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Introduction

Areyoureadyfor

agenticclockspeed?

Anintroductiontoaseriesontheoperating-model

decisionsagenticAIputsinfrontoflargeenterprises

andtheirITorganizations—andonitstransformationalimpactonlargeITdepartments.

OLIVERWYMAN

AMARSHBUSINESS

Ourpointofview

AgenticAIcreatesanewchallengeforITorganizationstoovercome—

andtocapitalizeon.Itdrasticallycutsthetimeittakestoperformactivitiessuchascoding,testing,anddocumentationthatusedtoabsorbmostof

theworkdonebyITdepartments.Atthesametime,itshrinksthetime

enterpriseshavetoevaluatechangerequests,assessimpact,validate

changes,orreacttoacyberattack."Agenticclockspeed"isthetermfor

howmuchmorequicklyITorganizationsmustnowrun.Becauseagentic

AItoucheseveryITprocess,everythingisaffected.

Closingthatgapmeansrethinkingoperatingmodels,economics,

workforces,andriskcontrols.Capturingitsvaluemeansreengineeringhowworkisdone,beforescalingupagents,andadaptingdatagovernance,

context,andauthoritytothenewenvironment.

◎OliverWyman2

◎OliverWyman3

Twoclocksareoutofsync,andthemarketispickingwinners

ThecenterofgravityinenterpriseAIhasmovedtwiceinfiveyears—fromthemodel'sweights(thechoiceandsizeofmodels),towhatwasfedintothosemodels(promptengineering,

retrieval-augmentedgeneration,andsoon).Now,ithasmovedagaintotheharnessthatturnsamodelintoanagentandtothenumberofthoseagentsabusinesshasrunninginproduction.Eachshifthaschangedwherethemoneygoes,wheretheriskslie,andwhatdifferentiates

companiesfromoneanother.Anyonestillaskingwhichmodeltheyshoulduseisansweringquestionsfromthe2023exam.

Exhibit1:ThecenterofgravityinenterpriseAIhasmovedtwiceinfiveyears—fromweightstocontexttotheharness

Harness&Mesh

Skills,process,agenticmemory,observabilty,guardrails,A2A,

orchestration,MCP...security

Context

PromptingRag,context

engineering,chainofthought.….

Model&Weights

Training,finetuning,

size,scoresGPU...

20222026

Mostoftheprogresssincemid2025hasnotcomefrombettermodelsorprompting,

butwhatdrivesthemodelitselftheharness

ThebottleneckthisshifthascreatedisdelayinghowquicklycompaniescanrolloutagenticAI.Thehardpartistimingbecausethemovingpartsrunonverydifferenttimetables.Afrontier

model'scapabilityrebasesroughlyeverysixmonths,anenterpriseITdecisiontendstoworkforaroundthreetofiveyearsand,whileanattackercanexploitaflawwithinhours,itcanstilltakeweekstodevelopapatch.Runninganenterpriseacrossthatdisconnectiswhatwecallagenticclockspeed.Itisaschedulingproblembeforeitisatechnologicalone.

Thewarningsignsarealreadyvisible.S&PGlobal's2025enterprisesurvey¹foundthat42%

ofcompanieshadabandonedmostoftheirAIinitiativesthatyear,upfrom17%in2024—

withescalatingcosts,unclearbusinessvalue,andinadequateriskcontrolstherecurringcauses.Thesameresearchidentifiesthecomplexityofdeployingagentsatscaleasabarrierto

production.Cigref²reachesasimilarconclusionforlargeorganizations:valuedependsnot

onlyonthetechnology,butalsoonorganizationaltransformation,datagovernance,security,platformfoundations,andchangemanagement.

1S&PGlobalMarketIntelligence,enterpriseAIsurvey,2025:42%ofcompaniesabandonedmostoftheirAIinitiativesduringtheyear,upfrom17%in2024.

