2025 AI脉搏调研报告（第三卷）：从自动化迈向自主化

FromAutomationtoAutonomy

ThecapabilitiesandcomplexitiesofAIagents

Tableofcontents

03Executivesummary

07Futureexpectationsforautonomy

09Thecapabilitiesofdecision-makingAIagents

10ThesprinttoonboardAIagents

12AIagents:Transformingbusinessfunctions

13

Integrationplanning:Unlocking

organisationalstrategies

15

AutonomyambitionversusAIreality:

ClosingtheagenticAIreadinessgap

17Surveydemographicsandmethodology

18AboutProtiviti

3

AIPULSE|Executivesummary

Executivesummary

It’shappeningnow—fastandfuriously.TheAIrevolutionisacceleratingtowardssystemscapableofbothcollaboratingwithhumansinunprecedentedwaysandmakingautonomous

decisions.Protiviti’slatestAIPulseSurveyshowsnearlyoneinfourorganisations(23%)hasalreadyintegratedagenticAI1andmulti-agentAI2intocoreoperations,andanother27%plantodosowithinsixmonths.

MostAIagentsalreadyorsoon-to-bedeployedareoperatingwithinclearlydefinedareasofresponsibility,whereorganisationsbalanceautonomywithoversight.Whilethesurveyshowsmost

respondentscurrentlyfavoursemi-autonomousAIagents,thispreferredlevelofagentcomplexitycouldbeshort-lived,giventhepaceofchange.Nearlyoneinfive(20%)respondentshavealreadyimplementedorplantodeployfullyautonomousagents,withthevastmajorityexpectingtodosowithinthenextyear—faroutpacingthosewithlonger-termtimelinesofonetofiveyears.

Agentsofchange

Decisionsonwhen,whereandhowtoimplementagenticAIcapabilitiesarecloselyalignedwithanorganisation’slevelofmaturityofAIadoption.Forexample,organisationsatthehighestmaturitylevelsofAIadoptionarepursuingearlyintegrationofagenticAIaggressively,comparedtothoseatthelowerlevels.Itonlymakessense.Atthemorematurelevels,organisationsaremotivatedbecauseAIisalreadyenhancingperformanceandscalability,andAIreturnoninvestmentsisexceedingexpectations.Thecentralmessagehere:ExperiencewithAIbuilds

confidenceinitscapabilities.

Attheexecutiveleadershiplevels,C-suiteandboardmembersaremoreinclinedtosupportAI-drivendecision-makingthanemployeesatlowerlevels.LeadershipiseagertouseAItovalidatehigh-stakesdecisions,especiallythoserelatedtofunctionslikeIT,customerserviceandoperations,whichareripeforautomation,optimisationandintelligentdecision-making.

Nodoubt,businessleaderswillneedhelpimplementingagenticAI—andtheyknowittoo.Evenorganisationsatthemostmaturelevelsarebalancinginternalinnovationwithexternalpartnershipsandplatformintegration.Thiscollaborativeapproachreflectsapragmaticunderstandingofthechallengesahead.

AswewrapupourseriesofAIPulsesurveys3for2025,therearekeymessagestoremember:OrganisationsaregenerallyambitiousaboutAIsystems,includingagenticAI,butmanyarestillbuildingthegovernance,infrastructure,skillsetsandethicalframeworksneededtobeeffective.It’sessentialthattheyremaingroundedintherealitiesoftechnologicalmaturity,regulatoryconstraintsandtheimportanceofhumanoversight.Speedandagility,investmentincleanandsecuredata,andeffectivegovernancewillremainkeygoingforward.

1AgenticAIreferstoAIsystemsdesignedtoactasautonomousagents,capableofmakingdecisions,takingactionsandinteractingwiththeirenvironmentorusersbasedongoals,contextanddata.

2Multi-agentAIinvolvesmultipleautonomousagentsworkingcollaborativelyorcompetitivelytosolvecomplexproblems,simulateenvironments,ormanagedistributedtasks.

3ProtivitipublishedtheseAIPulsesurveysearlierthisyear:

FromExplorationtoTransformation:WhatAISuccessLooksLike

and

FromDataConfusiontoAIConfidence:DataIstheFoundationofTrustworthyAI

.

AIPULSE|Executivesummary

Notablefindings

01

Semi-autonomousAIagentsarethecurrentpreferredchoice

Acrossindustries,38%prefersemi-autonomousagentsorsystemsactingwithindefinedlimits.

