人工智能安全与治理现状（英文）

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Acknowledgments

LeadAuthors

HillaryBaron

Contributors

StephenLawtonDanieleCattedduRichMogull

JohnYeoh

AntonChuvakinDouglasKo

GraphicDesign

StephenLumpe

AbouttheSponsor

MakeGooglepartofyoursecurityteamwithunmatchedthreatvisibility,aunifiedsecurityplatform,andMandiantfrontlineexperts—superchargedbyAI.

OrganizationscanreducedigitalriskandsecuretheirAI

transformationwiththesamecybersecurityspecialists,

capabilities,andsecureenterpriseplatformsGoogleusestokeepmorepeopleandorganizationssafeonlinethananyoneelseintheworld,poweredbyourindustry-leadingthreat

intelligence.AIenhancesallofthesecomponents,enablingsecurityteamstodetectmorethreats,minimizetoil,and

takeproductivitytonewlevels.

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TableofContents

Acknowledgments 3

LeadAuthors 3

Contributors 3

GraphicDesign 3

AbouttheSponsor 3

TableofContents 4

ExecutiveSummary 5

BytheNumbers—AISecuritySnapshot 5

KeyInsights 6

1.GovernanceIstheMaturityMultiplier 6

2.SecurityBecomesanEarlyAIAdopter 6

3.LLMConsolidationwithinMulti-ModelStrategies 6

4.ExecutiveAIEnthusiasm,QuestionsAboutAbilitytoSecure 6

5.AIOwnershipIsDiffuse—SecurityIsSteppingUp 6

6.DataRiskTakesCenterStage—ButModelRisk&SafetyStillLagsBehind 6

What’sNext? 7

KeyFindings 8

KeyFinding1 8

KeyFinding2 10

KeyFinding3 12

KeyFinding4 14

KeyFinding5 15

KeyFinding6 17

Conclusion 19

Demographics 20

SurveyMethodology 21

GoalsoftheStudy 21

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ExecutiveSummary

Thesurveyrevealsacleardivide:organizationswithestablishedAIgovernanceareacceleratingadoptionwithconfidence,whiletherestaremovingquicklybutwithoutthestructuresneededtomanageemergingrisk.AsgenerativeandagenticAIscalefrompilotstoproduction,thegap

betweengovernance“haves”and“have-nots”isbecomingthestrongestpredictorofreadiness.Thisyear’sCSA–GoogleCloudsurveyshowssecurityleaderssteppingintoadefiningmoment—workingtosecureAIsystemsevenastheybeginusingAItostrengthensecurityitself.Themarketisevolvingat

remarkablespeed,andgovernanceisemergingasthefoundationthatdetermineswhetheradoptionadvancesresponsiblyoroutpacesanorganization’sabilitytomanageit.

“Asorganizationsmovefromexperimentationtooperationaldeployment,strongsecurity

andmaturegovernancearethekeydifferentiatorsforAIadoption.”

—Dr.AntonChuvakin,SecurityAdvisoratOfficeoftheCISO,GoogleCloud

Acrosseverysectorandregionsurveyed,organizationsarenowembeddingAIintocoreoperationsandsecurityworkflows.However,thegovernancestructuresandtalentpipelinesneededtosecurethis

adoptionarestillcatchingup.

BytheNumbers—AISecuritySnapshot

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KeyInsights

1.GovernanceIstheMaturityMultiplier

OrganizationswithformalAIgovernancearesignificantlymoreadvanced:

●2xmorelikelytoadoptagenticAI

●3xmorelikelytotrainstaffonAIsecuritytools

●2xmoreconfidentinprotectingAIsystems

Thisreinforcesgovernanceasthefoundationforresponsibleinnovation—andapractical

countermeasureto“shadowAI.”

2.SecurityBecomesanEarlyAIAdopter

Inamarkedshiftfrompasttechnologycycles,securityteamsareamongtheearliestadoptersofAI.Over90%ofrespondentsaretestingorplanningtouseAIforthreatdetection,redteaming,andaccesscontrol—highlighting

theurgencyandopportunitytoembedAIintosecurityfromtheoutset.

3.LLMConsolidationwithinMulti-ModelStrategies

Organizationsarepursuingmulti-model

strategies—usinganaverageof2.6models—butdeploymentsareincreasinglyconcentrated

amongthe“BigFour”:Gemini,Claude,GPT,andLLaMA.Whilethissignalsgrowingoperational

maturity,italsointroducesnewresilience,

interoperability,andvendorlock-inconcerns.

