2026人工智能如何重塑资产管理研究报告 How artificial intelligence is shaping asset management

MERCER

AMARSHBUSINESS

Howartificial

intelligence

isshapingasset

management

Contents

Executivesummary3

Surveyoverview4

AIintegrationintheinvestmentprocess5

NatureofAIcapaility

7

ResourcingdedicatedtoAIdevelopment

9

BenefitsoservedfromAIintegrationsofar

10

MainarrierstofurtherAIadoption

11

Conclusion13

2

Howartificialintelligenceisshapingassetmanagement

3

Howartificialintelligenceisshapingassetmanagement

Executivesummary

Thiswhitepapersummarizestheresultsofa

Mercersurveyof131assetmanagersconductedinFeruary2026onhowartificialintelligence(AI)iseingintegratedintotheinvestmentprocess.Accordingtothesurveyfindings,theindustry

isinanactiveearly-adoptionphase:morethan

halfoffirmsreportliveAIintegrationinatleast

onestrategy,andasustantialcohortreports

pilotorproof-of-conceptactivity.Firmsreport

thestrongestmeasuraleenefitsinoperationalefficiencyandinthespeed/qualityofinsights,

ratherthaninimprovedreturnsorriskreduction.1

AIadoptiontodayisconcentratedinidea

generation,processingunstructureddata,

andsignalgeneration.Fortradeexecution

andportfolioconstruction,AIutilization

remainsuncommon.TheprimaryarrierstoAIadoptionaredataquality/access,regulatoryandcomplianceconcerns,andsystemsintegration.Respondentsidentifydatagovernanceand

system-levelrisks(includingherding)asthemostsignificantregulatorylindspots.

Keyfindings:

55%

reportAIisintegratedinatleastoneoftheirstrategy’sinvestmentprocesses

18%

havenotyetintegratedAIintoanypartoftheirinvestmentprocess

91%

plantoincreasetheiruseofAIinthenext12months

69%

reportdataconstraintsasa

significantarrierthatpreventsfurtherAIadoptionintheir

investmentprocess

73%

areusingAIforoperationalefficiencyintheirexistingteams(forexample,

automatingroutinetasks)

28%

haveinternallydevelopedAImodels

4

Howartificialintelligenceisshapingassetmanagement

Surveyoverview

TheMercer2026AIinAssetManagementSurvey

wasconductedviaanonlinesurveyinFeruary2026.Responseswereprovidedy131assetmanagers

fromacrosstheworld.

1.Firm-sizedistriutionyassetsunder

managementUSD$,asatDecemer31,2025

5%

22%

21%

21%

21%

$1Bto<$10B$50Bto<$250BLessthan$1B

$250Bto<$1T$10Bto<$50B$1T+

9%

2.Respondents’headquarterslocation

5%

10%

3%

1%

14%

60%

21%

USUKEurope(excludingUK)Canada PacificAsia(excludingPacificand/MiddleEastLatinAmericaMiddleEast

1%

Source:MercerArtificialIntelligenceAssetManagerSurvey,Feruary2026

Source:Mercer,ArtificialIntelligenceAssetManagerSurvey,Feruary2026

RespondentswereaskedaouttheAIintegrationstage,usecasesacrosstheinvestmentlifecycle,thenatureofAIcapabilities,resourcing,datainputs,measurablebenefits,staffeducation,barriers,andregulatorylindspots.

AIintegration

intheinvestment

process

Artificialintelligencehasarguablybecomeanessentialcomponent

ofourdailylives,andasset

managementfirmsarenoexceptiontothistrend.TheadoptionofAIisnolongermerelyatrendthatfirmsfollowtomaintainmarketpresence.Rather,webelieveithasbecome

adecisivefactorforoperational

efficiencyandfasterdecision-

making.Theprimaryobjectiveofthissurveywastogaininsightintohowassetmanagementfirmsare

presentlyincorporatingAIintotheirinvestmentprocesses.

Theassetmanagementindustry

isinanactiveearly-adoption

andscale-upphase:55%offirms

haveintegratedAIinatleastone

strategy’sinvestmentprocess,and27%offirmshaveintegrateditas

apilotorproofofconcept.The

alanceof18%offirmshavenot

yetintegratedAI.WeaskedallfirmswhethertheyplantoincreaseAIuse

intheinvestmentprocess,and91%saidtheydo,sowewouldexpectthe18%figuretodecreasesignificantlyoverthenext12months.

