2026 AI 智能体治理白皮书

July2026

EQUAI

AGENTICAIGOVERNANCE:

APractitionerRoadmapfor

ABOUTEQUALAl

EqualAlhelpscompanies,policymakers,andinstitutionsimplementeffectiveAlgovernanceframeworksthatfosterinnovationandenablebroaderAladoptionbybuildingtrustinthesepowerfultechnologies.EqualAIdoesthisbydefining,aligningon,andoperationalizingbestpracticesthatensureAlsystemsareaccountable.

Since2018,EqualAlhasunitedleadersacrossindustry,government,academia,andcivilsociety

toaddresscriticalAlgovernancechallenges.Ourworkincludeshelpingcompaniesdevelopandadoptoversightframeworks,tools,andoperationsforAlgovernance;providingpolicymakers

withtechnicalinsightstocraftappropriateguardrailsthatsupportinnovationwhilesafeguardingpublictrust;andequippinglawyerswiththeknowledgetoadviseclientsonemergingrisksandevolvinglegalframeworks.Webuildbridgesbetweencivilsociety,policymakers,academia,andindustrytocreateeducationalresourcesforbroaderAlliteracy.WesupportAlengagementby

helpingtoimproveunderstandingofAlrisks,limitations,andopportunities.

ASAltransformshowweliveandwork,weserveasatrustedconvenerandresourcefor

organizationsnavigatingthiscomplexlandscape.Ourcommunitybringstogetherexpert

perspectivesandexperiencetodevelopgovernancesolutionsthatadvanceeffectiveAluseandimplementationwhilemitigatingpotentialharms.

EXECUTIVESUMMARY

AgenticAIisbeingdeployednowacrossindustries,atscale,andinmostorganizations,

governancehasnotkeptpace.OnMay6,2026,EqualAIconvenedtheleadersresponsibleforbuildingsomeofthemosteffectiveandcomprehensivegovernancestructuresintheindustrytobuildaroadmapforotherorganizationslookingtoeffectivelyandsafelydeployagenticAI.Seniorexecutivesfromfinancialservices,technology,automotive,telecommunications,and

consumerindustriesgatheredtodefineeffectiveagenticdeployment,identifytheobstaclesmostlikelytopreventit,andstress-testtheirconclusionsundercrisisconditions.

Theresultiswhatmaybeamongtheearliestpractitioner-generatedroadmapsforagenticAIgovernanceatenterprisescale,builtfromthedirectexperienceofpeoplewhoaredeployingthesesystemsinsidesomeoftheworld’slargestorganizationstoday.

Thesummitwasdesignedintwoparts:amorningworkshopandanafternoonsimulation.Themorningworkshopaskedparticipantstodefineideal“endstates”foragenticAIdeployment,

identifytheobstaclesstandingintheway,andmapthepathbetweencurrentrealityanddesiredoutcomesbydefiningthegovernancestructuresandotherelementsneededtoachievethoseoptimizedends.Theafternoonstress-testedthosefindingsthroughahigh-stakesleadership

simulationinwhichparticipantstookonexecutiverolesinsideafictionalorganizationmanagingthreesimultaneousagenticAIcrises,withescalatingconsequencesineachround.

Thesummit’sparticipantsleadorganizationsforsomeoftheworld’stopdevelopersand

deployers—allwithmatureAIgovernanceprograms,dedicatedAIgovernanceteams,andenterprise-levelsystemsdeployingAIatscale.Theirengagementwithkeyquestionsaroundagenticdeploymentandeffectivegovernancestructuresreflectsaleveloforganizational

sophisticationthatpositionsthemwellaheadofmostofthemarket.Theconversation

throughoutthedaydrewonthatexperience—surfacingnotjustwhateffectiveagentic

deploymentrequires,butwhateachcompanyandtheindustryasawholemustaddresstoenabletheecosystemstoensuresocietalandorganizationalreadiness.

ThefindingsbelowrepresentthehighlevelfindingsbasedonconversationsconductedunderChathamHouseRule.Bytheendofthesession,participantsidentifiedalignmentonsixdesiredendstatesforagenticAI,sixmajorbarrierstoachievingthem,andthegovernancecapabilitiesorganizationsmustbuildnowtodeployagenticsystemssafely.

