalinquiries.

AgenticAI

andautonomy

Orchestrateandexecuteworkflowsautonomously.

UseAIagentstoanalyze

marketconditionsandsales&operationsdatatoadjustproductpricesinrealtime.

ScalingsupplychainresiliencewithAI8

AIassistants:

Lynchpinsofintelligentsupplychainoperations

Forsmarterandfasterdecision-making,supplychainsmusttapintovastamountsofdisconnecteddata.Historically,thishasbeenasignificant

challenge.Butnow,criticalinsightsfromoperationaldatacanbesurfacedrapidly—andmoreeasilythanever—whenthecapabilitiesofemployees

areenhancedbyAI-powereddigitalassistants.

SynergybetweenpeopleandAItouchesvirtuallyeverysupplychainlink,fromplanningandsourcingtomanufacturinganddistribution.Infact,

70%ofCSCOssaygenAIhasenhancedtheirresponsivenessand

communicationswithcustomers.And55%oforganizationssaygenAIvalidatesandaggregatesinformationreliablyforemployees.Thatfigurerisesto69%fororganizationsmakinghigherAIinvestmentsinsupply

chainoperations.

AsexecutivesexperimentwithandoptimizegenAI’sapplicationinsupply

chainoperations,theyfindthatsomeareasbenefitmorethanothers.Today,theyreportthatoperationalperformance(67%)isthetopbenefitfrom

investingingenAI,whilepredictabilityandresponsivenesstooperationaldisruptions(60%)rankssecond.

Forexample,alargeglobalmanufacturerisseeingsignificantimprovementsintradecomplianceandlogisticsoperationsbyusingaglobaltrademanagementsolution,embeddedwithAI.Automatedcustomsdeclarationsforimports

replacemanualprocessesandreducethetimetoclearcustoms.And

AI-poweredupdatesaddnewcapabilities,suchasauser-configurableplatformthatcanprovidetradeincentiveprocessingreliefandreporting.1

ThosemakinglargerAIinvestmentsinsupplychainoperationsseeadditionalcapabilitieswithinreach.Forexample,executivesinleadingorganizationssaythatgenAIwillenableimprovedsupplychainmanagement68%more

frequentlythanpeers.TheyalsoexpectgenAI-enabledvisualizationand

simulationtouncoverbottlenecksinrealtime61%morefrequently;andtheyanticipategenAIwillaccelerateinnovationforsupplychainproductdesign

36%morefrequently.

AgenticAIoperatingmodels

proactivelyrespondto

disruptions,makeforecasts

moreaccurately,andprovidegreatervisibilityacrosssupplychainecosystems.

ScalingsupplychainresiliencewithAI9

ScalingsupplychainresiliencewithAI10

Buildingautonomousadvantage:TheagenticAIoperatingmodelforsupplychains

Whetheritisdisruptiontoglobaltrade,climate-relatedevents,geopolitical

conflict,inflationorsystemiccomplexity,supplychainexecutivesare

accountableforfindingworkarounds.74%oftheseleaderssaygenAIenablesbettervisibility,insights,anddecision-makingacrossecosystems.Togo

further,theseleadersareturningtoagenticAIsolutionstoactautonomouslyonthoseinsightstohelpmakeoperationsmoreagile,adaptive,andresilient.

Now,forthefirsttime,maturityinagenticAItechnologyenablessupplychainorganizationstobuildacomprehensiveagenticAIoperatingmodel(seeFigure2).Configuredtomeetthedynamic,data-driven,andcomplexrequirements

ofsupplychainoperations,thismodelrepresentsanewwayforsupplychainleaderstoachieveoperationalresilience,notonlyinsidetheirown

organizationsbutacrossentirepartnerecosystems.

ThereasonagenticAIoperatingmodelcapabilitiesextendbeyondAI

automationandassistanceisfundamental—thesemodelsarepoweredby

muchmoredatafrommanymoresources.AgenticAImodelsstartwith

operationaldatafromERPapplicationsandfit-for-purposesupplychainapps.Theyalsoincludeagent-to-agentinterfaceswithecosystempartnersandtapintoexternaldatasources,suchasweatherreports,marketindexes,and

geopoliticalevents.