4.ExecutiveAI

Enthusiasm,QuestionsAboutAbilitytoSecure

ExecutiveenthusiasmforAIremainshigh,yet

mostrespondents(72%)wereeithernot

confidentorneutralintheirorganization’sabilitytosecureit.While70%reportmoderatetofullleadershipawarenessofAIsecurityimplications,thisgapunderscorestheneedfordeeper

governance,education,andcross-functionalcollaboration.

5.AIOwnershipIsDiffuse—SecurityIsSteppingUp

ResponsibilityforAIdeploymentisdistributed

acrossfunctions,butsecurityteamsnowleadAIprotectionin53%oforganizations.

Securityisnolongeranafterthought—it's

emergingasbothastakeholderandapioneerinresponsibleAIimplementation.

6.DataRiskTakes

CenterStage—But

ModelRisk&SafetyStillLagsBehind

Organizationsareprioritizingwell-understood

risks:52%citesensitivedataexposureastheir

topconcern,followedbyregulatorycompliance(50%).Thesetraditionalissuesfaroutweigh

newerAI-specificthreatslikemodeldrift,

promptinjection,andmodeltheft—whichremainacknowledged,butrarelyrankedastop-tier.

That’snotablegiventhatadatabreachtodaycarriesan

averageglobalcostofUS$4.88

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million

—makingthestakesoftreatingAI

securitysolelyasanextensionofexistingprivacyandcomplianceframeworksfartoohigh.

However,adeeperissueliesbeneaththe

surface:just21%ofrespondentscallout

model-levelrisks—includingdatapoisoning,promptinjection,orotherformsofmodel

manipulation—askeyconcerns.Partofthis

reflectsamaturitygap,butitalsohighlightsa

practicalreality:model-focusedrisksarenewer,andmanyorganizationsarestilldevelopingtheskillsandfamiliarityneededtousetheemergingtoolingthathasonlyrecentlycometomarket.

What’sNext?

Thisreportcallsonorganizationsto:

●AccelerateAIgovernanceusingframeworkslike

CSA’sAICM

or

Google’sSAIF,then

s

upplementedwhereappropriatewithindependentassessmentsoradvisoryservices.

●InvestinAI+Cybersecurityskillbuildingthroughtraining,upskilling,andinter-teamcollaboration

●Embedsecure-by-designprinciplesintoAIdevelopmentworkflows

●Measurewhatmatters—frommodelintegritytopolicyadherence

Insummary,thesurveyrevealsalandscapewhereAIismovingfaster—andsecurityiscatchingup.Thedifference-makerisgovernancematurity:organizationsthatoperationalizetheirpoliciestodaywillbetomorrow’sleadersintrustworthyAIadoption.

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KeyFindings

AIadoptionisstillearlybutacceleratingrapidly,andthisyear’sresultsshoworganizationsmovingfrom

experimentationtomeaningfuloperationaluse.Whatstandsoutisnotjustthepaceofdeployment,buttheheightenedawarenessaccompanyingit:leadersareengaged,governanceeffortsareemerging,andteamsareworkingtobalanceinnovationwithaccountability.Acrossbothdimensionsofthe

survey—securingAIsystemsandusingAItostrengthensecurity—organizationsaremakingearlyprogress,evenastheycontinuetograpplewithfoundationalchallengesinriskunderstanding,dataprotection,

staffing,andpolicy.

KeyFinding1:

StrongAIGovernanceAssociatedwith

Confidence,RiskAwareness,and

ResponsibleInnovation

WhileorganizationscontinuetobuildtheirAIsecuritycapabilities,thepresenceofformalgovernancepoliciesstandsoutasoneoftheclearestpredictorsofmaturityandreadiness.Only26%of

organizationsreporthavingcomprehensiveAIsecuritygovernancepoliciesinplace,butanadditional64%saytheyhavesomeguidelinesorareintheprocessofdevelopingthem.Thesenumbersshowthatwhilecomprehensivegovernanceremainstheexception,mostorganizations

recognizeitsimportanceandaretakingstepstoformalizeit.

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Thedatarevealaconsistentpattern:maturegovernanceisstronglyassociatedwithbetteroutcomesacrossmultipledimensionsofAIadoptionandsecurity.