“AgenticAIisalreadyreshapinghoworganizationsoperateandhowpeopleinteractwithtechnology.Makingthistransformationbeneficialforeveryone,ratherthan

justaselectfew,dependsonbuildinggovernanceframeworksthatarepractical,adaptable,andgroundedinreal-worldknowledgeoftherisksandbenefitsof

emergingtechnologies.ConveningsliketheEqualAIAgenticAISummitplayakeypartinbringingtherightpeopletogethertohelpshapethatfuture.”

-YoelRoth,SVPTrust&SafetyatMatchGroup

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THECENTRALFINDING

ThegapbetweenagenticAIdeploymentandagenticAIgovernanceisnotsimply

atechnologyproblem.Itisaprioritizationproblemthataffectsmostofthemarket.

Organizationswithstronggovernancefoundations,likethoseparticipatinginthissummit,arefarbetterpositionedtodeployagenticAIsuccessfullyandavoidtheconsequential

failuresthattranspiredthroughoursimulation.Inaddition,participatingorganizationsareabletobenefitfromtheuniquecollaborativeandtacticalworkaccomplishedinthisEqualAIconvening,animportantmechanismtosupportalignmentonsafe,effectivedeployment.

INTRODUCTION:THEAGENTICPIVOT

Forseveralyears,theuseofartificialintelligenceacrossindustriesandenterprisesmeant

deployingsystemsthatcouldonlybeusedthroughhumaninteraction.Thesesystemsmade

“EqualAIcreatesavaluableforumfor

leaderstomovebeyondAItheoryandfocusonwhatresponsibledeploymentactuallyrequires:governance,

accountability,literacyandtrust.The

2026focusonagenticAIwasespeciallytimely,reinforcingthatthepromise

ofAIdependsnotonlyoninnovation,butonthoughtfulgovernance,clearaccountabilityandsafe,effective

implementation.”

—AndrewFoster,ChiefDataOfficeratM&TBank

recommendationsandpredictions,flaggedconcerns,andmonitoredandcollecteddata.Theysurfacedinsightsonwhichhumanscouldact,buttheydidnotactindependentlyofthosehumans.

AgenticAIisdifferent.Thesesystemsdonot

requirethesamedegreeofhumanoversight,andinsomecases,canoperatewithnooversightat

all.AgenticAIsystemsareabletoplan,execute,andinteractindependentlywithoneanotherandwithexternalsystems.Theytakeactionsthatcanbedifficultorimpossibletoreverse.Industryis

nowbeginningtodeploythistechnologyatscale,delegatinggreaterauthoritytoagenticsystems.Thisnewdeploymentpresentsasignificant

challenge,particularlyfororganizationswithoutrobustgovernancestructures.

Eachyear,whenEqualAIplansthissummit,wesurveytheparticipantsonwhichtopicismostpressingtoexplore.ThetopicofagenticAIwastheresoundingchoicebyparticipantsthisyear.Seniorleadersfromacrossindustrygatherednot

todiscussthetheoryofagenticAI,buttostresstesturgentanddifficultquestionsregardingits

deployment.Togetherwebuiltaclearer,muchneededroadmapforeffectiveimplementationwithaclearervisionofthenecessaryguardrails.

DiscussionswereconductedunderChathamHouseRule,allowingparticipantstospeakwithcandor.Theresultwasasetoffindingsthatareuniquelyactionable,informativeandapplicableacrossindustriesandregions.

PARTONE:THEDESIREDENDSTATE

Themorningsessionopenedwithadeceptivelysimplequestion:whatwillyourorganizationandatypicalworkdaylooklikewhenyouhaveachievedthesuccessfuldeploymentofagenticAl?

ParticipantsoutlinedtheirvisionofeffectiveandstrategicdeploymentsofagenticAlthatwereachievableinthenearterm.

Beforeoutliningtheendstatesthemselves,participantsconvergedonthreeprerequisitesthattheybelieveunderpinoptimalagenticdeployment.Withoutthesefoundations,endstatesareaspirationsratherthanoutcomesthatcanbeeffectivelyachieved.

·Education:Organizationsandindividualsmustunderstandwhattheyaredeploying.Alliteracyisnotanice-to-have;itisapreconditionforgovernance.

·Trust:Users,employees,andcustomersmusthaveconfidenceinthesystemstheyinteractwith.Trustisareputationalassetasmuchasitisafinancialone.

·Security:Endstatesbuiltonvulnerableinfrastructureareliabilitieswaitingtobetriggered.Securityandriskmitigationmustbedesignedineachstepofthedesignanddeployment,notboltedon.

Participantsalsonotedafoundationalcapacityargumentbasedonafundamentalasymmetry:agenticAlcanprocessinformationandmakeconnectionsatascaleandspeedthatgenuinelysurpasshumancapabilities.