ScalingsupplychainresiliencewithAI11

Figure2

AgenticAIsupplychainoperatingmodel

Supplychainandenterpriseapplications

ERP.CRM.Integratedplanning.SLM?t-for

purposemodels.Legacysystems,EnterpriseandecosystemAPIs.

Agenticautomation

Ecosystempartnersystems

ERP.Transportationmanagementsystem(TMS),Warehousemanagementsystem,(WMS)Inventorymanagement.

Dataintegrationengine

Predictiveanalytics

andoptimizationengine

Impactevaluation

Externaldata

Feedbackloopand

decision-supportanalyzer

Sensors:Manufacturing,transportation,

environmental,security,weather,economicindices,markettrends,geopoliticalevents.

Riskanalyzer

Machine-humancollaborator

Integratedplanning

Predictivedemandandsupplyplanning–analyzingexternalfactorsandcurrentconditions.

Global.Enterprisewide+Ecosystempartner’ssystems.Agenttoagent.

Procurementoptimization

Dynamicsourcinginreal-timebasedonchangingmarketconditions,demand,suppliercapacity.

Supplierriskmitigationanalysisandstrategies.

Inventoryoptimization

AutomaticreplenishmentactionsacrossallinventorytypesandSKUswithsensorandlocationtracking.

Inventorybalancingbaseduponreal-timevariabilities.

Productionoptimization

Intelligentyieldpredictionwithvariableanalysisofresources,assetsandenvironmentfactors.

Rawmaterialand?nishedgoodsplantandful?llmentallocation.

Logisticsoptimization

Transportationoptimizationwithdynamicre-routingbasedontraf?c,weather,and

customersegmentation.

Roboticsandautomatedguidedvehiclesfordistributionactivities.

Customerand?eldserviceautomation

24/7customerand?eldservicesresponsivenesswithpersonalizedcustomerexperiences.

Aggregatedcustomerfeedbackanalysisfrommultiplechannels.

ScalingsupplychainresiliencewithAI12

AgenticAIoperatingmodelsproactivelyrespondtodisruptions,makeforecastsmoreaccurately,andprovidegreatervisibility

acrosssupplychainecosystems.

Forexample,autonomousagentsworkingwithinthe

agenticAIoperatingmodelcanperformcoresupplychainassignmentssuchasadaptingtochangingmarket

conditions,reroutingshipments,negotiatingwith

suppliers,andmitigatingrisksinrealtime—allwithoutdependingonpeopletomakedecisionsormanually

intervene.InitialanalysisintoagenticAIdeploymentpointstostrongusageontasksrelatedtodynamic

sourcinginprocurementworkflows,basedonmarketdemandandsuppliercapability.

Allthiscanfreeupmoretimeforpeopletoworkonstrategicdevelopmentandcustomerrelationships.AndtheseexamplesarejustastartasorganizationslearnmoreaboutwhatagenticAIcandointheir

operationalenvironments.

Poweredbyadataintegrationengineandinteracting

directlywithsupplychainsystems,agenticautomationprovidestoolsforpredictiveanalytics,workflow

optimization,impactevaluation,riskanalysis,

anddecisionsupport.Agenticautomationalsorelies

onclosecollaborationbetweenpeopleandtheirdigitaltools,aswellasamongteammembersworkingacrossorganizationsandpartnerecosystems.

ScalingsupplychainresiliencewithAI13

Inasupplychainenvironment,anagenticAIoperatingmodelanalyzescurrent

conditionsandexternalfactorsintegratingdemandpredictionandsupplyplanning.Themodeloptimizesprocurementthroughreal-timedynamicsourcing,basedonchangingmarketconditions,andoptimizesinventoryacrossSKUswithsensorandlocation

tracking.Andwhenitcomestooptimizingproduction,anagenticAIoperatingmodelpredictsyieldswhileanalyzingresources,assets,andenvironmentalfactors.

Inthelogisticsspace,theagenticAIoperatingmodeloptimizestransportationwithdynamicreroutingbasedontrafficandweatherconditionsandcustomersegments.Andforcustomerandfieldserviceautomation,themodelaggregatescustomer

feedbackandrespondswithpersonalizedcustomerexperiences.