•OrganisationsinadvancedAIstagesaremoreinclinedtowantfullyautonomousagents.TheirgrowingconfidenceinAItranslatestoagreaterwillingnesstodelegate

complextaskstoautonomoussystems.

04

AImaturitydefinesagenticAIpreparedness

AImaturityisastrongpredictorofagenticAIreadiness,

withstages4and5organisationsleadingthechargeinthecategoriesofalreadyintegratedandplannedintegrationwithinsixmonths.

•Early-stageorganisationsareshowinggrowinginterest

inexploringAIagentsbutplanningslowerexecution.

02

Organisationsarealreadyseeingthebenefits

AgenticAIisstreamliningdecision-making,automatingroutinetasksandenhancingreal-timeinsights.

•Seventy-sevenpercentofthemostmatureorganisationsareusingorexpectAIagentstomanagerepetitivetasks.

•C-suiteandboardmembersaremoresupportiveof

handingdecision-makingprocessestoAIagents,evenasoperationalteamsremaincautious.

05

ApproachestoagenticAIdevelopmentvary

Early-stageorganisationsareactivelyengagingvendorpartnersandopen-sourceecosystemstohelptransitionfromexplorationtopilotimplementation.

•Morematureorganisationsareemployingnearlyallavailableapproaches,includinginternaldevelopmentteams,customsolutionsandecosystemparticipation.

03

UsesvarybasedonAImaturity

Morematureorganisationsareexpandingtheuse

andcompliance-drivenfunctions.Attheinitialand

ofagenticAIintostrategicplanning,frauddetection

experimentalstages,operationalandcustomer-facing

functionsaretheprimaryfocus.

4

5

AIPULSE|Executivesummary

Figure1:Stagesofmaturity:WhereorganisationsareintheirAIjourney

Stage1:InitialStage2:ExperimentationStage3:DefinedStage4:OptimisationStage5:Transformation

7%30%28%25%10%

OrganisationrecognisesAI’spotentialbenefitsbuthas

limitedunderstandingand

nostrategicinitiatives.Key

performanceindicators(KPIs)havenotyetbeendefined.

Organisationhasinitiatedsmall-scaleAIprojectsandpilotprogramstoassess

feasibilityandbenefits.

Organisationhasintegrated

AIsolutionsintoexisting

businessprocesses,enhancingoperationalefficiencyand

decision-making.

OrganisationhasoptimisedAIsystemsforperformanceandscalability,withcontinuous

improvementsbasedondatafeedback.

AIdrivessignificantbusinesstransformationatthe

organisation,creatingnewopportunitiesandreshapingtheindustrylandscape.

ConsistentwithProtiviti’stwopriorAIPulsesurveys,thelargestshareoforganisationsisinstage2,withasteadyprogressiontowardstage4.Only10%haveachievedfulltransformation,while7%remainattheinitialstage.Comparatively,surveys1(April)and2(June)showedthatthenumberoforganisationsatfulltransformationwas8%and7%,respectively.

6

AIPULSE|Executivesummary

Figure2:AgenticAIcomplexitylevels:AbreakdownofthecapabilitiesorganisationsseekfromAIagents

AgenticAIComplexity

Definition

%ofRespondents*

Basictaskautomation

Agentsfollowpredefinedworkflowswithlimiteddecision-making.

12%

Context-awareassistants

Agentsadapttouserinputandcontextbutrequirehumanoversight.

25%

Semi-autonomousagents

Agentsmakedecisionsandtakeactionswithinboundeddomains.

38%

Fullyautonomousagents

Agentsindependentlyplanandexecutemultisteptaskswithminimalhumanintervention.

19%

Semi-autonomousagentsarethemostpreferredcapabilitysoughtbyrespondents,reflectingastronginterestinAIagentsthatoperatewithhumanoversightinadefinedareaofresponsibility.

*Roughly6%ofrespondentsareundecidedonthelevelofcomplexitytheyenvisionfortheirAIagents.

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AIPULSE|Futureexpectationsforautonomy

FutureexpectationsforAIautonomy

WhatlevelsofcomplexityandautonomydoesyourorganisationenvisionforitsAIagentsinthefuture?

Moreorganisationsfavoursemi-autonomousoverothercapabilitylevels,indicatinga

preferenceforsystemsthatcanactindependentlywithindefinedlimits.Incontrast,fewer

than20%ofallrespondentsanticipateashifttowardfullyautonomousagents,alonger-termaspiration.

Onthelevelofcomplexityofagents,veryfewrespondentsselected“undecided,”indicatingthatmostorganisationshaveaclearvisionofwhatroletheywantthetechnologytoplay.