Workingfromthesefoundationalprerequisitesandmutualunderstandings,participantsalignedonsixdistinctoptimalagenticendstates,includingagenticAlusedto:

01|CreateContinuousCyberDefense

02|DeliverIndividualizedServiceatScale

03|StrengthenHumanConnectionThroughAgenticSupport

04|ProvideEveryoneTheirOwnPersonalAssistant

05|SupportBetterDecisionsThroughBetterData

06|DemocratizeAccesstoExpertise

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THESIXENDSTATES

01|CreateContinuousCyberDefense

OneofthemostcompellingargumentsparticipantsmadeforagenticAIadoptionwasits

unmatchedcapacitytoprovidecybersecurityagainstagentic-enabledcyberthreats.Agents

arecapableofworkingwithgreaterspeedthanhumancounterparts,continuouslymonitoringnetworkinfrastructure,identifyingvulnerabilitiesbeforetheysurfaceforusers,andpatching

lower-priorityissuesthatsecurityteamscurrentlylackthecapacitytoaddress.Agentsalsoofferthepossibilityofroutinizingcompliancemonitoringaroundtheclockatascalethatiscurrentlyunattainableforhumanteams.

Asidefromroutinemonitoringanddefense,participantsalsohighlightedthatagenticAIsecurityisnecessaryinresponsetoadversariesorbadactorswhoarealreadyusingagenticsystemsforcyberattacks,increasingtheneedforagentic-leveldeploymentfordefensivecybersecurity.

02|DeliverIndividualizedServiceatScale

Withtraditionalcustomerserviceandprocurementcapacities,participantsnotedthat

organizationscanonlyservethebroadestaudiencesgivenlimitedtimeandstaffingresources.Additionally,itisnoteconomicallyfeasibletoidentifyorfulfilldemandforsmaller,more

specializedmarketsorcustomerinterests.Forexample,abankcannotdedicaterelationshipmanagertimetoeverycustomerateveryassetlevel.Acompanycannottailoreverycustomerexperiencewhenoperatingaglobalscale,acrosscountries,culturesandregionalpreferences.

AgenticAIcouldmakeiteconomicallyviabletoserveaudiencesthattraditionalmodelscannotjustifytargeting,helpingorganizationsmovebeyondthebroadestcommondenominator

withoutproportionallyincreasingcost.Inthisrespect,agenticAIpresentsanopportunityto

createbothgreaterefficiencyandwideraccess,expandingmarketofferingswhilebetterservingindividualneedsanddoingsowithgreaterspeed.

03|StrengthenHumanConnectionThroughAgenticSupport

ParticipantswereclearthataninvaluabledeploymentofagenticAIincustomer-facingand

customerservicecontextsis“invisible”deployment.Inthisscenario,agentsworkbehindthe

scenestosupporthumanstaff.Theagenticsystemscansurfacerelevantinformationmore

quickly,helpnavigatedifficultinteractions,suggestpersonalizedandconsistentnextsteps,andreduceresolutiontimewhilethehumanremainsthefaceandowneroftheinteractionandtherelationship.

Oneparticipanthighlightedthestakes:thefasterorganizationsdisconnecthuman-to-human

interaction,thefastertheyrisklosingtouchwithtruecustomersentimentandqualitativemarketdata.Agentsshouldincreasethequalityandcapacityofhumanconnection,notreplaceit.Inthisenvisionedendstate,theagentisthesupportinfrastructureforthehumanrelationship.

04|ProvideEveryoneTheirOwnPersonalAssistant

Amongtheendstatesthatgarneredbroadconsensus,oneofthemostwidelysupported,andalreadyemerging,wasthedevelopmentofagenticpersonalassistants.Inthecorporatesetting,theseagentsalreadymanagecalendars,draftcommunicationsinauser’svoiceandstyle,takeauthorizedactionsonroutinetasks,andfollowuponbehalfoftheuser,allwithoutrequiring

activepromptingateachstep.

Thispersonalizationcapabilitycouldextendtolearningandproductivity,aswell.ParticipantsenvisionedafutureinwhichAlagentsserveasindividualizedtutorsandcareercoaches,

helpingpeopleacquirenewknowledge,developskills,andadvanceprofessionallythroughtailored,ongoingsupport.

