2025年负责任AI的商业价值白皮书

IDCWhitePaper,sponsoredbyMicrosoftIDecember2024

FROMRISKTOREWARD:

TheBusinessCasefor

ResponsibleAl

DaveSchubmehlResearchVicePresident,

ConversationalArtificialIntelligenceand

IntelligentKnowledgeDiscovery,IDC

RituJyoti

GroupVicePresident/GeneralManager,

WorldwideArtificialIntelligence,Automation,

DataandAnalyticsResearchPractice,IDC

FromRisktoReward:TheBusinessCaseforResponsibleAl

IDC

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TableofContents

CLICKANYHEADINGTONAVIGATEDIRECTLYTOTHATPAGE.

ExecutiveSummary 3

Introduction 4

KeyFindingsfromtheSurvey 7

ResponsibleAlTooling 11

AdditionalInsightsfromtheStudy 18

AlAdoption 18

ImportantUseCases 20

AdviceandRecommendation 22

Conclusion 28

Definitions 30

GenerativeAl 30

ResponsibleAl 31

ResponsibleAIAttributes 31

Appendix1:SupplementalData 33

AbouttheIDCAnalysts 37

MessagefromtheSponsor 38

FromRisktoReward:TheBusinessCaseforResponsibleAl

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ExecutiveSummary

EveryorganizationneedstoberesponsibleatthecoreintheAleraasithelpstheorganizationacceleraterealizationof

thebenefitsofAI.Aresponsible-at-the-coreorganizationhasthefollowingfoundationalelements:

Corevaluesandgovernance:Itdefinesandarticulates

responsibleAl(RAl)missionandprinciples,supportedbytheC-suite,whileestablishingacleargovernancestructureacrosstheorganizationthatbuildsconfidenceandtrustinAltechnologies.

Riskmanagementandcompliance:Itstrengthens

compliancewithstatedprinciplesandcurrentlawsandregulationswhilemonitoringfutureonesanddevelopspoliciestomitigateriskandoperationalizethosepoliciesthroughariskmanagementframeworkwithregular

reportingandmonitoring.

Technologies:Itusestoolsandtechniquestosupportprinciplessuchasfairness,explainability,robustness,accountability,andprivacyandbuildstheseinto

Alsystemsandplatforms.

Workforce:ItempowersleadershiptoelevateRAlasa

criticalbusinessimperativeandprovidesallemployeeswithtrainingtogivethemaclearunderstandingofresponsibleAlprinciplesandhowtotranslatetheseintoactions.TrainingthebroaderworkforceisparamountforensuringRAladoption.

ThepurposeofthispaperistoprovideinformationandevidencethataresponsibleAlapproachfostersinnovationbyaligning

Aldeploymentwithorganizationalstandardsandsocietal

expectations,resultinginsustainablevaluefororganizationsandtheircustomers.

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Introduction

AccordingtoIDC'sFebruary2024WorldwideSemiannual

ArtificialIntelligenceSystemsSpendingGuide,Version1,

whichtracksAlsoftware,hardware,andservicesacross

industriesandusecases,enterprisesworldwideareexpectedtoinvest$232billiononAlsolutionsin2024.

Alsolutionsaretransformingadiverserangeofindustries,fromfinanceandmanufacturingtoagricultureandhealthcare,byenhancingoperations

andreshapingthenatureofwork.Enterprises'applicationofgenerativeAl(GenAI),whichisrapidlyunfolding,canrevolutionizecustomerexperiences,boostemployeeproductivity,enhancecreativityandcontentcreation,

andaccelerateprocessoptimization.

However,Alalsocreatesrealrisksandunintendedconsequences.Alsystemscaninadvertentlyperpetuateoramplifysocietalbiasesduetobiasedtrainingdataoralgorithmicdesign.Alsystemsareoftentrainedonlargeamountsof

datacollectedfromvarioussources.Alprogramoutputsmayrunintocopyrightinfringementconcerns.Alhallucinationsareincorrectormisleadingresults

thatAlmodelsgenerate.Theseerrorscanbecausedbyavarietyoffactors,

includinginsufficienttrainingdata,incorrectassumptionsmadebythemodel,

lackofcontext,orbiasesinthedatausedtotrainthemodel.Solackofgroundingcancausethemodeltogenerateoutputsthat,whileseeminglyplausible,

arefactuallyincorrect,irrelevant,ornonsensicalandfurtherdepletetrust.

