bcg -人工智能领跑者改变工作方式的五种途径 Five Ways That AI Front-Runners Change How Work Gets Done

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ARTIFICIALINTELLIGENCE

FiveWaysThatAI

Front-RunnersChangeHowWorkGetsDone

By

SagarGoel

,J

ulieBedard

,

MatthewKropp

,AshleySim,andCharikleiaKaffe

ARTICLESEPTEMBER24,202615MINREAD

AIfront-runnerfirmsdon’tnecessarilyhaverecord-breakingamountsofAIusage.Instead,they

useAIto

reimaginehowworkgetsdone

:reinventingtheiroperatingmodelsandditching

establishedhierarchiesandprocessesinpursuitofspeed,growth,andcompetitiveadvantage.

Butwhatisreallyworking—andwhatcanleadersoftraditionalfirmslearnfromthesuccessesofAIfront-runners?

Arecent

BCGInstitutestudy

showedwhatisatstake:companiesthatareabletomakethis

transformationandredesignworkandtalentwithAI,ratherthanjust

layeringAItoolsontopof

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oldapproaches

,outperformtheirpeersbymorethan11percentagepointsinindustry-adjustedshareholderreturnsannually,drivenbyrevenuegrowthandmarginexpansion.

Tobetterunderstandthisjourneyinpractice,wewenttothesource,interviewingseniorleadersatmorethan50AIfront-runnerfirms.Thesecompaniesareheadquarteredintencountries,range

fromstartupstoenterpriseswithover50,000employees,andrepresentmorethanadozen

industries.WetalkedtoleadersatdifferenttypesofAIfront-runnerfirms,including23AInativesbuiltonAI,18digitalplatformswithAIasthecoreengine,and9incumbententerprisesrewiringthebusinessaroundAI,functionbyfunction.(Seethesidebar,“Methodology,”formoredetails.)

Methodology

ThisarticledrawsonaqualitativestudyofAIfront-runnercompaniesconductedbytheBCGInstitutebetweenMarchandAugust2026.

HowWeSelectedCompanies.WedefineAIfront-runnercompaniesas

organizationsforwhichAIfundamentallyredefineswhatthecompanyofferstoitscustomers,howitcompetes,andhowitoperates.Thesamplespansthreearchetypes:

AI-Native.CompanieswhereAIisthecorevalue-creatingengineoftheproductorsystem,whetherdigitalorphysical.

Digital-First.Digital-nativeplatformsthatuseAIasacoreengineforoptimization,ranking,personalization,coordination,ormonetization.

TraditionalFront-Runners.IncumbententerprisesusingAItooptimizeandreshapelegacyoperationsorproductsatscale,withoutchangingtheircore

businessmodel.Largeorganizationsrarelymoveuniformly.Whatwestudied,andwhatourexamplesdescribe,arethespecificfunctionsandworkflows

thathavegonefurthestwithAI.

WhoWeSpokeTo.Weconductedinterviewsacross50companieswithleaderspositionedtodescribehowworkisorganizedratherthanhowthetechnologyisbuilt:chiefpeopleofficers,chiefsofstaff,founders,andfunctionalleaders.Oursamplerangesfromstartupstomajorenterprises,withbasesacrosstheglobe.

Geographiccoverageis63%NorthAmerica,21%Europe,MiddleEast,andSouthAmerica,and16%Asia-Pacific.

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Industrycoverageishalfsoftwareandservicesandhalfdiversifiedacrossotherindustries.

Sizecoverageisacrosscompanyscales(14%withfewerthan50employees;24%withmorethan10,000),spanningstartupstolargeenterprises.

HowWeConductedtheInterviews.Eachinterviewwasasemi-structured

conversationfollowingninethemes:theroleofAIintheorganization,culture,

roles,skills,theemployeevalueproposition,recruiting,performance

management,upskilling,andwaysofworkingandgovernance.

HowWeAnalyzedtheData.Weworkedthrougheachtranscriptagainstthenine

themesinourinterviewguide,thentestedwhichpatternsrecurredacross

companiesregardlessofsize,geography,orarchetype.Fiveheldupconsistently,

andbecamethedimensionsdescribedhere.Wethenwentbackthroughthe

sampleandassessedeachcompanyagainsteachdimension,countinga

dimensiononlywherealeaderdescribedsomethingalreadyinplace,notan

intention.Thatscoringunderpinstheprevalencefigurescitedthroughout,

includingthat80%ofcompaniesdemonstratedatleastthreeofthefive.Weused

AItoolstosupporttheanalysis—workingthroughtranscripts,surfacingpatterns,

andtestingexamplesagainstsourcematerial—witheveryfinding,quotation,and

companyexampleverifiedbytheresearchteamagainsttheoriginaltranscript.