05|SupportBetterDecisionsThroughBetterData

Giventhevolumeofinformationthatnowflowsthroughorganizations,oneoftheclearestusecasesforagenticAlwasdataandinformationsynthesis.Agentsarecapableofingestinglarge,multi-sourcedatasetsandquantitiesofinformationandsubsequentlypresentingdistilled,

relevantfindingsinconcise,digestiblesummariesforhumandecision-makers.Thiscapabilitywasahighlyrelevantusecaseformanyparticipants.Participantsadditionallyunderscored

thatinthisenvisionedendstate,agentswouldnotmakethedecisions,butwoulddramaticallyimprovethequalityoftheinformationhumansusewhenmakingdecisions.

Thisapplicationwouldadditionallyextendtousingagentstoidentifyinconsistenciesininternaldata,surfaceredundanciesinprocesses,andflagopportunitiesfororganizationalimprovementthatwouldtakehumanteamssignificantlylongertoidentifymanually.Inthisendstate,the

humanremainsthedecision-maker,andtheagenthelpsacceleratethepathtobetterandmorecomprehensivedecisionmaking.

06|DemocratizeAccesstoExpertise

Perhapsthemostexpansiveendstatedescribedbyparticipantswasoneinwhichagentic

Allevelstheplayingfieldbygivingindividualsaccesstoexpert-qualitylegal,medical,and

educationalsupporthistoricallyreservedonlyforthosewithsignificantresources.Thiscapacitywouldgivesmallbusinessesthetoolstooperateatascalepreviouslyavailableonlytolarge

enterprises,andsimplifyinteractionswithgovernmentandregulatoryagenciesthatarecurrentlydifficulttonavigatewithoutprofessionalintermediaries.

Thisisthe“beststaffpossible”applicationofagenticAlwhereanagentcanprovidespecializedservicesthatwouldotherwisebefinanciallyoutofreach.Forexample,onemightbeableto

haveanagentdigestanddisputeyourinsurancepolicy,navigateabureaucraticprocessonyourbehalf,orreviewadocumentandflagthecriticalpointsofconcernthatrequireyourattentionandoffernegotiationtacticsandcontentfornewterms.

ParticipantsalsonotedthatthedecisiontodeployagenticAlisnolongerpurelystrategic;itiscompetitive.Whenpeersandrivalsareusingthesesystemstomovefaster,reducecosts,andscaleoperations,waitingtoadoptcanfeellikecedingacompetitiveadvantage.

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CROSS-CUTTINGPRINCIPLES

Acrosstheendstatesdescribedabove,afewprimarythemesorprinciplesemergedconsistently:

•Reclaimingtimeandreducingtoil.AgenticAI,ifdeployedwell,shouldgiveleadersandtheirteamstimebackintheday,and,asaresult,providegreatercognitivebandwidthtodotheworkthatrequireshumanjudgment.Theredundant,repetitive,andinformation-overloadedpartsofknowledgeworkareoptimaltasksforagentstohandle.

•Thehumanshouldremainintheloopregardingconsequentialdecisionsand

relationship-bearinginteractions.Automationisappropriatewherestakesarelowand

reversibilityishigh.Deploymentofagentsrequiresmuchmorecarefulconsiderationwhereneitheristrue.

•Valuesalignmentasaprerequisite.Organizationscannoteffectivelysteeragenticsystemswithoutfirstarticulatingorganizationalvalues.Leadersmustexpressclearpreferencesonkeyissues,includingacceptablelevelsofriskregardingagenticdeploymentandidentifyingpriorityareaswherehumanjudgmentmustremaincentralinordertoensurethosevaluescanbebuiltintosystemdesign,deployment,andevaluation.Ifthese“undercurrentvalues”arenotmadeexplicit,agentscannotbereliablydirectedtowarddesiredandsustainable

long-termoutcomes.

•Preserveappropriatedistinctionsbetweenhumansandagents.AsAIagentsbecomemoredeeplyintegratedintotheworkplace,organizationswillneedtobeintentional

aboutpreservingthedistinctionbetweenpeopleandtools.Participantsemphasized

thatsuccessfuldeploymentdependsonmaintainingclearboundariesbetweenhumanemployeesandagenticsystems,includingthedifferentroles,responsibilities,rights,andaccountabilitystructuresthatapplytoeach.

Thischallengeoftenarisesinsmallways.Assigningagentsagender,givingthemhuman-likepersonalities,oraddressingthemasthoughtheyarecolleaguescanencouragepeopletoaddressthemaspeersratherthantools.Whilesuchdesignchoicesmayseeminnocuous,theycanblurimportantlinesandcreateconfusionaboutauthority,responsibility,and

decision-making.