FromRisktoReward:TheBusinessCaseforResponsibleAl

91%

arecurrentlyusingAltechnologyattheir

organizationand

expectmorethan

24%improvementincustomerexperience,businessresilience,

sustainability,and

operationalefficiencybecauseofAlin2024.

AsAltechnologiesbecomeincreasinglysophisticated,thesecurityrisks

associatedwiththeiruseandthepotentialformisusealsoincrease.Forexample,hackers/badactorscancontrolGenAlfoundationmodeloutputbypoisoningthegroundingdata.Ortheycouldusepromptinjectionattacksthatdisguisemaliciousinstructionsasuserinputs,trickingthelargelanguagemodel(LLM)intooverridingdeveloperinstructionswiththegoalofmanipulatingthemodeltoproducea

desiredresponse.Jailbreaking,atechniquethatattemptstobypassorsubvertthesafetyfiltersandrestrictionsbuiltintoLLMs,isalsopopularwiththebadactors.

AccordingtoIDC'sMarch2024Microsoft—ResponsibleAISurvey(n=2,309)

(sponsoredbyMicrosoft),whichgatheredinsightsonorganizationalattitudes

andthestateofresponsibleAI,91%arecurrentlyusingAltechnologyattheir

organizationandexpectmorethan24%improvementincustomerexperience,

businessresilience,sustainability,andoperationalefficiencybecauseofAlin2024.RespondentswhouseresponsibleAlsolutionssaythatithashelpedwithdata

privacy,customerexperience,confidentbusinessdecisions,brandreputation,andtrust.

Albringsnotonlyunprecedentedopportunitiestobusinessesbutalso

anincredibleresponsibility.Toensuretrustandfairnesswiththeircustomersandstakeholders,aswellasadheretoemerginggovernmentalregulations(e.g.,theEUAIAct),organizationsneedtobefocusedonresponsibleAI.

TheEUAIAct,whichaimstogovernthewaycompaniesdevelop,use,andapplyAl,wasapprovedinMay2024andwentintoeffectinAugust2024.Thelegislationappliesarisk-basedapproachtoregulatingAl,whichmeansthatdifferent

applicationsofthetechnologyareregulateddifferentlydependingonthelevelofrisktheyposetosociety.

ForAlapplicationsdeemedtobe“highrisk,”forexample,strictobligationshave

beenintroduced.Suchobligationsincludeadequateriskassessmentandmitigationsystems,high-qualitytrainingdatasetstominimizetheriskofbias,routineloggingofactivity,andmandatorysharingofdetaileddocumentationonmodelswith

authoritiestoassesscompliance.

TheEUAIActhasimplicationsthatgofarbeyondtheEU.Itappliestoany

organizationwithanyoperationorimpactintheEU,whichmeanstheAlActwilllikelyapplytoyounomatterwhereyou'relocated.OversightofallAlmodelsthatfallunderthescopeoftheAct—includinggeneral-purposeAlsystems—willfallundertheEuropeanAIOffice,aregulatorybodyestablishedbytheCommissioninFebruary2024.

Essentially,organizationsneedtoberesponsibleatthecoreandproactively

operationalizeAlgovernanceacrosstheprojectlifecycle,supportcollaborativeriskmanagement,andadheretoevolvingAlregulationsandtheirpoliciesandvalues.

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FromRisktoReward:TheBusinessCaseforResponsibleAl

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AsconsumersbecomemoreawareofAI'simpact,theydemandgreater

transparencyandresponsibleuseofAI.ManyorganizationsareintegratingresponsibleAlintotheirCSRstrategies,recognizingthatresponsibleAl

practicescanenhancetheirreputationandcontributetosocietalwell-being.BusinessesareadoptingresponsibleAltomitigaterisksassociatedwithAl,suchasbiases,securityvulnerabilities,andunintendedconsequences.