Intermsoftheareasofthe

investmentprocessthatcurrentlyuseAI,thechartelowshows

thatcurrentdeploymentsare

concentratedonupstream,

research-orientedworkflowsandonunlockingvaluefromdata.Amongtheareasthatremainnascentin

AIadoptionaretradeexecutionandportfolioconstruction.

5

Howartificialintelligenceisshapingassetmanagement

3.AreasoftheinvestmentprocessthatuseAIcurrently

Ideageneration/research

Processingunstructuredandexternaldatasets

Signalgenerationandmarkettrendanalysis

Clientreporting

Riskmanagement

Portfolioconstruction

Tradeexecution

49%

27%

24%

4

0%

33%

27%

31%

24%

45%

16%

27%

57%

15%

16%

69%

13%

10%

77%

7%

3%

90%

■Alreadyintegrated■Pilot/proofofconceptonly■Notapplicable

Source:MercerArtificialIntelligenceAssetManagerSurvey,February2026

6

Howartificialintelligenceisshapingassetmanagement

NatureofAIcapability

AIisbeingusedpredominantlytoseek

improvementsinproductivityandaugmenthumandecision-making(co-pilot).

73%offirmsareusingAItoimproveoperationalefficiencywithintheirexistingteams(forexample,automatingroutinetasks),while68%offirms

goeyondthat,usingAIasapartnerinthe

investmentprocess(forinstance,providing

insightsandanalysis).Fewfirms(only5%)entrustAIwithautonomousorsemi-autonomous

decisionauthorityininvestmentdecisionssuchastradeorinvestmentrecommendations.

73%offirmsare

usingAItoimproveoperationalefficiencywithintheirexistingteams

Themarketcurrentlyreliesheavilyonvendor

solutions,with63%offirmsusingoff-the-shelfAItoolsand51%offirmsapplyingproprietary

tuningtovendormodels.Fullyin-houseplatformuildsarelesscommon(28%),reflectingcost,

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Howartificialintelligenceisshapingassetmanagement

complexity,andspeed-to-marketconsiderations.Only9%offirmsarecurrentlyoperatingafully

proprietaryAIplatform.Whileunderstandale

fromaresourcingandcostperspective,thisdoespotentiallyraisetheissueofvendor(andperhapsevenmodel)concentrationrisk(identifiedasa

concerny9%ofrespondents—seepage12)

4.NatureofAIcapaility(multiple

answerspermitted;percentagesasedonthetotalnumerofassetmanagers)

Weusevendor/off-the-shelfAItools

63%

Weusevendortoolswithproprietarytuningorcustommodelconfigurations

51%

WehaveinternallydevelopedAImodels

28%

WeoperateafullyproprietaryAIplatform/architecture

9%

Source:Mercer,ArtificialIntelligenceAssetManagerSurvey,Feruary2026

8

Howartificialintelligenceisshapingassetmanagement

Intermsofthetypesofdatausedbyasset

managementfirmsintheirAImodels,

unstructuredtexthasemergedasamajorinputalongsidetraditionaltime-seriesandfundamental

data.Firmsblendinternalandvendorfeeds,and

ameaningfulminorityusesalternativedata.

5.DatatypesusedinAImodels(multiple

answerspermitted;percentagesbasedonthetotalnumberofassetmanagers)

Unstructuredtextandtranscripts

68%

Traditionalfinancialdata(prices,fundamentals)

66%

Proprietaryinternaldata

61%

Vendorprovideddata

58%

Alternativedata(satellite,socialmedia,ESG,forexample)

41%

Other

4%

Source:Mercer,ArtificialIntelligenceAssetManagerSurvey,February2026

9

Howartificialintelligenceisshapingassetmanagement

ResourcingdedicatedtoAIdevelopment

Accordingtothesurvey

results,mostfirms’

organizationalstructuresincludesmall,focusedAI

teamsembeddedwithin

investmentfunctions.57%offirmsreportonetofivefull-timeemployees(FTEs)dedicatedtoAIworkwithininvestmentteams.This

suggeststhatmanyAI

initiativesarepragmatic,use-case-ledandmayrelyonvendorpartnershipsorcentralizedITsupport.