We’veidentifiedfivedimensionsalongwhichAIfront-runnershavechangedtraditionalwaysofworking.Theyare:

Thepurposeofwork.

Theworkitself.

Thedecisionarchitecture.

Coordinationofwork.

Rewardsandcompensation.

Mostoftheleaderswespokewithdescribedundertakingseveraloftheseshiftsatonce,and80%demonstratedatleastthreeofthefive.Forleadersoftraditionalcompanies,thesedimensions

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offeraviewofhowtomanagetheAItransitionfortheirorganizationsandteamsandaguidetotheradicalshiftsinmindsetandstructurethatareneededtoenablethetransformation.

ThePurposeofWork:FromAssignedJobstoOwned

Outcomes

Thedefaultfortraditionalcompaniesistodefineworktop-down,withfixedrolesandassigned

tasks.Inthisenvironment,eachemployeeisresponsibleforaboundedscopeofwork.However,inmorethanhalfofoursampleofAIfront-runners,leadershipsetsthedirection,butindividualsandteamsowntheoutcomes.Employeesarestillaccountableforthe“what”buthavegreateraccountabilitytochoosethe“how.”

Inthisstructure,rolesblur,withworkersassemblingaroundproblemsratherthanorg-chart

positions.AtAIcodingagent

platformBolt.new

,teambordersaredeliberatelyloose:ifsomeone’sjudgmentorskillisusefultoacolleague’sproblem,theysimplyhelp—withoutneedingtoroute

therequestthroughamanagerorwaitforittobeaddedtoaroadmap.Theexpectationthatyou’llpitchinwhereveryou’reusefulholdsregardlessofformalrole.

InmorethanhalfofoursampleofAIfront-runners,

leadershipsetsthedirection,butindividualsandteamsowntheoutcomes.

Infact,justundertwo-thirdsoftheleaderswespoketonotedtheircompanyhadheavilyreducedproceduralchecksandsignoffs,insteadputtingrealtoolsandbudgetsinpeople’shandsand

makingend-to-endownershipbothsafeandexpected.AtclouddeploymentplatformRailway,

oneleaderdescribedtheshiftasgivingupapolicingandrubber-stampingrole,whilemorejuniorworkerstookontheresponsibilitytoact,andtheaccountabilityforwhathappensnext.

Managersholdafter-actionreviewsratherthanneedingupfrontapprovals.Theytradesignoffsforstagedrollouts,andweeklystatusreviewsforbroadteamaccessandautonomy.Meanwhile,

engineerslookbeyondthecodetounderstandthebusiness,customers,andsystemonelevelhigher.

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AIcoachingplatformValencealsoencouragesandsupportsemployeesinfindingtheirownAI

solutionstoproblems.Employeesowntheproblemandaregiventheautonomyandbudgetto

obtaintherighttoolstosolveit—subjecttoanITsecuritycheckandafinancereviewofspendingpatternstoensureefficiency.Existingtoolsaremadewidelyavailable,butteammembersare

alsoexpectedtofindnewtools,experimentwiththem,andadoptthemtomaketheirworkmoreeffective.

TheWorkItself:From“HumansProduce,MachinesAssist”to

“MachinesProduce,HumansDirectandEvaluate”

Intraditionalcompanies,humansaretheproducersandtheirrolessitinfixedfunctionallanes.

Technologyisusedtospeedupselecttasks.ButinAIfront-runnerfirms,workshiftsfrom

executingtoframingtheproblemandsettingtheobjective.AIhandlesmoreofthedoing(drafting,building,executing)andpeopleshifttodirectingthetechnology—settingthebrief,steering,andevaluatingwhethertheoutputisgoodenoughtoship.Thatchangestheshapeofarole.One

personcannowproducewhatusedtotakeateam,soexistingrolesstretchtocoverfarmore

ground.PeoplegrowbydirectingAItocoveralargerscope,notjusthiringbeneaththem.Entirelynewroleshavealsoemergedtobuild,manage,andgoverntheAIlayer.