However,17%ofgovernmentrespondentschose“undecided,”highlightingadegreeofcautioninpublicsectorplanning.

Maturitydrivesambition

OrganisationsatmoreadvancedstagesofAIadoption—specificallythoseinstages4

and5—aremorelikelytoimplementfullyautonomousagents.Context-awareassistants,atransitionalphasetowardautonomy,arewidelyusedorpreferredinstages2and3.

ThissuggeststhatascompaniesgainexperienceandconfidenceinAIcapabilities,their

Figure3:AgenticAIcapabilitypreferencesbystagesofmaturity

Stage1:Initial

41%19%14%11%15%

Stage2:Experimentation

16%39%29%7%9%

7%25%52%12%

4%

Stage3:Defined

1%

6%18%46%29%

Stage4:Optimisation

2%

5%6%25%62%

Stage5:Transformation

BasictaskautomationContext-awareassistantsSemi-autonomousagents

FullyautonomousagentsUndecided

8

AIPULSE|Futureexpectationsforautonomy

willingnesstodelegatecomplextaskstoautonomoussystemsincreases.

Industry-specificreadiness

•A&D(aerospaceanddefense),FS(financialservices),M&D(manufacturinganddistribution)andE&U(energyandutilities)showthestrongestsupportforsemi-autonomousagents.

•TMT(technology,mediaandtelecom)leadsamongtheindustrygroupssupportingfullautomation.Thegroup’sinnovation-drivenandinfrastructure-readysectorsaremosteagertoautomatecomplex,multisteptaskswithminimalhumanintervention.

•Context-awareagentsarefavouredinsectorswherehumanoversight,regulatorycompliance,andpersonalisationaremostcritical.Governmentandhealthcare,

understandably,areleadersinthiscategory.

Leadershipperspectivesonautonomy

•AmongboardandC-suiteexecutives,37%expecttointegratesemi-autonomousagents,while31%foreseefullyautonomousagents.

•Meanwhile,directors,managersandvicepresidentshaveamoreconservativeviewofAIagents,withonly16%expectingfullautonomy,possiblyduetotheircloserproximitytooperationalrisksandimplementationchallenges.

Figure4:Industryexpectationsforusingsemi-autonomousagents

49%

A&D

FS

45%

M&D

44%

E&U

42%

Healthcare

39%

CPG+Retail

38%

TMT

33%

Government

23%

9

AIPULSE|Thecapabilitiesofdecision-makingAIagents

Thecapabilitiesofdecision-makingAIagents

TowhatextenthaveordoyouexpectagenticAIsystemstoaffectthedecision-makingcapabilitiesofyourorganisation?

TheanticipatedbenefitsofAIagentsondecision-makingcapabilitiesvarysignificantlyacrossindustries,organisationalmaturitylevelsandleadershiproles.

Automatingroutinedecisions

OneofthemostwidelyexpectedimpactsofagenticAIistheautomationofroutine

decision-making.Thisisparticularlynoticeableamongstage5organisations,where77%ofrespondentsexpectAItotakeoverrepeateddecisiontasks.However,thisexpectationis

Priorities

notablylowerinthegovernmentandM&Dsectors,likelyduetoregulatoryconstraintsandoperationalconservatism.

Enhancingreal-timeinsights

Acrossnearlyallindustries,thereisastrongconsensusthatagenticAIwillimprovereal-timedataprocessingandinsightsgeneration.Thiscapabilityisespeciallyemphasisedinhealthcareandtechnology.

Figure5:IndustryexpectationsofAIagentdecision-makingcapabilities

A&D

ConsumerPackagedGoods+Retail

E&U

FSI

Automatedecision-makingprocesses

Gov

Improvereal-timedecision-making

Healthcare

Improvereal-timedecision-making

M&D

Improvereal-timedecision-making

TMT

Improvereal-timedecision-making

1

Improvereal-timedecision-making

Improvereal-timedecision-making

Improvereal-timedecision-making

2

Automatedecision-makingprocesses

Enablepersonal

services

Automatedecision-

makingprocesses

Improvereal-timedecision-making

Streamlineresourceallocation

Automatedecision-makingprocesses

Supportcomplianceandriskmanagement

Automatedecision-makingprocesses

3

Streamlineresourceallocation

Automatedecision-

makingprocesses

Streamlineresourceallocation

Enablepersonalservices

Automatedecision-makingprocesses

Enablepersonalservices

Streamlineresourceallocation

Facilitatecomplexproblem-solving

Enablepersonalservices

AIPULSE|ThesprinttoonboardAIagents

ThesprinttoonboardAIagents

Whatisyourorganisation’sexpectedtimeframeforintegratingagenticAIand/ormulti-agentAIsystemsintoyourcoreoperations?