6.NumerofFTEsdedicatedtoAI

development,implementation,oroversight

0

18%

1-5

57%

6-10

10%

11-20

7%

21-50

5%

50ormore

2%

Source:Mercer,ArtificialIntelligenceAssetManagerSurvey,Feruary2026

Regardingemployeeeducationandcapailityuilding,56%offirmshaveadedicated

platformorprogramtoeducateexisting

employeesonutilizingAIintheirrespectiveroles.Firmsrecognizethatadoptionrequiresculturalandcapailityshiftsandsomeareinvestingintrainingandupskilling.

10

Howartificialintelligenceisshapingassetmanagement

BenefitsobservedfromAIintegrationsofar

Firmshavestartedto

evaluatetheiruseofAI.Theclearestmeasurablegainssofararereportedtobeefficiency(69%)andimprovedinsights(55%).EvidencethatAIhas

improvedinvestmentreturns(8%)orreducedportfoliovolatility(8%)islimitedamong

respondentstodate.

7.MeasuraleenefitsoservedfromAIintegrationsofar(multipleanswerspermitted;percentagesasedonthetotalnumerofassetmanagers)

Enhancedoperationalefficiency

69%

Fasterorhigher-qualityinsights/decisionmaking

55%

Expandedcapabilities

40%

Reducedcosts

24%

Betterclientengagement

19%

Other

11%

Improvedreturns

8%

Reducedrisk/volatility

8%

Source:Source:Mercer,ArtificialIntelligenceAssetManagerSurvey,Feruary2026

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Howartificialintelligenceisshapingassetmanagement

Mainbarriersto

furtherAIadoption

Therearestillseveral

barriersthatpreventfirms

fromfurtheradoptingAIintheirinvestmentprocesses.Dataconstraintsand

regulatoryconcernsarethedominantfrictions,with69%and59%offirmsreportingso,respectively.Systems

integrationandtrustin

modeloutputsarematerial.Firmsalsopointoutthe

costofimplementationandsecurityconcerns,aswellastalentshortages,butthisisalessfrequentlycitedconcern,likelyreflectingvendor

usageortargetedhiring.

8.MainarrierstofurtherAIadoptionintheinvestmentprocess(multipleanswerspermitted;percentagesasedonthe

totalnumerofassetmanagers)

Dataquality/access

69%

Regulatoryorcomplianceconcerns

59%

Integrationwithexistingsystems

48%

EfficacyofAImodels

39%

Modelexplainability

31%

Costofimplementation

27%

Other2

20%

Talentshortage

15%

Source:Mercer,ArtificialIntelligenceAssetManagerSurvey,Feruary2026

Intermsofthelargestregulatoryblindspots

inhowAIisbeingusedintheinvestment

industrytoday,firmsareconcernedthatcurrent

regulatoryframeworksmaynotadequately

coverdatagovernanceorsystem-levelrisk

andherdingbehaviors.Accountability,vendorconcentrationrisk,andtransparencyarealso

relevantblindspotshighlightedbyfirms.

9.Largestregulatoryblindspotsin

howAIisbeingused(multipleanswerspermitted;percentagesbasedonthe

totalnumberofassetmanagers)

Datagovernance

31%

System-levelriskandherdingbehaviour

24%

Other³

16%

Accountability

16%

Vendorconcentrationrisk

9%

Non-staticmodels

4%

Source:Mercer,ArtificialIntelligenceAssetManagerSurvey,February2026

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Howartificialintelligenceisshapingassetmanagement

Conclusion

Thesurveyshowsassetmanagersareinanactive

early-adoptionphasewithAI:amajorityhaveintegratedAIintoatleastonestrategy,andmostplantoincreaseuse.

Adoptionisconcentratedupstream—inidea

generation,processingunstructureddata,and

signalgeneration—wheremeasuralegainshavesofareenstrongestinoperationalefficiency

(reportedyroughlysevenin10firms)andfaster,higher-qualityinsights(reportedymorethan

half).Bycontrast,trustinAItomakeautonomousinvestmentdecisionsremainslimited.