Amongourinterviewees,two-thirdsdescribepurposefullytraininguptheirworkforcesomore

peoplecandirectAI,notjustuseit.TheyachievedthisbysettingAI-fluencyexpectations,hiringforAIcompetence,wiringfluencyintoeachlevel,andmakinglearningcontinuousandpeer-led.WesawmultiplewaysthatAIfront-runnercompaniesaredoingthis.

InAIfront-runnerfirms,workshiftsfromexecutingtoframingtheproblemandsettingtheobjective.

ThecloudcontentcollaborationcompanyMirorunsamultilevelAI-fluencyprogram,expectingeveryemployeetobuildandleveragemultipleAIagentstodeliveroutcomes,ratherthanjusthelpingonatask-by-taskbasis.

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CloudintegrationsoftwarecompanyZapierdefinesAIfluencyacrossfourdimensions—mindset(curiosity),strategy(whenandwhennottoapplyAI,matchingproblemtotool),building(hands-onusetoproducequalityresults),andaccountability(knowingwhatoneistryingtoachieveandholdingoutputtoit).Assuch,thecompanytreatsAIfluencylessas“tooluse,”whereinAIis

appliedtodiscretetasks,andmoreabouthowapersonthinksabouttheirthinking.Thisisreflectedinthecompany’shiring,evaluation,anddevelopmentapproaches.

SoftwaregiantSalesforceexpectsmanagerialcapability—foresight,judgment,settingaplanwithcheckpoints,andknowingwhentointervenewithAI—fromallemployees.Evenanewjoiner

entrustedwithacostlyAIagentisexpectedtomanageitwithjudgment,steppingintoredirectitratherthanallowingittodriftoffcourseandconsumeexcessbudget.

AIcontroltowerServiceNowisredesigningworktohelpemployeesfocusonwhat’simportant.

Employeesarerewardedforshowingadaptability,curiosity,andtheabilitytoapplycontextto

createdeeperinsights.Leadersexpectworkerstoshiftfromexecutiontoinsightandhavebuiltarichorchestrationlayerwithalibraryofagentsandthetoolstocreatetheirown.

AIfront-runnersarealsoestablishingnewrolestoenabletheiroperatingmodel.Specifically,weidentifiedfiverolearchetypestimeandagainduringourinterviews.

CitizenBuilders

Citizenbuildersareoperatorsinthebusiness,buildingtheirownappsandagentstodotheirownjobbetter,reducingtheolddependenciesonengineering,data,oroutsideagencies.

CodingagentCursorhasemployeesoutsideengineeringdoingtechnicalworkthemselves.An

internalmarketerreplacedanentireagencybybuildinganappthatgeneratedthousandsof

growth-marketingassets,andthefinanceteamnowmodelsforecastsanddigsintousagetrendsdirectlyinthedata,ratherthansendingrequeststoadatateam.

EnterpriseAIcompanyDevRevhasseennontechnicalemployeesshipproductionsoftware—asales-opspersonwithnotechnicalbackgroundbuiltafullSlackbotthatreadsfromandwritesbacktotheCRM.

WorkflowDesigners

Peopleinthisrolerethinkacompany’sinternalmultistepprocessesfromendtoend:mappinghowworkflowsacrosspeopletoday,decidingwhatAIshouldabsorbversuswhatstayshuman,andrepositioningthehandoffpoints.

WhenenterpriseGenAIplatformWriterwastryingtoachievemorefrequentreferencesinAI

assistantanswers,thisapproachpaidoff.TheredesignedworkflowmeantAIagentscouldmine

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salescallsforcustomerquestionsandquicklycheckthoseanswersagainstWriter’sowncontenttofindgaps.Humanworkerscouldthenfocusonthepartofthejobwherejudgmentwasrequired—decidingwhatnewcontentwaspublishedinresponse.

Inanotherexample,hiringplatformGreenhouseisintroducinganoperations-oriented

“innovationlead”withineachdepartment—apersonwhoidentifieswhichworkflowstoautomateandevaluatestoolstodoso,thenpartnerswithacentralenterpriseappsteamofITengineerstobuildthesolutions.

AIGuardians

AIguardiansgovernriskandcomplianceandkeeptheAIecosysteminbounds.