Thesurveyshowsstrongnear-termfocusonintegratingagenticAI,withonly5%oftotalrespondentstargetingathree-to-five-yearhorizon—alifetimeintoday’sfast-evolvingAIlandscape.Clearly,mostorganisationsrecognisetheurgencyandstrategicpriorityofadoptingagenticAIcapabilitiessoonerthanlater.WhensegmentedbyAIadoptionstageormaturitylevel,thedatarevealsanuancedprogression:

•Stage5organisations—thosealreadyleveragingAIforindustry-shapinginnovation—areunsurprisinglyahead,with83%reportingthattheyhavealreadyimplemented,orplanningtodosoin6months,agenticAIormulti-agentAI.

•Stage4showsthehighestnear-termmomentum,with70%alreadyintegratedorareplanningintegrationwithinsixmonths,andanother17%areplanningtodosowithin12months.TheseorganisationsareaggressivelyscalingAIforperformanceandstrategicimpact.

•Stage3organisationsareactivelyexpandingAIacrossbusinessfunctions,with29%planningagenticAIintegrationwithin12monthsand19%planningtodothesamewithinonetotwoyears,indicatingabalancedanddeliberateapproach.

•Stage2reflectsgrowinginterest,with36%targetingintegrationwithin12monthsand28%withinonetotwoyears,suggestingintentbutslowerexecution.

•Stage1organisationsremaincautious,withmorethanhalfexpectingtointegrateAIagentswithinonetotwoyearsorthreetofiveyears,highlightinglimitedreadiness.

Fromanindustryviewpoint,technologyandhealthcaresectorsareleadinginreadiness,withasignificantsharehavingalreadyimplementedagenticAI.

Financialservices,especiallyinassetandwealthmanagement,showstrongmomentum,whileretailandmanufacturingarecatchingup,withmanyplanningintegrationswithinthenextsixto12months.

Incontrast,organisationsinthegovernmentandeducationsectorsaremorecautious,oftencitinglongertimelinesorongoingevaluations.

10

AIPULSE|ThesprinttoonboardAIagents

Innovation-drivensectorsoftenhavethetechnical

talent,agileprocessesandcloud-nativeinfrastructuretosupportrapidagentic

AIadoption.Sectorsthattendtomoveslowerare

thoseheavilyrelianton

budgetcycles,procurementprocessesandpublic

accountability.

Figure6:AgenticAIintegrationtimelinebystagesofmaturity

29%

20%

33%

18%

Stage1:Initial

30%

36%

28%

6%

Stage2:Experimentation

49%

29%

19%

3%

Stage3:Defined

70%

17%

10%

3%

Stage4:Optimisation

83%

8%

6%

3%

Stage5:Transformation

Alreadyintegrated+Withinthenext6monthsWithinthenext12months

Within1-2yearsWithin3-5years

11

12

AIPULSE|AIagents:Transformingbusinessfunctions

AIagents:Transformingbusinessfunctions

Inwhatfunctionsorareasofyourbusinessareyoucurrentlyusing,pilotingorexpectingtouseagenticAIand/ormulti-agentAIsystems?

AsorganisationsprogressintheirAIjourney,theyexpandtheuseofagenticAIintomorestrategicplanningandcompliance-drivenfunctions.

Forexample,avicepresidentofITfromaU.S.healthcareproviderinstage4notedthat

agenticAIhasalreadybeenintegratedacrossmarketing,customerservice,humanresources,financeandlegal,andtheorganisationismaking“continuousimprovementsbasedondata

feedback.”PlansaretosupportcomplianceandriskmanagementfunctionsusingtheseimprovedAIagents.

AchiefexecutiveofficerfromanAustralianretailfirm,alsoinstage4,sharedthatagenticAItoolsarebeingdeployedforfrauddetection,ITandriskmanagement,usingamixof

customframeworksandvendorpartnerships.Theinvestmentsofaris“slightlyexceedingexpectations”theCEOadded.

Overall,themosttargetedfunctionsincludeIT,customerservice,operations,and

marketingandsales—areasthatarefoundationalforautomation,dataprocessingandcustomerengagement,makingthemidealentrypointsforagenticAIdeployment.