Governancematurityisalsotiedtoleadership

awarenessandorganizationalconfidence.Among

organizationswhoseboardsfullyunderstandAI’ssecurityimplications,55%have

comprehensivegovernancepolicies.Those

withestablishedgovernancealsoreporthigher

confidenceinprotectingAIsystems—48%

describethemselvesasconfident,comparedto

23%withpartialguidelinesand16%still

developinggovernance.Theseresultsshowthat

formalgovernancehelpsalignleadershipvisibility,riskunderstanding,andoperationalassurance.

Theconnectionextendstoworkforcereadinessaswell.

Sixty-fivepercentof

organizationswith

comprehensivegovernance

policiesarealreadytraining

staffonAItools,whilejust27%withpartialpoliciesand14%with

developingpoliciesaredoingthesame).TrainingisakeyenablerofresponsibleAIadoption,andthesenumbersindicatethatgovernancemayhelpmoveorganizationsfromawarenesstoaction—ensuring

staffknowhowtouseAItoolssecurelyandeffectively.

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Finally,robustgovernancemayhelporganizationsavoidthe

riseof“shadowAI

”(unsanctionedor

unmanagedAIusethatintroducescomplianceanddataprivacyrisks).Asorganizationsformalizetheirgovernance,AIadoptionbecomesencouragedandstructuredratherthanrestricted,reducingthe

incentiveforemployeestouseunapprovedtools.ThisapproachcontrastswithearlycloudandSaaSadoptioncycles,wherealackofgovernanceoftenledtouncontrolleduseandsecurityblindspots.

ThesefindingshighlightthecentralroleofgovernanceinadvancingAIsecuritymaturity.Organizations

thatinvestearlyincomprehensivegovernanceframeworksarebetterpositionedtoinnovateresponsibly,maintainleadershipalignment,andbuildstaffconfidence.Governanceprovidesthefoundationfor

sustainableAIadoption,bridgingthegapbetweenenthusiasmandexecution,andensuringthatinnovationmovesforwardsecurely.

KeyFinding2:

SecurityBecomesanEarlyAdopterofAI-

ShiftFromLaggingtoLeading

Thisyear’sresultssignalaturningpoint:securityteamsarebecomingearlyadoptersofAI,notfollowers.Historically,securityfunctionshavefocusedonsecuringimplementationsofemergingtechnologies.

However,the‘AIforsecurity’usecaseissocompelling,comparedtopasttechnologies,thatapparently

hasincreasedtheappetiteforexperimentationwiththenewtechnologyandthisinturnwillhelp

acceleratethematurityof‘SecuringAI’.Infact,13%oforganizationsreportthatsecurityisresponsibleforadoptionofAI.Inthisnewparadigm,securityhasanopportunitytobeembeddedinAIadoptionrather

thananafterthought.

Nearlyhalfoforganizations(48%)report

thattheyhavealreadytestedAIcapabilitiesinsecurity,andanother44%plantodosowithinthenextyear.Thismeansthatover90%areat

leastexploringhowAIcanimprovedetection,

investigation,orresponseprocesses.The

numbersareevenmoreencouragingforagenticAI—autonomousorsemi-autonomoussystemsusedforincidentresponse,redteaming,or

adaptiveaccesscontrol.Nineteenpercentare

alreadyusingthesetools,andanother47%plantoadoptthemwithinthenextyear.Withonly10%reportingnoplanstoinvest,thisrepresentsa

majorinflectionpoint:AIisnotjustafutureconceptforcybersecurity,itisbecominga

near-termoperationalreality.

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ThegrowthinAIuseforsecurity

standsinsharpcontrastto

2024,whenresourcelimitations

andstaffingshortageswerethe

mostfrequentlycitedbarriersto

AIimplementationsinsecurity.

Ayearago,athirdof

organizationssaidskillgapsand

lackofknowledge.Thecurrent

resultssuggestthat

organizationshavemade

tangiblemovementtoward

implementation:90%are

activelyprovidingor

planningacombinationof

generalsecurityawareness

andcybersecurity-focusedtrainingforAItools.

ConfidenceinusingAIinsecurityisalsorising,

particularlyamongorganizationswith

comprehensivegovernanceframeworks—54%ofthosewithformalgovernancepolicies

reportconfidenceintheirabilitytoleverageAIinsecurity,comparedtojust25%among

thosewithpartialguidelines.