Onecloud-basedcompanyrunsadedicatedAIcounciltogetherwithcomplianceandgovernanceteams.WhenamanagerelevatesaproposedAIusecaseoragentwithabusinessjustification,itisregisteredandundergoescomplianceandgovernancechecksbeforethecouncilreviewsitandvotesonwhetheritproceeds.Afterinitialdeployment,complianceteamsstayinvolvedin

decidingwhetheritisfittorolloutmorewidely.

AIdatainfrastructurecompanyScaleAImaintainsadedicatedunittostrengthentheguardrailsofthefirm’sownmodelsandagenticsystemsagainsthallucinationsanddataleakageby

subjectingthemtosystematicattack.

DomainAnchors

Domainanchorsencodeexpertknowledgeintoreusableform.Fourinfivefirmsdescribed

capturingtheknowledgeheldbytheirstrongestexpertssothatthewholeorganizationcandrawonit,notjustthepeoplewhositnearthem.

AI-poweredskillsintelligenceandeducationtechnologycompanyWorkerahiresonespecialistperdomain(suchasaPh.D.psychometrician)toencodetheirunderstandingintoadocumentthatanagentreadsandamplifiesacrossthecompany.

InsurtechcompanyReservbuiltitsownplatformonwhichemployeescreateAIagentsfortheirwork,capturingeachperson’sexpertiseinhowtheiragentsoperate,tobereusedacrossthe

company.Astheseagentsmultiplied,thegainscompounded.Thetimetobuildanewlearning-and-developmentprogramfellfrom18monthstofourweeks,responsestoregulatorychangesdroppedfromaboutthreedaystoaboutanhour,andjunioremployeeswereabletotakeon

higher-stakesworkthantheywouldnormallyhandlethisearlyintheircareers.

AtWalmart,employeesoftenmoveroleswithinthecompanyevery18to24months.Toensuretheirknowledgeisn’tlost,expertsdocumentthedifferentversionsofhowworkactuallygets

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done,buildinga“digitaltwin”oftheirroles.

AgentShepherds

Agentshepherdsoverseehowafleetofagentsoperate:howtheyrunandperform,whattheycanaccess,andwhentheyareshutdown.

Bolt.newdescribesacentral,AI-nativeroleresponsiblefordatagovernance,role-basedaccesscontrol,whereagentsarehosted,andmonitoringordecommissioningthosethatmisbehaveasagentsproliferateacrosstheorganization.

Walmartiscreatingorchestrationrolestomanageitscomplex,interconnectedAIsystems—anextensivemarketplaceofagentsspanningcustomer-facingandinternalsuper-agents—andtosupporttheteamsbuildingthem.

TheDecisionArchitecture:FromConcentratedtoDistributed

Underthedefaultoperatingmodel,decisionsflowup,informationdispersionforces

centralization,seniorityconfersauthority,andaccountabilityconcentratesatthetop.AtAIfront-runnerfirms,thislinearstructureisdisrupted.Deterministic,rule-basedcallscangotoagents;

reversible,lower-riskcallsarepusheddowntowardwhoeverisclosest;andirreversibleonestendtostayup.Decisionrightsaretiedtothereversibilityofthecall,ratherthansenioritylevel,whileaccountabilityismorebroadlydispersed.

Abouthalfthefirmswespoketodescribedpushingdecisionsdownward.EngineeringintelligenceplatformJellyfishletstheengineerclosesttotheworkmakethecall.Oneexampleisin

integrationwork:it’shighlyrepetitive,withsimilarchangesmadehundredsoftimes.Eachchangeusedtoneedsignofffromacodeowneroutsidetheteam.WhentheteambuiltAItoolstowrite

theintegrationcode,changevolumerosesharply,andreviewsbecameanevenbiggerbottleneck.Today,theengineerwhowritesthechangeapprovesit,mindingguardrailsagreedonceratherthanarevieweachtime,andchangesclearwithinadayratherthanthree.Accountabilityfollowsthe

decision:youcanshipitifyouwant,butyouownitifitbreaks.

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Abouthalfthefirmswespoketodescribedpushingdecisionsdownward.

EnterpriseAIcompanyHappyRobotroutesrule-bounddecisionstoagentsandkeepshumansforthejudgmentcalls.Inthepast,ahumanwoulddecidewhichengineergetsstaffedonwhich

customerdeploymentbyweighingcapacityandtimelines.Nowanagentappliesdeterministiclogic,escalatingtoahumanonlywhenrealjudgmentisneeded,sohumanworkers’timecanbespentonhigher-valuework.