2Cigref(associationoflargeFrenchenterprisesandpublicbodiesondigitalmatters),publicationsonagenticAIand

enterprisereadiness,2025-2026.Valuedependsonorganizationaltransformation,datagovernance,security,platformfoundations,andchangemanagement.

https://www.cigref.fr

◎OliverWyman4

Thesefindingsdemonstratethatmodelcapabilitydoesnotonitsowncreatevaluefor

businesses.Cost,value,control,andorganizationalreadinessrepeatedlycomeupassticking

points.Basedonthosesignalsandonourconversationswithexecutives,ourconclusionis

thatcompaniesaredesigningtheiragenticoperatingmodelsaroundtheirbindingconstraints.Theyshouldinsteadbebasedontheenterprise'sabilitytoadaptwhomakesdecisions,

howfundingandcostsarecontrolled,theworkforce,governance,andhowoperatingprocessesruninpractice.Enterprisesthatcannotadaptatthatpacewillkeeppayingforthetechnologywithoutseeingthevaluefromit.

Agenticclockspeed

Themismatchbetweenhowfastagenticsystemsgenerate,act,spend,andfail(months,

minutes,hours)andhowfasttheenterprisedecides,budgets,patches,andcontrols(years,quarters,weeks).Closingthatgapisprimarilyanoperating-modelandcontrolproblem,notamodel-selectionproblem.

What200seniorexecutivestoldus

InJuly2026,OliverWymansurveyed70CEOsandexecutivecommitteemembers,aswellas

130CIOsandCTOsatlargeenterprisesacrossEuropeandNorthAmerica.Weusedtwoparallelquestionnairesonthesamepopulation³.Thefirstpaperoftheseries,What200seniorexecutivestoldusaboutagenticAI(S1),reportsthefindingsinfull.

Ambitionisaligned,butfundingandrealizedvaluearenot.64%ofCEOsexpectatwo-to-

three-yearproductivitygainof11%to20%,andbothsides—unusuallyforatechnologycycle一agreethatthegainwillcomefromchanginghowworkisdoneandbringingdataunder

controlratherthanbuyingtools(61%ofCEOs;72%ofCIOeffortonthelargestinitiativealreadysitsoutsidetooling).Yet48%ofCIOssayITisfundedtodeliveronly1%to10%,andonboth

sidesjust1%ofrespondentssaymostproductivitygainshavereachedtheP&Lasbankablevalue.Bothsidesagreeonthethesis,buttheyhavenotyetbuilttheinfrastructureand

operatingmodelthattranslatesitintoearnings.

CEOs'desiredautonomyoutstripsthereality.83%ofCEOssaytheyarewillingtograntagentsmoderateorhighautonomyonprocessesthattouchcustomers,revenue,orfinancialcontrols,while70%ofCIOsreportagentsinproductionstillcappedatper-stephumanapproval.

Thatmakeshumanverificationcapacity—theleast-fundedinvestmentareaintheCIO

3TheOliverWyman2026ParallelSurveysonCEOsandTechLeadersonAgenticAIandIT,July2026

◎OliverWyman5

sample—thepracticalceilingonscale.Withthatamountofcautionbuiltintotheprocess,thespeedatwhichhumanscheckagenticworkhasbecomethebottleneck.

Confidencerunsaheadoftheevidence.84%ofCEOsratetheirorganization"leading"or

"ontrack"toscalesafely,butonly25%oforganizationsholdatamper-evidentaudittrail,only10%canproduceacompleteagentregistryondemand,andonly21%haveappointedaheadofAIgovernance.Themessagefromthesurvey-andthisseries—isthatbusinessesshouldjudgetheirnextphaseofinvestmentonobservabledeliveryevidenceratherthanexecutiveconfidencealone.Aboardthatrequeststheunderlyingevidencewilllearnquicklywhether

itexists.