Theimplicationsofthischangearesignificant.Security’searlyembraceofAIcouldhelpclose

long-standinggapsbetweensecurityandoperations,creatingasharedunderstandingofthe

technologiesdrivingbusinessinnovation.AsAIcontinuestotransformdigitalenvironments,securityprofessionalswhouseAIthemselveswillbebetterpositionedtounderstanditsrisks,capabilities,andoperationaldependencies—makingthemmoreeffectivepartnersacrosstheorganization.

ThesefindingssuggestthatAIinsecurityhasreachedaninflectionpoint.Afteryearsofbeing

cautiousfollowers,securityteamsarenowamongtheearliestadoptersofAI,demonstratingboth

curiosityandconfidence.Thisproactiveposturenotonlyimprovesdefensivecapabilitiesbutalso

reshapestheroleofsecurity—fromafunctionthatreactstonewtechnologies,toonethathelpsleadandshapehowtheyaresafelydeployed.

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KeyFinding3:

EnterpriseLLMAdoptionAccelerates

TowardaMulti-ModelFutureDominatedby

aFewProviders

Largelanguagemodel(LLM)adoptionhasmovedfromexperimentationtoenterprise-scaledeployment,markingamajorinflectionpointintheevolutionofAIstrategy.Morethanhalfoforganizations(54%)reportusingpublicfrontiermodelssuchasGPT-4,Claude,orGemini,whilenearlyhalf(47%)areusingvendor-hostedprivatemodelsthroughserviceslikeGoogleVertexAI,AzureOpenAI,orAmazon

Bedrock.Another44%areleveragingself-hostedoropen-sourcemodelsintheirowncloudoron-premenvironments,andjust12%reportnoplanstouseLLMs.

In2024

,only22%oforganizationswereactivelyusinggenerativeAIand55%werestillplanningforadoption.Oneyearlater,thatintenthasclearly

translatedintoaction.GenAIhasshiftedfromaforward-lookinginvestmenttoanoperationalcapability.

Thisexpansion,however,isnotevenlydistributed.Adoptionisrapidlyconsolidatingaroundasmall

numberofmajorproviders.GPT(OpenAI)leadswith70%oforganizationsreportinguseorevaluation,followedbyGemini(Google)at48%,Claude(Anthropic)at29%,andLLaMA(Meta)at20%.Together,these“BigFour”accountforthevastmajorityofenterprisedeployments,signalinganecosystem

increasinglydefinedbyahandfulofdominantplayers.Theconcentrationofadoptionechoesearlierpatternsseenincloudcomputing,whereearlyinnovationgavewaytoconsolidationaroundlarge

hyperscalers.

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Organizationsalsoreportusinganaverageof2.6differentmodels,suggestingthatmanyarepursuingamulti-model.Ratherthanstandardizingonasingleplatform,theyarecombiningdifferentmodelsforspecificbusinessusecases.Thismirrorsbroadercloudstrategiesthatblendpublic,private,multi,and

hybridenvironments—allowingorganizationstobalanceinnovation,datagovernance,andrisk.

ThesetrendsillustrateapivotalmomentinenterpriseAImaturity.LLMsarenolongeranemerging

technology;theyarebecomingfoundationaldigitalinfrastructure.Yetwiththatgrowthcomesnew

concentrationrisks,asdependenceonasmallnumberofprovidersintroducespotentialchallengesinresilience,interoperability,andgovernance.AsorganizationscontinuetointegrateLLMsintocore

operations,diversificationstrategies,riskframeworks,andopenstandardswillbeessentialtoensuringthatthenextphaseofAIadoptionisnotonlyscalablebutalsosustainableandsecure.

AsLLMsbecomefoundationalinfrastructure,organizationsnowfacethechallengeofsecuring

increasinglycomplex,multi-modelenvironments.

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KeyFinding4:

LeadershipEnthusiasmforAIOutpaces

UnderstandingofPotentialSecurityRisks

WhileAIadoptionhas

acceleratedacrossthe

enterprise,manyleadersremainmoreenthusiasticaboutits

potentialthanawareofitsrisks.Themajorityofrespondents

(72%)areneutralorlack

confidenceintheir

organization’sabilityto

executeasecuritystrategyforAI,while51%areneutraland21%saytheyarenotconfident.In2024,just4%saidtheywerenotconfidentandamajority

ratedthemselvesconfident

(25%)orveryconfident(26%).