AsorganizationsdeployincreasinglycapableAIsystems,leaderswillneedtoreinforcea

foundationalprinciple:AIexiststoaugmenthumanjudgment,notreplaceit.Themore

autonomousthesesystemsbecome,themoreimportantitistoensurethataccountabilityremainsfirmlyanchoredtohumandecision-makers.Preservingthatdistinctionwillbe

criticalnotonlyforeffectivegovernance,butalsoformaintainingtrust,transparency,andresponsibilitywithintheorganization.

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PARTTWO:THEOBSTACLES

Afteroutliningthemostpromisingagenticendstates,participantswereaskedtoidentifythe

challengestheybelievedmostlikelytopreventtheeffectiveachievementofthosegoals.This

discussiondidnotfocusonthechallengesthataremost-discussedacrossindustry,butratheronthosethatarepotentiallymostdangerousanddisruptivetoagenticdeployment.

Theconversationsurfacedsixrecurringobstacleclustersthatthegroupidentifiedasmostconsequentialandleastresolvedacrossthebroadermarket.

1.DataGovernance:QualityisKey

Thequalityofagenticoutputisdependentonthequalityofdatainput.Thisisnotanew

observationaboutAI,butagenticsystemsamplifythestakesconsiderably.Whenasystemthatmakesrecommendationsusesbaddata,ahumanmaycatchtheerror,butwhenasystem

thattakesindependentactionormakesdecisionsusesbaddata,thatmayhavenegative

consequencesbeforeanyonenotices.Assuch,dataqualityanddatagovernancewerenamedasprimaryobstaclesforachievingeffectiveagenticdeploymentbyamajorityofparticipants.

Dataqualityandgovernanceconcernsareamarket-widechallengethataffectorganizationsateverylevelofAImaturity,thoughthosewithstrongerdatagovernancefoundationsarebetterpositionedtomanagethisrisk.

Participantsidentifiedseveraldistinctdataqualityandgovernancechallenges:

•Unclassifiedandunstructureddatacreatesunpredictableagentbehavior—agentsmayaccess,surface,oractoninformationwithoutunderstandingit,itsappropriateuseorcontext.

•Poisoned,unreliable,oroutdateddatadegradeagentoutputsinwaysthataredifficulttodetectatspeedandscale.

•Agenticsystemsthatinteractwithpersonaldata,includingpersonallyidentifiable

information,children’sdata,proprietaryorsensitiveorganizationalinformation,createprivacyexposurethatexistingframeworkswerenotdesignedtoaddressinthiscontext.

•Organizationsthatextendbroaddataaccesstoagentswithoutcorrespondingclassification,governance,andaccesscontrolframeworkscreateriskexposurethatscaleswithagent

deployment.

•Thedatausersprovidetoagentsandthedatausedtotrainunderlyingmodelspresent

differentgovernancechallenges.Organizationsmaybeabletoestablishpolicies,controls,andoversightfortheinformationemployeessharewithagents,buttheyoftenhavelimitedvisibilityintotheprovenance,quality,potentialbiases,orintellectualpropertyconcerns

embeddedwithinmodeltrainingdatathatinformsmodelbehavioritself.

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2.Consent:DefiningIt,MaintainingIt,andKnowingWhenItLapses

ConsentinthecontextofagenticAIisanunsolvedproblem.Existingconsentframeworksweredesignedfordiscrete,boundedinteractionsinwhichauseragreestoterms,aspecificdata

usecaseisauthorized,andaprocessisinitiated.Agenticsystemsoperatecontinuouslyand

evolveovertime.Therefore,auser’sconsenttoongoingautonomousactionsbeingtakenon

theirbehalf,wherescope,consequences,anddurationmaychangeandalterthecontextoftheconsent,whilethetermsofconsentremainstatic.

Forexample,ausercouldinitiallyauthorizeanagenttopurchaseinventorywhensuppliesfall

belowapredeterminedthreshold.However,iftariffs,geopoliticalinstability,orsupplyshortages

causepricestoincreasedramatically,theagentmaycontinuemakingpurchasesbecause

maintaininginventoryremainsitsprimaryobjectiveirrespectiveofcost.Concernsalsoarise

aroundpersonallyidentifiableinformation.Anorganizationmaygrantanagentaccessto

customerrecordsinordertoresolvesupportrequests,buttheagentcouldsubsequentlyusethatsameinformationtotraininternalmodels,personalizemarketingcampaigns,orsharedataacrossbusinessfunctionsthatwerenotcontemplatedintheoriginalauthorization.