Thisproactiveapproachhelpsinsafeguardingtheiroperationsandreputation.CompaniesthatprioritizeresponsibleAlareoftenseenasleadersininnovation.Byaddressingsocialandmoralconcerns,theycandifferentiatethemselvesinthemarketandattractmorecustomersandpartners.

Thereisagrowingtrendofcollaborationbetweentechnologists,legalexperts,andotherstakeholderstodevelopcomprehensiveresponsibleAlframeworks.ThisinterdisciplinaryapproachensuresthatdiverseperspectivesareconsideredinAldevelopment.WithincreasingregulationsliketheEU'sAIActandthe

U.S.AIBillofRights,companiesareprioritizingresponsibleAlpracticestoensurecomplianceandavoidlegalrepercussions.Thesetrendshighlighttheindustry'srecognitionofthecriticalroleresponsibleAlplaysinensuringsustainable

technologicaladvancement.

IDCdefinesRAlasthepracticeofdesigning,developing,anddeployingAlina

waythatensuresfairness,reliabilityandsafety,privacyandsecurity,inclusiveness,transparency,andaccountability.TocreatetrustinAl,organizationsmust

movebeyonddefiningRAlprinciplesandputthoseprinciplesintopractice.

Algovernanceisessentiallythesetofprocesses,policies,andtoolsthatbringtogetherdiversestakeholdersacrossdatascience,engineering,IT,compliance,legal,andbusinessteamstoensurethatAlsystemsarebuilt,deployed,used,andmanagedtomaximizebenefitsandpreventharm.Algovernanceallows

organizationstoaligntheirAlsystemswithbusinessandlegalrequirementsthroughouteverystageofthemachinelearning(ML)/generativeAllifecycle.

IDCdefinesRAlasthepracticeofdesigning,

developing,anddeployingAlinawaythatensuresfairness,reliabilityandsafety,privacyandsecurity,inclusiveness,transparency,andaccountability.

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KeyFindingsfromtheSurvey

AccordingtoIDC'sMicrosoft—ResponsibleAISurvey,over30%ofthe

respondentsnotethatlackofgovernanceandriskmanagementsolutionsisthetopbarriertoadoptingandscalingAl(seeFigure1,nextpage).

Equallyimportanttonoteisthatmorethan75%oftherespondents

whouseresponsibleAlsolutionssaythatithashelpedwithdataprivacy,

customerexperience,confidentbusinessdecisions,brandreputation,

andtrust(seeFigure2,page9).Basically,bybeingproactiveandusing

RAltoolsandtechnologiestoidentify,mitigate,andmonitorrisksthroughouttheAllifecycle,theycanmitigateunintendednegativeconsequences.

Asorganizationsarebuying,developing,anddeployingAlinawidevarietyof

solutions,theyarealsograpplingwiththeneedtodevelopresponsibleAlpolicies,procedures,andpractices.Accordingtothesurvey,organizationsarestillintheearlydaysofdevelopingandfollowingacomprehensiveresponsibleAlpracticeonaworldwidelevel.WhileAlisnotnewandorganizationshavebeenusing

Al-poweredsolutionsforawhile,onlythemoreAl-matureorganizationshavebeenproactiveaboutembracingitresponsibly.GenAlhasbeenacatalyst

tobroaderAladoptionbuthasalsobroughtalotmoreissuesarounddata

security,IPleakage,hallucinations,copyrightinfringement,andthreatsfrombadactors.Onaregionalbasis,EMEA,LatinAmerica,andAsia/Pacificlagbehind

NorthAmericaintermsofgovernancestructuresandtechnologyusedtoenforcegovernance.Lackofhumancapital,dataavailability,funding,trustconcerns,

andregulationshavebeenthekeyinhibitorstoAlmaturity(seeFigure3,page10).

Asystematicapproachrequiresproventools,frameworks,andmethodologies,enablingorganizationstomovefromprinciplestopracticewithconfidence.

EstablishingaresponsibleAlapproachthatisrobust,fair,andmaintainedon

anongoingbasiscanalsoenableorganizationstocommunicateandcollaboratewithconfidence.NorthAmericahasbeenattheforefrontwithearlyadopters

andmoreAl-matureorganizations.