Implementationpatternsarepragmaticand

vendor-led.Mostfirmsrelyonoff-the-shelftools,witharoundhalfapplyingproprietarytuningtovendormodels.Onlyasmallminorityoperate

fullyproprietaryplatforms.Small,emedded

AIteamsarecommon,andunstructuredtext

alongsidetraditionalfinancialandinternaldatadominatemodelinputs.Theprincipalfrictions

toroaderadoptionaredataqualityandaccess,regulatoryandcomplianceconcerns,andsystemsintegration.Atthesametime,firmsflagdata

governanceandsystem-levelrisks(includingherding)asprominentregulatorylindspots.

Amongotherinitiativesintheinvestmentsusiness,wearedevelopingan

AI-poweredmanagerresearchtooltostreamlinetheprocessingofstructuredandunstructured

dataandsupportthedraftingofresearch

documentsforothinvestmentandoperationalduediligence.Consistentwiththemajorityofrespondents,ourapproachlayersproprietary

13

Howartificialintelligenceisshapingassetmanagement

tuningontopofavendormodel,usingMercer’shistoricalresearchandduediligenceguidance,reflectingtheprevalent“co-pilot”roleAIplaysinpracticeandhelpingensurethattheMercerresearchDNAremainscentraltoourwork.

Inadditiontothemanagerresearchtool,

MercerisemeddingnewAI-enaledoperatingpracticesintoourcolleagueworkflowsacross

ourusinesses,withtheintentiontohelpenaleourspecialiststofocustheirtimeonhigh-impactjudgement,interpretation,andclientpartnership.

Wealsohaveastrongfocusontraining,withdedicatedtrainingmodulesand

cross-teamworkinggroupsencouragingtheuseofAIandprovidingguidance

totheroaderteamonusecases.

Takentogether,theevidencefromthesurvey

leadstothreeclearfindings.First,AItodayis

principallyanaugmentationtoolthatcould

supportproductivityandinsightratherthan

asourceofautonomousinvestmentdecision

making.Second,thedominantadoptionmodelisvendor-centered,withproprietaryadaptationsandmodestteamresourcing.Third,achieving roaderadoptionmaydependonaddressing

dataquality,governance,andsystem-levelrisksaseducationandintegrationscaleacrossfirms.

Methodology

TheMercer2026AIinAssetManagementSurveywasconductedviaanonlinesurveyinFebruary2026.Responseswereprovidedby131asset

managersfromacrosstheworld.Itisimportanttorecognizethatsurveyresultsaresubjectto

inherentlimitationsanduncertainties.Thesurveyresultsmaynotcaptureallrelevantfactorsor

marketconditions.Wegatheredinformation

througharequestsenttoourextendednetworkofmanagerrelationships.Itisimportantto

notethatrespondentsdidnotreceiveanyformofcompensationtocompletethesurvey.

Endnotes

1AllresponsesaresourcedfromMercer'sArtificial

IntelligenceAssetManagerSurveyconducted

inFebruary2026,basedonresponsesfrom131

participants.Responseswereprovidedbyglobal

assetmanagers.Itisimportanttonotethatthe

participantsdidnotreceiveanyformofcompensation.

Itisimportanttorecognizethatsurveyresultsare

subjecttoinherentlimitationsanduncertainties.The

surveyresultsmaynotcaptureallrelevantfactors

ormarketconditions.Theseresultsshouldnotbe

construedaspersonalizedinvestmentadvice.

2Other:Securityandprivacyconcerns,governance

andorganizationalreadiness,culture,trackingand

meetingchangingregulatoryrequirements,applicabilityasa"judgmenttool,"addressinginfrastructure(data

platforms,APIframeworks),constrainedresources(smallAIteam),difficultyembeddingAIintobusinessprocesses,bandwidth,hallucinations,andmore.

3Other:Regulatoryconcerns,manydifferentAI

regulationsglobally,mixofemergingrisks,accountability,transparency,confidentialityandprivacyrisk,accuracy

risk,biasrisk,intellectualpropertyrisk,vendor

concentrationrisk,lackofcleardisclosurerequirementsforAIuse,distinguishingbetweenoperationalefficiencytoolsinvestmentdecisionsupport,andmore.

14|Howartificialintelligenceisshapingassetmanagement

Authors

BeverleySharp

GlobalManagerResearchLeader

beverley.sharp@

AnaTavaresVieira

SeniorAssociate,ManagerResearch

ana.tavares.vieira@

Contactus

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