100%

50%

Exhibit2:Readinessisuneven:theplatformisaheadofthedata,andthedataisaheadofthecontrols

31%

17%

9%

74%

70%

62%

17%

13%

7%

PlatformDataControls

■NotreadyReadyinpartsLargelyready

Source:TheOliverWyman2026ParallelSurveysonCEOsandTechLeadersonAgenticAIandIT,July2026

◎OliverWyman6

AgenticAIturnstheITteamfromalabormodelintoasupervisionmodel

AgenticAIchangestheroleofITbecauseitmovesAIfrombeingatoolusedbyindividuals

toactingasaco-workeroperatingacrossmulti-stepworkflows.Thehumanrolebecomes

moresenior,fromspendingthemajorityoftheirtimeexecutingtaskstosettingintent,

definingarchitecture,supervisingquality,anddecidingwhennottotrustthemachine.

Thevalueinthisdynamiccomesfromredesigningworkflows,organizingknowledge,

governingdata,andbuildingtheconnectiveinfrastructurethatallowsagentstooperate

atscale—ratherthanjustmakingindividualautomatedactivitiesfaster.Organizationsthatreorganizearoundsupervisionwillcompoundthosegains,whereasthosewhoretrofitagentsontoalabor-modelorganizationwilldiscovertheyhavemerelyautomatedthebacklog.

Thewinnerswillmanagetheirowntransformationinsteadofjustbuyingtoolsandexpectingchange

ThereisastrongproductivitycaseforagenticAI,butuserswillneedflawlessexecutioninordertoreapitsrewards;buyingtoolswillnotyieldsuccessonitsown.Whatanenterprisecanreasonablyexpecttogainismeasuredinarangeratherthananumberpromisedbythevendor.Thatrange

dependsonplatformmaturity,processdiscipline,datareadiness,andchangemanagement.Inourexperienceworkingwithclients,scalingagenticAIistypically80%aboutchangingtheorganization'soperatingmodeland20%aboutthetechnologyitself—buildingtheinternalplatform,simplifyingprocesses,definingautonomyandaccountability,investinginsupervisionskills,andmeasuring

valueagainstbusinessoutcomes.Companiesthatpreparewiththosecriteriainmindwillconvertagentsintoalastingadvantage.ThosethattreatagenticAIasanewtoolwillreceivefasteroutput,butitwillcomewithmoreinstability,uncontrolledcost,andlimitedvalue.

LargeITprogramsfailonmanagementfarmoreoftenthantheydoontechnology,soagenticAI

mustberunasagenuinetransformation.Thatmeansshapingtheoperatingmodelfirst:decidinghowagenticAIwillbedelivered;segmentingtheestatebyvalueandreadiness;andagreeingon

sourcing—ratherthanretrofittingitoncetheagentsarealreadyinplace.Italsomeansbuildingtheplatformintherightorder:fundingtheconnectiveharnessbeforethewidermesh,andunlockingindividualdomainsbeforescalingacrossthemenmasse.Anditmeansachievingbuy-infromthe

organizationatlargebyshowinghowthenewtechnologyworkswithworkingoutputratherthanslides,runningtrainingsessions,andgettingmiddlemanagementonboardearlyintheprocess.

Allofthatisbecausepeople,andnotmodels,willdecidewhetherimplementingagenticAIissuccessful.

◎OliverWyman7

Whenthepriceofintelligencedrops,theadvantagemovestowhatonlyyouown

Frontiermodelsareconvergingincapabilityandfallingsharplyinprice,sotheadvantages

businessescangainbyrentingthebestmodelarediminishing.Lastingadvantagesaremoving

tothestrengthsacompetitorcannotrentofftheshelf:acompany'sproprietarydataandcontext,itsreengineeredprocesses,andthedisciplinetorunagentsatscale.Oursurveyrespondents

alreadyseethingsthisway.Whenaskedwherelong-termadvantageswillsit,CEOspointto

reengineeredprocessesandtheoperatingmodel(74%),aswellasproprietarydataandcustomerknowledge(64%),whileprivilegedaccesstoaleadingmodelorvendorbarelyregisters,at4%.4