OneofthekeyattributesofanagenticAIoperatingmodelforsupplychainsisits

flexibility.Theseframeworkscanbeseamlesslyintegratedwithexistinganalyticstools,suchasinventoryandtransportationmanagementsystems,potentiallymakingan

immediateimpactonoverallsupplychainperformance.

By2026,57%ofexecutivesexpectagenticAIwillmakeproactiverecommendationsbasedonwhatitlearns,and62%expectAIagentswillmakesupplychainprocess

automationandworkflowreinventioneffortsmoreeffective.Additionally,76%ofCSCOssaytheiroverallprocessefficiencywillbeimprovedbyagentsthatperformrepetitive,impact-basedtasksfasterthanhumanscan.

EmployeesworkingwithagenticAIwillbemoreinvolvedthanevertohelpensuresafe,responsible,andaccuratesupplychainoperations.Andforthisinvolvementtobe

successful,eachemployeemustbeheldaccountableandbedeeplyinvolvedin

orchestratingagenticAIoutcomes.AsAIagentsarewoventighterintosupplychain

workflows,theirlevelofautonomyshouldbecloselymonitoredbypeopleandadjustedasneeded.

AssupplychainsseekdifferentiatedoutcomesfromagenticAI,they’llneedtobalanceinnovation,speed,andgovernancetodrivegreaterconsistencyinthevaluecapturedby

improvedworkflows.Understandinghowthemodelcandelivervaluestartswithreal-timevisualizationofanagenticAIoperatingmodelacrossalldimensions.

Visualizingoperationsbeginswithlookingathowdataflowsintoaplatform—typicallythroughanERPsystem—withageospatial,informational,andanorchestration

analyzer.Next,agenticAI-enabledvirtualmodelssimulatehowspecificeventscould

impactsupplychainoperations.Agentsevaluatedifferentscenariosandmodel

potentialproblemsthatmightresult—suchasglobaltradeimbalances,costspikes,andmaterialshortages—andgenerateplanstomitigatedisruptions.

Withperspectivesprovidedbyproactivesimulations,supplychainleaderscanpivotquicklytomakebetterdecisions,capitalizeonemergingopportunities,andshare

insightsquicklyacrosssupplierecosystemstoscaleinnovation(seeFigure3).

ScalingsupplychainresiliencewithAI14

Figure3

AgenticAIacceleratesinnovation

Innovation

AIagentsautonomouslyexecuteinterconnected

supplychainworkflows

acrossecosystems.

Action

Fliptheagenticpropositionfromreactiontopro-actiontodrivenewopportunitiesforgrowth.

Evaluation

Agenticmodelsevaluate

scenariostoanticipate

problemsandgenerateplanstomitigatedisruptions.

Simulation

AgenticAI-enabledvirtualmodelssimulatereal-worldeventimpactsonsupply

chainoperations.

ScalingsupplychainresiliencewithAI15

Actionguide

Bytappingintoindustry-specificdatageneratedbyERPplatforms,CSCOscanuse

genAIassistantsandAIagentstodevelopnewbusinessstrategies,streamline

productdevelopment,andoptimizeglobaloperations.Asmultiagentsanalyze

historicaldataandcurrenttrendstopredictfutureoutcomes,theseAI-informed

resourcescananticipatedemand,managerisksbetter,andplaninventorymore

effectively.Inaddition,theautonomouscapabilitiesofagenticAIenablecontinuousself-adjustmentbasedonreal-timedata,helpingtoensurethatsupplychainscan

swiftlyadapttounexpectedevents.

TheagenticAItrainispickingupspeed—63%ofCSCOssaythatbynextyear,AIagentswillcontinuouslyimprovesupplychainperformancebymakingfeedback-based

adjustments.Butbewareoftherisks:executivesciteconcernsarounddataaccuracyorbias(72%)anddatasecurityandprivacy(63%)asthetopchallengesforgenAIinsupplychainoperations.

ScalingsupplychainresiliencewithAI16

GetseriousaboutdevelopinganagenticAIoperatingmodelforyoursupplychain.

–EvaluatecurrentoperationstofindoutwhereagenticAI

canbringthemostvalue.Identifyyourchallengeswithdata,

workforcere-skillingandgovernancemodels.ClearlyarticulatethebusinessimpactyouaimtoachieveanddevelopKPIsandothermeasurementstotrackprogressagainstyourgoals.