FromRisktoReward:TheBusinessCaseforResponsibleAl

FIGURE1

TopBarrierstoAlAdoption

31%

30%25%

25%

WhathavebeenyourtopbarrierstoadoptingAl?(Percentageofrespondents)

LackofAlgovernanceandriskmanagementsolutions.

Lackofskilledpersonnel(datascientists,dataengineers,orAlmodelers)…

Lackoffairness,explainability,

transparency,anddatalineagetools……………

Cost…………….

Adversarialrobustness

(securityandsafetyofalgorithms).……………

23%

Lackofcontentsafety

(abusemonitoring)…………………

21%

Machinelearningoperation……

Lackofadequatevolumesand

qualitytrainingdata..……………

21%

19%

Unclearbusinesscasesor

involvement/supportfromLOB……

Decisioncriteriaofthesolution…

Lackofmodelmonitoring

(dataandconceptdrift)tools.……

Lackofdigitalwatermarking………

Hallucinations.……

17%

17%

17%

Notes:DataismanagedbyIDC'sGlobalPrimaryResearchGroup.DataisweightedbyITspendingbycountry.Multipleresponseswereallowed.Usecautionwheninterpretingsmallsamplesizes.

n=2,562;Source:IDC'sMicrosoft—ResponsibleAISurvey,March2024

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FIGURE2

LevelofImpactofOrganization'sResponsibleUseofAISolutions

Howimpactfuldoyouconsideryourorganization'sresponsibleuseofAlsolutionsinpreservingeachofthefollowing?

(Percentageofrespondents)

77%

76%

76%

76%

76%

Dataprivacy………………

Customerexperience

(satisfaction,loyalty)…

Confidencein(business)decisions

Brandreputation…………………

Publictrust…………………

.……

74%

Revenue…………

73%

Employeeexperience.

71%

……

…

ESGratingsandinvestors'actions.………

69%

Avoidinghiddencosts.………

69%

Limitedregulatorybacklash-

legalcompliance.…………

68%

Avoidingcriminalinvestigation…………

Notes:DataismanagedbyIDC'sGlobalPrimaryResearchGroup.DataisweightedbyITspendingbycountry.

Usecautionwheninterpretingsmallsamplesizes.Scoresarebasedonascaleof1-5(1=notimpactful,5=veryimpactful).

n=2,562;Source:IDC'sMicrosoft-ResponsibleA/Survey,March2024

FromRisktoReward:TheBusinessCaseforResponsibleAl

FIGURE3

GovernanceFrameworksinPlace:WorldwideandRegionalSplit

Whichofthefollowingarecurrentlyinplaceatyourorganization?

(Percentageofrespondents)

■Worldwide■EMEA

Clearframework(principles,policies,

technologies,andprocesses)………………

Mechanismstoenforce/apply

theframework……………

Governancestructuretooverseeimplementation..………………..

TechnologiestoenforceresponsibleAlrules,policies,andprocesses..

46%

87%

84%

83%81%

89%

81%

73%

67%

70%

70%

75%

69%

62%

66%67%

66%

57%

54%

60%

Notes:DataismanagedbyIDC'sGobalPrimaryResearchGroup.DataisweightedbyITspendingbycountry.Multipleresponseswereallowed.Usecautionwheninterpretingsmallsamplesizes.

n=2,562;Source:IDC'sMicrosoft—ResponsibleAISurvey,March2024

Foranaccessibleversionofthedatainthisfigure,seeFigure3SupplementalDataintheAppendix.

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ResponsibleAITooling

IDCisseeingthatorganizationsareusingavarietyoftoolstoensureresponsibleAl,rangingfromsoftware-based

monitoringtoolstoincludinghumanoversight(alsoknownashumanintheloop)

ThetoolsformonitoringandcheckingoutputfromAlrangefromcontent

filteringandabusemonitoringtobiascheckingandfromvisualexplainabilityto

groundednessdetection.Thisareaofsoftwareisrapidlyevolving,andIDC

expectstoseealargersetofvendorsofferingsolutionsinthisareaoverthe

next12-18months.Figure4(nextpage)showshoworganizationsarethinking

abouttheuseoftechnologycombinedwithhumanoversightastheRAltools

andtechnologiesarerapidlyevolving.Figure5(page13)showshoworganizationswillbeallocatingtheirbudgettoincluderesponsibleAlsoftware.ConsideringtheirlackofbothAlskillsandtoolstosupporttheirRAlrequirements,aboutone-thirdoftherespondentsplantoleverageprofessionalservicessupportalongwith

RAIsoftware.