Ofcourse,pushingdecisionsdownworksonlyifpeoplehavethejudgmenttomakethem.More

thanhalfthefirmswespoketodescribedbuildingthisjudgmentdeliberately—makingreasoningvisibleinopenchannels,normalizingchallengeanddiscussion,andgivingless-experienced

employeesrealdecisionstomakeearlierintheirtenure,withsupportfrommoreexperiencedcolleagues.

Reservasksstaffwhoareclosesttoproblemstodesignandproposesolutionsandtolead

iterationcycles.Seniorleaderssteertheprocessratherthanprescriptivelyinstructingtheir

workers,whoareabletodevelopbetterjudgmentasaresult.AtCursor,workersshareAI-

generatedproposalsinpublicchannelsalongsidetheirexplanationofwhytheyhadtheAI

approachtheworkasitdid.NoonecanhidebehindAIoutput,andcolleaguesareexpectedto

challengeweakAI-drivenworkratherthandefertoit.WorkAIplatformGleanmakesbuilding

judgmentanexplicitresponsibilityofmanagers,particularlywhenitcomestonewgradswho

haveyettobuildprofessionalexperienceandlackthepatternrecognitionthatexperiencedstaffdevelopovertime.

TheCoordinationofWork:FromRoutineAlignmenttoCalibrationandRelationshipBuilding

Meetings,statusupdates,syncs,andapprovalstraditionallyconsumealargeshareof

employees’timebutareoftennecessarytoensurethatkeyknowledgeandcontextare

transmittedfrompersontoperson.Now,AIcanabsorbmanyoftheroutineadminandalignmenttasksandrelocatethecontexttosystemswhereitcanbeaccessedmoreconveniently.InAI

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front-runnerfirms,humansmeettomakedecisions,exchangeideas,andbuildrelationships.

Abouttwo-thirdsofourintervieweessaidmeetingshavebecomemoreconsequential,anda

majoritydescribedmiddlemanagersshiftingfrombeingcoordinatorstobecomeplayer-coaches.

Abouttwo-thirdsofourintervieweessaidmeetingshavebecomemoreconsequential.

DevRevspenttwoyearsbuildingaproprietaryknowledgesystem,Computer,thatholdscompany-widecontextcentrally.Anyemployeecanqueryitdirectlyforanswersinsteadoffindingtherightpersonorteamtoask—removingtheinformationhandoffsthatnormallyrunthroughthe

hierarchy.WorkeraopensitsweeklyleadershipmeetingwithanAIagentthatreviewsemailandSlacktosetoutdecisionsmade,decisionsstillpending,andrecommendationsgroundedina

human-authoredtradeoffdocument,freeingmoretimeforgenuinedebate.

OthercompaniesredesignmeetingsarounddecisionsandproblemsolvingratherthanhandoffsorstatusandprotecthumancontactforwhatAIcan’treplicate,suchastrust,tacitcontext,andcreativefriction.MirohasshiftedroutinedataandstatusworktoAI,handlingdashboardsand

updatesthroughnatural-languagequeriesratherthanmeetings,andredirectedpeopletowardcustomerrelationship-building,whichitregardsasworkAIcannotreplace.

RewardsandCompensation:

FromTenureandActivityto

Impact,Judgment,andLeverage

Intraditionalcompanies,payandadvancementfollowtenure,activity,andoutputvolume;

reviewsareannual,top-down,andmanager-to-employee.InAIfront-runnercompanies,pay,

promotion,andreviewrewarddemonstratedjudgment,theleveragesomeoneextractsfromAI,andtheimpactofwhattheydeliver.Feedbacktendstobemorecontinuous,visible,andpeer-informed.

Whenevaluatingsuccess,AIfront-runnersfocusonthequalityofthinking,ratherthan

deliverables.Somethree-quartersweighjudgmentoveractivity.Sothetestmovesoffthepageandintorealtime:peopleareaskedtoexplaintheirplanbeforeworkstartsandtoshowwheretheyoverrodewhattheAIgavethem.

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Whenevaluatingsuccess,AIfront-runnersfocusonthequalityofthinking,ratherthandeliverables.