Fromanindustryperspective,technology,healthcareandfinancialservicesleadinadopting

AIagentsinIT,frauddetection,andriskmanagement,whereasretailandmanufacturinghaveastrongfocusonoperationsandsupplychainmanagement.

Figure7:Topbusinessfunctionscurrentlyusing,testingorexpectingtouseagenticAI

84%

72%

56%

53%

5%

5%

50%

48%

48%

46%

43%

38%

32%

38%

32%

28%

6%

Stage1

Stage2FraudDetection

Stage3Stage4Stage5

ITCustomerServiceOperations

AIPULSE|Integrationplanning:Unlockingorganisationalstrategies

Integrationplanning:Unlockingorganisationalstrategies

HowisyourorganisationplanningtodeveloporintegrateagenticAIand/ormulti-agentAIcapabilities?

TheagenticAIraceisprogressingquickly;organisationsaremovingfasttoavoidfallingbehindthecompetition.AlackofinternalskillsetsisdrivingdemandforexternalexpertisetohelporganisationsdevelopAIagentcapabilities.Overall,themostcommonapproachesorganisationsaredeployingtodevelopagenticAIcapabilitiesinclude:

•Expandingexistingenterprisetechnologylandscapes(46%)

•LeveragingexistingplatformswithprebuiltagenticAIcapabilities(46%)

•Partneringwithexternalvendors(45%)

13

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AIPULSE|Integrationplanning:Unlockingorganisationalstrategies

Onthe“howwedoit”question,thesurveyuncoversclearpatternsemergingacrossdifferentAImaturitystages:

•Stage1organisationsshowminimalengagement,with29%stillevaluatingoptions.Theirlimitedstrategicactivityunderscorestheexploratorynatureofthisphase.

•Stage2organisationsbegintoengagemoreactively,particularlythroughvendor

partnershipsandopen-sourceecosystemparticipation.Thisstagemarksthetransitionfromexplorationtopilotimplementation.

•Stage3organisationsdemonstrateashifttowardinternalcapabilitybuilding.They

activelyexpandtheirtechnologylandscapesandbegindevelopingcustomframeworks,indicatingamorestructuredandstrategicapproach.

•Stage4organisationsshowthemostbalancedandaggressivestrategyadoption.

Organisationsatthisstageutilisenearlyallavailableapproaches,includinginternaldevelopmentteams,customsolutionsandecosystemparticipation,reflectingtheircommitmenttoscalableandefficientAIintegration.

•Stage5organisationsrelyheavilyoninternaldevelopmentteamsandcustomframeworks.TheirstrategiessuggestdeepintegrationofagenticAIintocoreoperations,withafocusoninnovationandautonomy.

Figure8:Strategicintegrationapproachesbystagesofmaturity

MaturityStage*

CommonStrategies

Stage2

Externalvendors,existingplatforms,feasibilitytesting

Stage3

Customframeworks,internalteams,open-sourcecollaboration

Stage4

Full-spectrumintegration,scalabilityfocus

Stage5

Proprietarydevelopment,ecosystemleadership

*Stage1organisationsaremostlystillexploringoptionsonhowtodevelopagenticAI.

AIPULSE|AutonomyambitionversusAIreality:ClosingtheagenticAIreadinessgap

AutonomyambitionversusAIreality:ClosingtheagenticAIreadinessgap

Organisationsareaspiringtowardautonomy,butthere’sampleevidencethatmanymaybeoverestimatingtheirreadiness.ThecombineddatafromthreeAIPulseSurveysfindthatmostorganisationsarestillinstages2to3,indicatingearlytomid-levelmaturity.Onlyasmallfractionreportsbeinginthemostadvancedstage,thelevelofmaturitythatiscriticaltoadoptingautonomousAIagentssuccessfully.

Additionally,asignificantpercentageofearly-stageorganisationscitesignificantgovernance,infrastructureandethicalchallenges—elementsthatarefoundationaltoautonomousAIsystems.Theseorganisationsareseekingbasicenablementtools,notadvancedgovernanceorethicaloversightframeworks,anotherclearsignofamismatchbetweenaspirationsforautonomyandactualpreparedness.

Here’sthebottomline:OrganisationsintheearlystagesoftheirAIjourney,thosestillgrapplingwithfoundationaltechnologieslikeopticalcharacterrecognition(OCR)androboticprocessautomation(RPA),areunlikelytoembraceAIagentswithoutsignificantsupport.Incontrast,stage3and4organisations,whichpossessinternalcapabilitiesandstrategicclarity,arebetter