Thesemoderateconfidence

levelssuggestthatasAI

systemsmovefrompilottoproduction,organizationsarerecognizingthedepthofthesecuritychallenge—andrealizingtheymaynotyethavetheskillsorresourcestomeetit.

Atthesametime,leadershipremainsheavily

investedinadvancingAIadoption.In2024,82%oforganizationssaidtheirexecutiveleadershipwas

activelypushingforAIinitiatives.While70%of

organizationsreportmoderatetofullleadership

awarenessofAI’ssecurityimplications,this

awarenessunderstandablyremainsaworkin

progressgiventhespeedoftechnologicalchange.

ExecutiveenthusiasmforAIcontinuestooutpaceconfidenceinmanagingitsrisks,underscoringtheimportanceofstrengtheninggovernancecapabilitiesovertime.

Thesefindingsrevealacriticalinflectionpointinorganizationalreadiness.AIadoptionhasbecomea

board-levelpriority,butunderstandingitssecurityimplicationshasnotmaturedatthesamepace.To

closethisgap,leadershipmustevolvefrombeingchampionsofAIinnovationtostewardsofAI

risk—fosteringdeepercollaborationwithsecurityteams,investinginspecializedexpertise,andintegratingAIgovernanceintoenterpriseriskmanagement.Partofthisuncertaintymayalsostemfromstill-evolvingownershipstructuresaroundAIdeploymentandprotection.

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KeyFinding5:

ResponsibilityforAIDeploymentIs

DistributedAcrossTeams,butSecurity

OwnershipIsClearlyEmerging

OwnershipofAIwithinorganizationsremainsdistributed,reflectingboththecomplexityof

implementationandtheearlystageofoperationalmaturity.Whenaskedwhichteamisprimarily

responsibleforAIdeployment,20%identifiedadedicatedAIorMLteam,followedcloselybytheITdepartment(19%)andcross-functionalgroups(16%).Theremainderisdividedamongthesecurity

team(13%),seniorleadership(9%),anddatascienceoranalyticsteams(8%).

WhileAIgovernanceresponsibilitiesremaindistributedacrossfunctions,earlysignsofconsolidationmaybeemerging.In2024,74%oforganizationsreportedplanstoestablishteamsdedicatedtogoverningthesecureuseofAI,andmanynowappeartobefollowingthroughwiththeformationofAIandMLteams.

Thistrendsuggeststhattoday’sdispersedstructuresmaymatureintomoreformalizedgovernancemodelsovertime,buttheyhaveyettofully

materializeasthetechnologyisstillintheearlystageofadoption.

Securityresponsibilities,however,appearmoreclearlydefined.Overhalfofrespondents

(53%)saythesecurityteamisprimarily

responsibleforsecuringAIsystems,withanother18%pointingtocross-functionalteamsand11%toIT.Comparedtodeployment

ownership,thisrepresentsstrongeralignmentwithtraditionalcybersecuritystructures.

©Copyright2025,CloudSecurityAlliance.Allrightsreserved.16

Inmanyorganizations,AIsecurityisbeingintegratedintoexistinggovernanceframeworksratherthanhandledseparately—mirroringearliertechnologytransitionssuchascloudandSaaSadoption,wheresecurityteamsgraduallyassumedresponsibilityoncetechnologiesmatured.

Fundingpatternsprovideadditionalinsightintohowaccountabilityisforming.Nearlyhalf(49%)report

thattheChiefInformationSecurityOfficer(CISO)overseesfundingforAIsecuritytools,followedbytheCTO(36%)andCIO(33%).Businessunitowners(25%)andemergingAIleadershiproles,suchasChiefAIOfficers(11%),alsoplayarole—indicatingthatfinancialresponsibilityforAIsecurityissharedbetweenoperationalandstrategicleaders.ThismixreflectsanevolvinggovernancemodelwhereAIsecurityis

treatedasbothatechnicalandbusinessinvestment.