AtdataandAIplatformClay,workisevaluatedbyreallyassessingthethinkingbehindit.Shortliveconversationsof15to20minutesareoftenreliedontocheckthatsomeonegenuinely

understandsandcanactonwhatthey’veproposed,sinceAI-assistedoutputcanlookpolishedwithoutthepersonhavingreasoneditthrough.

Gleanassessespeopleonboththequalityoftheirworkandhowtheyapplyjudgmentoverthe

AI’swork,inhiringandintheirroles.SalescandidatesaregiventhreeorfourprospectsandareaskedtouseAIandtheirownjudgmenttodecidewhichtopursuefirstandthentodraftthe

outreach.Theassessmentisoftheirintuitionregardingaccountstrategyandtheoutreachemail,theirjudgmentofwhentouseAI,andhowcriticallytheyreshapedwhattheAIproducedrather

thanacceptingitunchanged.Thesamestandardappliesoncetheyarehired.

Zapierevaluatespeopleonimpact,notactivity—forexample,whetheraworkerimproveda

businessmetric,thecustomerrelationship,orateammate’swork.ItnotesthatAIisbrilliantatactivity,sosomeonecanrackupheavytoolusageyetaccomplishnothing.

ScaleAIhasmadeadvancementimpact-driven,withpeoplereachingseniortitlesearlyintheircareerswhenresultsjustifyit.

It’salsoimportanttorecognizeaccomplishmentpublicly.Writercelebratestopcontributorsat

all-handsmeetingsandhasthemexplainwhattheybuiltandwhyitmattered,showcasingthosewhoseworkandmethodsareadoptedbyothersratherthanthosewhosimplyrecordthemostAIusage.Intraditionalfirms,expertsareoftendisincentivizedtopassontheirknowledgeforfearoflosingtheirstatusas“indispensable.”Bymakingtheactofsharingknowledgeavisiblepathto

success,AIfront-runnersensureit'smorewidelydispersed,andnotlostwhenstaremployeesdepart.

WhatCanTraditionalCompaniesDoToday?

TraditionalcompaniesembarkingonanAItransformationareinachallengingposition.TheyneedtomakethefiveshiftsthatAIfront-runnerfirmshavealreadyachieved,anddosowhile

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carryingtheexistingbusinesswiththem—amultiyearundertakinggiventhatthosesystemsactivelyresistthechanges.

Critically,leaderscannotpursueallfivedimensionsatthesamespeed—theyhavetosequenceandadaptthemtotheircompanyspecifics.Wefocusbelowonlargecompaniesinoursample

becausetheircoordinationcostsandlegacystructuremostresemblewhatincumbentswillfaceinthisjourney.Leadershavepushedfurtherandfasteronsomedimensionsthanothers.Roles

andjudgmentshiftfastest,becausetheydon’trequiredismantlinganything:almostalllarge

companiesarebuildingnewAI-erarolesandtreatingjudgment,notactivity,asthemarkofgood

work.Ontheotherhand,redefiningworkaroundoutcomesisunderwayatonlyabouttwo-thirdsoflargecompanies,andfewerthanhalfhavepushedauthoritydownthecorporatehierarchy.

WhatfollowsisaroadmapthattraditionalcompaniesshouldkeepinmindintheirjourneytoAI

front-runnertalentpractices:firstbuildingthefoundation,thenprovingitinoneplace,andfinallyscalingitacrosstheenterprise.

BuildtheFoundation

Definevalueandmaptheworkforceimpacts.Identifythebusinessoutcomesthatyour

prioritizedAIopportunitiesaremeanttounlock.Don’tadoptAIforitsownsake.Then,translatethoseoutcomesintowhichroles,functions,andskillsaremostaffected.

DefineAIfluency.ArticulatewhatAIfluencymeansforyourorganizationspecifically:themindset,judgment,andcapabilitybar,notjusttoolusage.Thenbuilditintohiringcriteria.China-based

real-estateplatformKeshifteditsinterviewquestions,de-emphasizingschoolpedigreeinfavorofaskingcandidates,especiallynewgraduates,directlywhattheybuiltwithAIandwhatthey

learnedfromusingit.

Equipandenable.GivepeoplerealtoolsandthespacetoexperimentwithAIintheiractualwork.Builddeeperfluencyandcapabilityinprioritizedareas,ideallythroughteam-basedworkflows,

anddesignlearningjourneystailoredtoeachfunctionorjobfamily.Walmartplacedfrontierto