Cognitivework-analysis,drafting,synthesis,code—isbecomingacommodity.Butasthat

workbecomesabundant,scarcityshiftstowhatcognitiveworkdoesnotcoverandtothe

institutionalknow-howthatcompoundsovertimeandishardtocopy.⁵Inotherwords一

judgment.ThatisalsowhyAIamplifiesdifferencesbetweenbusinessesratherthansmoothingthemout:Awell-runfirmwilluseagenticAIinsideadisciplinedoperatingmodelbetterthana

poorlyrunfirmwilluseitwithoutone.6Theempiricalsignalpointsthesameway,withacaveat.Microsoft's2026WorkTrendIndexattributesroughlytwo-thirdsofAI'smeasuredimpactto

organizationalfactorsratherthanindividualuse,andplacesonlyaboutafifthofusersinthe

"frontier"zoneofcompaniesthathaveredesignedtheirworkflowsaroundit.AsaCopilotvendor,Microsoftisaninterestedparty,soreadthisasdirectionalratherthanobjective.

Forexecutives,thischangesthequestionsfrom"Whichmodel"or"Whichvendor?"to"Which

layerdoweown?"and"Canwerunitbetterandfasterthanourcompetitors?"Theoldproductmoatserodefrombothsides:proprietarycodematterslessbecauseproducingitisnowcheap,andexclusiveaccesstoaleadingcapabilityisalsolessimportantbecausecheapermodelstendtocatchupwithinayearortwo.Butproprietarydata,agenticintegration,andhowthebusinessitselfisrunareallstillworthdefending.Thatiswhytheoperatingmodel,andnotthemodel

itself,isthesubjectofthisseries.

4TheOliverWyman2026ParallelSurveysonCEOsandTechLeadersonAgenticAIandIT,July2026.

5Y.Caseau,2026,drawingonL.AlexandreandO.Babeau:itiscognitiveworkthatcommoditizes,notjudgment;thescarceassetshiftstowhatabundantinteligencedoesnotcover.YvesCaseau,"TransformationdelasociétéetdutravailparlarévolutionpermanentedeI'A,"ArchitectureOrganisationnelleblog,February24,2026.

6DORA(DevOpsResearchandAssessment),StateofAl-assistedSoftwareDevelopment,2025;reported.AIdescribedasanamplifierofexistingorganizationalstrengthsandweaknesses.

https://dora.dev/research/2025/dora-report

7Microsoft

,

2026

WorkTrendIndexAnnualReport:Agents,humanagency,andtheopportunityforeveryorganization,publishedMay5,2026(fieldworkFebruary-April2026;20,000knowledgeworkersacross10countries);reported.Roughlytwo-thirdsofA'smeasuredimpactcorrelateswithorganizationalfactorsversusroughlyone-thirdindividual;about199%ofuserssitinthe

"frontier"zone.Vendorsource(MicrosoftsellsCopilot);treatasdirectional,notindependent.

/en-us/

worklab/work-trend-index

◎OliverWyman8

Agenticclockspeedisanoperatingmodelchallenge

Pivotingtoagenticclockspeedtouchesfivediscreteareas:wherevaluesits,thecostbase,theplatform,theworkforce,andtheriskclock.EachoneoverturnsanassumptionlargeITorganizationswerebuilton.

Exhibit3:AgenticAIoverturnsfiveassumptionslargeITorganizationswerebuiltonDimensionThebasisITwasbuiltonThebasisatagenticclockspeed

Wherevaluesits

Automatingtasks(tools,"RPA2.0")

Reengineeringthesystemandgoverningthedataandthememory

Thecostbase

Fixed,licensed,predictable(perseat)

Variable,metered,endogenous

(pertoken,setatruntime)

Theplatform

Procured,thenscaled

Sequenced—harness,portfolio,mesh一governedfromweekone

Theworkforce

Headcountproducingartifacts

Supervised,blendedhuman-plus-agentteams

Theriskclock

Patchandcontrolcyclesinweeks

Exploitandincidentcyclesinhours

Source:OliveWymananalysis,synthesizingthechaptersofthisseries.

Thesamespeedthatmakesagentseconomicallyattractivealsoexposesandmagnifiesweakprocesses.Afastergenerationlayerdoesnotcreatemorebusinessvaluewhenrequirementsareambiguous,verificationcapacityisflat,costsareunbounded,oraccountabilityisdiffuse.Itjustproducesmoreoutputagainstthesamebottlenecks.