FromRisktoReward:TheBusinessCaseforResponsibleAl

FIGURE4

AssetMixforMonitoringAfteranAISystemHasGoneLive:WorldwideandRegionalSplit

ToensureresponsibleuseofAlbyyourorganizationsoverthenext12-18months,pleaseindicatethemostlikelymixofassetstobeusedformonitoringafteranAlsystemhasgonelive.

Monitoringwillbedone...

…mostlybyresponsibleAl

governancesoftwarebutwith

someoversightbypeople…………

…mostlybypeoplebut

usingsomeresponsibleAlgovernancesoftware..

…byresponsibleAl

governanceplatformsonly(i.e.,nopeopleinvolved).

…bypeopleonly(e.g.,ethicsboardsdetermineethicaluse)

(Percentageofrespondents)

Worldwide

NA

EMEA

APAC

LATAM

50%

49%

51%

50%

49%

23%

22%

23%

23%

24%

17%

19%

20%

19%

13%

8%

7%

7%

9%

5%

Nomonitoringwillbenecessary3%2%3%2%1%

Notes:Totalsmaynotsumupt100%duetorounding.DataismanagedbyDC'sGlobalPrimaryResearchGroup.DataisweightedbyITspenadingbycountryUusecautionwheninterpretingsmallsamplesizes.n=2,562(worldwide),n=611(NA),n=819(EMEA),n=832(APAC),n=300(LATAM);Sourrce:IDC'sMicrosoft—ResponsibleAISurvey,March2024Foranaccessibleversionofthedatainthisfigure,seeFigure4SupplementalDataintheAppendix.

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FromRisktoReward:TheBusinessCaseforResponsibleAl

FIGURE5

AlOrganization'sBudgetAllocation,2024

AI/MLgovernancetool...……….…

Professionalservicesfor

responsibleAI………

AI/MLdevelopment

platforms/MachineLearningOps(MLOps)tools.…………

Others..……………..

WhatpercentageofyourAlorganization'sspendin2024willbeforeachofthefollowing?(Percentageofrespondents)

Worldwide

NA

EMEA

APAC

LATAM

35%

36%

35%

35%

34%

32%

31%

35%

32%

34%

18%

19%

17%

18%

17%

15%

15%

16%

15%

15%

Base=respondentsthatindicatedorganization'splantospendmorethan$1ontheirAlprojectsin2024.

Notes:Totalsmaynotsumupto100%duetorounding.DataismanagedbyIDC'sGlobalPrimaryResearchGroup.DataisweightedbyITspendingbycountry.Usecautionwhen

interpretingsmallsamplesizes.n=2.555(worldwidetn=611(NAL.n=819(EMEAL.n=830(APAC).n=300(LATAMI:Source:IDC'sMicrosoft一ResponsibleAISurveyMarch2024

Foranaccessibleversionofthedatainthisfigure,seeFigure5SupplementalDataintheAppendix.

TheAlregulatorylandscapeisdynamic,andcurrentlytheEUAIActandAmericanDataPrivacyandProtectionActarecriticalregulationsfororganizationstoadhereto(seeFigure6,nextpage).Itisimportanttonotethatwhiletheregulationswillincrease,organizationswillcontinuetospendonAlsolutionsbutdoitresponsiblyusingprofessionalservicesandgovernancetoolsandtechnologies(seeFigure7,page15).

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FIGURE6

AlRegulationsCriticalforOrganizations'AlImplementations

WhichofthefollowingemergingAlregulationsarecriticalforyourorganization'sAlimplementations?(Percentageofrespondents)

EUAlAct.………...

AmericanDataPrivacyProtectionAct(ADPPA),specificallySection207*.

Canada'sC-27Bill:DigitalCharter

ImplementationAct,2022…………….…

D.C.StopDiscriminationby

AlgorithmsActof2021…

UKWhitePaperonAl……..