Takentogether,thesefindingsindicatethatorganizationsarestillrefininghowAIfitswithinexisting

operationalandgovernancestructures.Securityownershipissolidifyingunderestablishedteams,butdeploymentandfundingresponsibilitiesremaindiffuse.TheriseofdedicatedAI/MLteamsreflects

progressfromlastyear’sintentionstocreateformalgovernancegroups,butthecurrentfragmentationpointstoanongoingneedforcleareraccountabilityandcoordination.ThefactthatsecurityteamsareassumingprimaryresponsibilitysoearlyinAI’smaturitymaymarkanotableshift—onewheresecurityitselfisbecominganearlyadopter,shapingtheguardrailsforresponsibleAIinnovation.

©Copyright2025,CloudSecurityAlliance.Allrightsreserved.17

KeyFinding6:

UnderstandingAIRiskandClosingSkills

GapsAretheBiggestChallengeswith

SecuringAI

Evenwithclearerownershipemerging,organizationscontinuetofacesignificantchallengesinbuildingtheskillsandriskunderstandingrequiredtosecureAIeffectively.OrganizationsciteunderstandingAIrisks(61%),skillgaps(53%),andlackofknowledgeamongcurrentstaff(52%)asthetop

hurdlestogettingstartedwithsecurityforAIimplementations.

Additionalbarriersincluderegulatoryanddataprivacycompliance(50%),integrationwithexisting

securityinfrastructure(43%),andpracticalconstraintslikecost(29%)andcompute/resourceallocation(26%).LoweronthelistareunderstandingAIbenefits(23%),findingviableusecases(20%),andunsureofAIeffectiveness(14%)—suggestingmostorganizationsseethevalue,butareconstrainedbyrisk

comprehension,skills,andcomplianceexecutionratherthanbylackofbusinessdemand.

Whenaskedtoranktheirtopsecurityconcerns,

organizationsoverwhelminglypointto

sensitivedataexposureastheirprimaryrisk,with52%rankingitastheirmostconcerningissue.Thisfarexceedsallotherrisks—compliancechallengeswerenextatjust16%,followedby

modelintegritycompromise(12%)anddatapoisoning(10%).Farfewerrespondentsviewpromptinjection(5%)ormodeltheft(5%)astop-tierthreats.Ontheoppositeendofthe

©Copyright2025,CloudSecurityAlliance.Allrightsreserved.18

spectrum,modeltheftwasmostfrequentlyrankedleastconcerning(37%),underscoringthat

organizationsarecurrentlymorefocusedondataleakageandregulatoryexposurethanonmoretechnicalortheoreticalAIattackvectors.Theprioritizationofdataandcomplianceriskssuggeststhatmany

organizationsaretreatingAIsecurityasanextensionofexistingprivacyandgovernance

frameworks—reinforcingtheperceptionthatthemostimmediatedangerliesnotonlyinadversarialattacks,butinlosingcontrolofsensitiveinformationthroughAIsystemsandintegrations.

Privacy&SafetyInsight

Fiftypercentofrespondentsciteprivacyandregulatorycomplianceastheirtopchallenge,only21%highlightrisksthataffectmodelreliabilityand

integrity,includingthreatslikedatapoisoningorpromptinjections.Thisrevealsapersistentgapbetweendataprotectionandsafetygovernance.

OrganizationsshouldgetanAIsecurityassessmentanddeterminethebestapproachtoextendtheirprivacycontrolstoincludesafety-by-design

principlessuchascontentintegrityevaluation,hallucinationmitigation,andbiastestingwithinTEVV(Testing,Evaluation,VerificationandValidation)

workflows.Thesesafeguardssupportboth

Google’sSecureAIFramework

(SAIF)

and

CSA’sAIControlsMatrix(AICM)

.

WhilemanypractitionersstillapproachAIworkloadsasanextensionofcloudenvironments,the

underlyingrisklandscapeisshifting.Traditionalcloud-nativeissues—misconfiguration,networkexposure,andaccesscontrolweaknesses—nowintersectwithAI-specificthreatssuchaspromptinjection,

model-outputdataleakage,andmodeldrift.Theserisksintroducebehavioralanddata-flowuncertaintiesthatexceedwhatconventionalcloudcontrolsweredesignedtomanage.Thefindingsshowthat

organizationsrecognizetheirprimaryrisks—especiallyarounddataexposureandcompliance—evenas

theycontinuetobuildtheskills,tools,andgovernanceneededforeffectiveAIsecurity.Extendingexistingprivacyandsecuritycontrolsremainsnecessarybutinsufficient;controls-basedapproachesalonecannotaddressthenon-deterministicandbehavior-drivennatureofAIsyst