Atagenticclockspeed,thehumanrolebecomesmoresenior.Peoplesetintent,definearchitectureandqualitybars,adjudicateexceptions,anddecidewherenottotrustthemachine.ITbeginstomovefromalabormodeltowardasupervisionmodel.

◎OliverWyman9

Theseriesataglance

ThisOliverWymanAgenticClockSpeedseriessetsouttheperspectiveanddecisiononthe

tableforexecutiveteamsrebasingtheiroperatingmodelstotheagenticclock.ItopenswiththesurveynoteWhat200seniorexecutivestoldusaboutagenticAI(S1),whichprovidestheevidencebase,continueswiththisintroduction,andthentakeseachofsixquestionsapartacross

deep-divepapers.Eachpaperanswersitsquestiontothesamestandardthesurveynoteapplies:observableartifactsoverstatedconfidence,andmechanismsoverambition.

S1-evidencebaseCO-commonframe~10Decisiondeepdives

What200seniorexecutivestoldusaboutagenticAI

Quantifiesthegapsinfunding,autonomy,governance,workforce

ownership,andvalueconversion

Areyoureadyforagenticclockspeed?

Definesthesixquestions,fivematuritydimensions,andcommonautonomyscale

usedacrosstheseries

Focusedperspectivesoneachofthesixquestions

Translateeachchallengeintoexecutivedecisions,requiredartifacts,anda

practicaloperatingmodelchangeagenda

Exhibit4:Thesixquestionstheseriesanswersandthedecisioneachputsonthetable

ThesixquestionsThedecisiononthetableSubjects

1.WhychangeyourIT

RunagenticAIasatoolingprogram,orasan

·What200seniorexecutivestoldus

operatingmodelsnowforagenticAI?

operating-modelrewrite?Thegainappearsonlyiftheoperatingmodelcanletit.

·Areyoureadyforagenticclockspeed?

·Youcan'tbuyyourwaytoagenticAI

2.Whatstrategicdecisions

Howdowebuildtheplatformwithoutbuying

·WhatisascalableagenticAIplatform?

matterwhenscalingagenticAI?

aheadofneed—andwhichlayerofdependency,andwhichartifacts,dowekeepportable?

·Howtomanagestrategicdependencyinyourplatform?

3.HowshouldITdelivery

Howfarupthechain—fromintenttobuildtorun

·Requirementsandintent:whencodeis

adapttoreapagentic

—doweletagentsact,andhowmuchauthoritydo

cheap,thebriefistheasset

AIbenefits?

wetransfer?

·AI-SDLC:canwemakeagenticengineeringreliable?

4.Howcanyouprepare

Whatchangesinwhatwebuyversusbuild,

·Buyvs.build:Modernizingtheapplication

workforcesandapplications

whicharchitecturemovescomefirst,howweuse

landscapeforagenticAI

foragentic?

agenticAItoaccelerateapplication-landscapemodernization—andhowdowerecomposetheworkforceratherthanshrinkit?

·TheimpactofAIonITtalent

5.Whatisthebeststrategy

Whataccountability,run-time,andcost-control

·AgenticgovernanceofIT

togovernandfund

layersmustITstandupbeforescaling—andhow

·Runningtheagenticestate

agenticAI?

dowebudgetavariable,endogenousbill?

·TheeconomicsofagenticAI

6.Howdoyousecureandsucceedat

AItransformation?

Runthechangeasareal,sequenced

transformation—in"seasons"—notatoolingrollout;reviewtheorganizationandoperatingmodelbystagetoscaleandoptimizevalue.

·TheagenticITorganization

·TheplatformoperatingmodelforagenticIT

·RebuildingtheITfunctionforAI

OliverWyman.Chaptertitlesandsequencingareindicativeandmayevolveastheseriesispublished.