NISTRiskManagementFrameworkandIndustryPlaybook.…………….…

ColoradoSB169:Concerning

ProtectingConsumersfromUnfair

DiscriminationinInsurancePractices..

Singapore'sModel

GovernanceFramework.

SR11-7-SupervisoryGuidanceon

ModelRiskManagement.……………

NYCAlgorithmicHiringLawNo.144.……………

CFPBCircular2022-03/RegulationB/EqualCreditOpportunityAct

TopRegion

NA

EMEA

APAC

ILATAM

39%

33%

26%

26%

6%

·Whichrequiresanalgorithmdesignevaluationandalgorithmicimpactassessment.Notes:DataismanagedbyIDC'sGlobalPrimaryResearchGroup.DataisweightedbyITspendingbycountry.Multipleresponseswereallowed.Usecautionwheninterpretingsmallsamplesizes.

n=2,562;Source:IDC'sMicrosoft-ResponsibleA/Survey,March2024

FromRisktoReward:TheBusinessCaseforResponsibleAl

FIGURE7

InfluenceofWorldwideIncreaseinAIRegulationsonanOrganization'sResponsibleAlSpendPlansintheNextTwoYears:WorldwideandRegionalSplit

Foreachofthefollowingareas,howwouldaworldwideincreaseinAlregulationsinfluenceyourorganization'sresponsibleAlspendplansinthenexttwoyears?

(Mean—percentageofincrease)

■Worldwide

6.4%

…5.4%

Al-poweredsolutions...7.3%6.4%

6.6%

5.2%

ITprofessionalservices5.2%

6.4%5.5%

5.0%

5.7%

Adversarialrobustness:4.3%

datasecurityandprivacysoftware6.2%5.4%

4.3%

5.3%

Driftmonitoringandrisk4.8%

managementsoftware…………5.8%5.3%

4.9%

5.5%

Businessprofessionalservices4.8%

forresponsibleA………………5.3%5.2%

3.5%

4.8%

Fairness,explainability,datalineage,4.5%

andtransparencytoolsandsoftware.6.0%5.1%

5.4%

4.8%

Digitalwatermarkingand4.6%

4.4%

contentsafetysoftware.5.1%4.8%

n=2,562;Source:IDC'sMicrosoft—ResponsibleAISurvey,March2024

Notes:DataismanagedbyIDC'sGlobalPrimaryResearchGroup.DataisweightedbyITspendingbycountry.Usecautionwheninterpretingsmallsamplesizes.

Foranaccessibleversionofthedatainthisfigure,seeFigure7SupplementalDataintheAppendix.

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Overtwo-thirdsoftherespondentsareplanningtouseAI/MLplatformswith

built-inRAlsupport(seeFigure8),and39%reportthattheplatformshould

providedashboardstoassess,monitor,anddrivetimelyactionsandmulti-personacollaboration(seeFigure9,nextpage).

FIGURE8

TypeofResponsibleAISoftwareUsed/PlanningtoBeUsed

WhattypeofresponsibleAlsoftwareisyourorganizationusing/planningtouse?

(Percentageofrespondents)

1%Noneoftheabove

31%

StandaloneresponsibleAlplatform

68%

AI/MLplatformwithbuilt-inresponsibleAlsupport

n=2,562;Source:IDC'sMicrosoft一ResponsibleAISurvey,March2024

Notes:DataismanagedbyIDC'sGlobalPrmaryResearchGroup.DataisweightedbyITspendingbycountry.

Usecautionwheninterpretingsmallsamplesizes.

FromRisktoReward:TheBusinessCaseforResponsibleAl

FIGURE9

CriticalCapabilitiesofaResponsibleAlplatform

WhatdoyouthinkarethecriticalcapabilitiesofaresponsibleAlplatform?(Percentageofrespondents)

Dashboardstoassess,monitor,and

drivetimelyactions/riskmanagement.

Multi-personacollaboration(datascience,legal/compliance,LOB,etc.).

39%

39%

Integrationswithdatagovernancesystems.

IntegrationwithMachineLearningOps(MLOps)/LargeLanguage

ModelOpsandmonitoringtools..……………

Multipledeploymento