–Assembleadiverseteamincludingdatascientists,supply

chainexperts,ITprofessionals,andotherdepartmental

leaders.MakethemresponsiblefordesigningandimplementingyouragenticAIoperatingmodel.Startsmallwithproofsof

concept,trackprogress,andscalequicklytodeployagenticAIsolutionsacrossyoursupplychain.

–Focusonautonomy,granularity,networkresilience,intelligentinterfaces,transparency,andcollaboration.Integrateethics

intotheAIoperatingmodeltosupportsupplychainpracticesthatarefair,transparent,andsociallyresponsible,andbuildbrandreputationandtrustwithcustomersandstakeholders.

EmpowersupplychainoperationswithagenticAI.

–EstablishKPIsforyourAIagentsandassignyourpeople

tomonitortheirperformance.Empoweryourpeopletoset

workflowoptimizationgoalsforAIagents,basedonbusiness

impact.Also,putyourpeopleinchargeofcontinuously

evaluatinghowwellAIagentsaremeetingpreassignedbusinessgoals.LeverageobjectivelysuccessfulagenticAIapplicationsasablueprintforfurtherinnovationinsupplychainactivities.

–Deployagentsthroughoutyourecosystemtoamplifyimpact

andreducecost.ImplementAIagentoperatingtasksacross

thespectrumofsupplychainworkflows—especiallythose

representedbyyourglobalpartners.MaphowyourAIagents

willworktogethertooptimizeexistingworkflows,createnew

workflows,andextendpartnercommunications—allinrealtime.EngagewithecosystempartnerstomutuallyassessandsupporteachotherinpursuitofagenticAIcapabilitiesthatgobeyond

thewallsofyourownenterprise.

–Taskagentstotransformdatafromroadblocktoaccelerator.

UseAIagentstoexplore,create,andtesthypotheticalwhat-

ifscenariosderivedfromextensiveproprietarydataand

organizationalexperience.Empoweragentstoautonomously

orchestrateactionsrequiredtoprepareforthemostimpactfulandlikelyscenarios.Developmechanismstomeasurethevalueofagentic-leddisruptionavoidancetosetabenchmarkfor

continuousagentimprovement.

ScalingsupplychainresiliencewithAI17

Authors

GeraldJackson

VicePresident,SCSolutionsStrategyandInnovation,Oracle

/in/gerald-jackson-8377831/

gerald.jackson@

Gerald’scareerfocusistohelpclientsunlockthefullpotentialofsupplychains

throughadvancedtechnology,data,humanenablement,andseamlessintegrationacrossfunctionalprocesses.HesharestheOraclevisiontoharnessthepowerof

moderntechnologyandrethinkcustomersupplychainstobesmarter,moresustainable,productive,andresilient.

ChiPark

SeniorSolutionsDirector,SupplyChangeManagement,Accelalpha

/in/chi-park/

chi.park@

Chiisasupplychainindustryveteranwith18yearsextensiveknowledgeofOracle

ERPandSupplyChainManagementapplicationsrangingfromsalesandoperations

planning,constraint-basedsupplychainanddistributionrequirementsplanning,

finiteproductionscheduling,discreteandprocessmanufacturing,ordermanagement,inventorymanagement,productlifecyclemanagement,andprocurement.Hispurposeisadvisingclientsinelevatingextendedsupplychainstothenextmaturitylevels,

includingAIautomations.

PushpinderSingh

Partner,GlobalSupplyChainTransformationLeader,IBMConsulting

/in/pushpindersingh/

p

ushpinder.singh@

Pushpinderpartnerswithleadingorganizationsworldwidetoacceleratetheirsupplychainperformance.Asastrategicadvisor,hebringsover24yearsofexperience,

drivingimpactfulchangeandlong-termvaluecreationforthenextgenerationof

supplychainleaders.Heispassionateaboutleveragingtechnologytosolvecomplexsupplychainchallenges.

KarenButner

GlobalResearchLeader,SupplyChainAIAutomation,IBMInstituteforBusinessValue

/in/karenvbutner/

kbutner@

Karenisresponsibleformarketinsights,trends,andleading