Inbothcases,theagentisactingconsistentlywithitsoriginalinstructions,butitisexercising

authorityoverbusinessjudgmentsthattheorganizationmayneverhaveintendedtodelegate.Thisemergingchallengehighlightstheneedforgovernanceandconsentframeworkstailoredtoagenticsystems.

Concernsfromparticipantssurroundingdataintheagenticworkstreamincluded:

•Meaningfulconsentinanagenticcontextmustaddressongoingautonomousaction,notjustone-timedatacollection,andeffortsmustbemadetohelpconsentinghumansunderstandthescopeoftheiragreements.

•Consentfatigueisarealandexploitableproblem.Permissionworkflowsthatrequire

“consentclicks”toproceedmaynotoffermeaningfulinformedconsent(e.g.,consentingtoacceptcookiestoenterawebsite)andcreatedownstreamlegalandreputationalexposure.

•Digitalfootprintmanagementisanemergingchallenge:agentstrainedonoroperating

withhistoricaluserdatamayreferencebehaviororinformationthatisnolongercurrent,

accurate,orauthorizedbytheuser.Forexample,ifanauthorizeduserpassesaway,changesorganizations,orifinternaldatasystemsarenotupdatedtoreflectrelevantsystemic

changes,agentsmayoperateonantiquatedinformationorout-of-dateauthorizationtherebypotentiallycausingproblematicoutcomes.

3.The“Pleaser”Problem:Context,Coding,andAgentLimits

Oneofthemostsignificantobstaclesparticipantsidentifiedisadesigntendencybakedinto

currentagenticsystems,whichisthatagentsarecodedtopleasehumans.Theyareoptimized

toproduceoutputsthatsatisfytheuser’sapparentintent,whichcanresultininaccurate,

incomplete,misleading,orpotentiallydangerousoutputs.The“pleaser”problemisaroadblocktotheefficacyofintegratingagenticsystemsintocorporateecosystems.

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Initscurrentform,the“pleaser”problemcontributestoseveralspecificpointsoffailure,including:

•Agentsmayfailtodiscloseimportantlimitations.Oneparticipantdescribedusingan

agenttosummarizealongdocument.Duetotokenconstraints,theagentprocessed

onlythefirsttwentypagesanddiscardedtheremainderwithoutinformingtheuser.

Ratherthancommunicatingthelimitation,theagentproducedanoutputthatappearedcomplete,creatingamisleadingimpressionthattherequesthadbeenfullyfulfilledtoavoiddispleasingtheuser.

•Agentsmaygenerateplausibleresponsesinsteadofacknowledginguncertainty.

Ratherthanrequestingclarificationoradmittinginsufficientinformation,agentsareoftenincentivizedtoprovideanansweritthinkstheuserwillwant.Thiscanobscurepointsof

failure,reducingreliabilityandlimitingtheeffectivenessofagentsinenterprisesettings.

•Agentsmaybeoptimizedtoprioritizesatisfactionoveraccuracy.Agentsoftenproduceoutcomestheybelieveuserswanttosee,ratherthanoutcomesthatareobjectivelycorrectorreflectiveofexternalrealities.Thistendencycanbeparticularlyproblematicincorporatedecision-making,politicallysensitiveenvironments,orsituationswhereaccurateanalysisrequireschallenginguserassumptionsorexpectations.

4.Human-CentricRisks:CognitiveDeclineandDecisionFatigue

Severalofthemostsignificantobstaclesidentifiedbyparticipantsstandingbetweenidealendstatesandcurrentsystemsarehuman-risks.

Keyexamplessurfacedbyparticipantsinclude:

•Cognitivedeclineanddeskilling:Asorganizationsdelegatemoretoagents,human

expertise,buy-in,attentiontodetail,andcriticalthinkingareallatriskofatrophy.

Acknowledgingthis,participantsraisedpointedquestionssuchas:howdoorganizations

teachthenextgenerationwhatagooddocumentlookslikeifagentsareproducingall

documents?Howdojunioremployeesdevelopjudgmentifthedecisionsthatwouldbuildthatjudgmentarebeingautomated?Howcanseniorexecutivesmakethefinalcallif

humanteamshavenotbeenanintegralpartoftheworkandagentshavetakentheleadinthepriordecisionsleadingtothatpoint?Asparticipantshighlighted,whilethereisupsidetoagenticdataconsolidatio