◎OliverWyman10

Fiverulestogovernyourjourney

1.Theresultsdependonyou—createtheconditionsandmeasurethemagainstyourownpipeline.IndependentstudiesandOliverWyman'sownonesdemonstratethatawiderangeofimpact,thematurityofthebusinessmodel,andhowwellitfitstotheagenticworld,mattermorethanindividualcodinggains.8

2.Buildaproperagenticplatformfoundation,intherightorder.Buildoneharness

aroundasingleworkflowthatpaysforitself,thenaportfolio,thenamesh.Tryingtobuildthewholemeshfirstbuysgovernancenooneuses;andneverbroadeningtoameshwillproduceafleetofagentsnoonecananswerfor.Buildthefoundationbeforescalingup,oryouwillgetdisorderatspeed.

3.Governfromweekone,andmakeaccountabilityandliabilityexplicit.Thequestionsmostprogramsavoid—"Whoisliablewhenanagentacts?"and"Whobearsthecost?"—shouldbeincorporatedintothedesignfromtheverybeginning.

4.Bewareofstrategicdependencies,andcontrolkeyassets(skills,procedures,memory).Ifbusinessescannotsimplyexplainwhichartifactsstayundertheircontrolifaprimary

supplierweretodoubleitspricesin12months,thatisanunmanageddependency.

Oursurveyshowedthatonly10%ofCIOscouldproduceasignedversionofthatoner.

5.Managethejuniortalentpipelineasadeliberatedecision,notadefault.Prioritizearchitecturaljudgmentandknowingwhennottotrustagent-writtencode—judgmentcannotbeoutsourced.

8GitHubCopilotrandomizedcontrolledtrial(55.8%task-completionspeed-up;reported):S.Peng,E.Kalliamvakou,P.Cihon,andM.Demirer,"TheImpactofAIonDeveloperProductivity:EvidencefromGitHubCopilot,"2023,

/

abs/2302.06590.METR

,

2025

(

experienced

open-sourcedevelopersmeasuredslowerwithAIassistanceinacontrolledsetting;reported),

◎OliverWyman11

Acommonnotionofautonomyacrosstheseries

Theseriesusesonescaletomakeautonomyexplicitandcomparable.Itdescribeshowmuch

ofaworkflowisperformedbypeopleversusagents:A1fullyhuman,A2human-led,A3human-assisted(copilots),A4supervisedautonomy(end-to-endstepsrunautonomously,humansontheloop),A5AI-dominated,A6fullyAI.MostenterprisevaluetodaysitsatA3toA4—consistentwiththesurvey,where70%ofCIOsreportproductionagentscappedatper-stepapproval.9

Autonomyisaper-workflowchoice,notablanketsetting;thesamerolecanbeA4foronetaskandA2foranother,and96%ofsurveyedCIOsalreadysetitperworkflow.

Exhibit5:Theseriesautonomyscale(A1-A6)—mostenterprisevaluetodaysitsatA3toA4Mostenterprisevaluetoday

Human

A1

Fullyhuman

A2

Human-led

A3

Human-assisted

A4

Supervisedautonomy

A5

AI-dominated

OAgent

A6

FullyAI

aper-workflowchoice—thesamerolecanbeA4foronetaskandA2foranother.

Source:OiveWyman.

Thewindowisopennow

waitingdoesnotreducetherisks

AgenticAIrepresentsarealshiftand,atenterprisescale,adeeptransformation.Thebesttimetosettheoperatingmodelisnow.Butthewindowisclosingasagentsmovetowardproduction,becausetheinputscompaniesneedwillnotbearoundforever.Theyincludethepeoplewho

stillunderstandtheoldcoresystems,thebaselinebusinesseshavenotyetmeasured,andthesuppliertermstheyhavenotyetnegotiated.Rebuildhowtheoperatingmodel,economics,

controls,andworkforceoperateatthisnewspeedbeforescalingup.Retrofittingthem

afterwardisexpensiveandinefficient,andit'salsothepathmostcommonlychosen.The

companiesthatwintheracetoclosethegapbetweenconfidenceandevidencewillsetthepaceatwhicheveryoneelseneedstorunjusttokeepup.

9TheOliverWyman2026ParallelSurveysonCEOsandTechLeadersonAgenticAIandIT,July2026.

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