2025年首席数据官调研报告：AI乘数效应：决策就绪型数据驱动增长加速（英文）

The2025Chief

DataOfficerStudyThe

AI

multiplier

effectAccelerate

growthwithdecision-readydataIBMInstitute

forBusiness

Value

|ResearchInsightsHow

IBM

can

helpIBM

has

been

at

the

forefront

of

helping

organizations

tap

intothepowerofdata

and

AI

todrivebusiness

transformation.

Withextensiveexperience

andexpertise,IBMprovides

tailoredsolutions

that

address

specificdatachallenges

andopportunities,includingdevelopingdynamicdata

strategies,implementingAI-enableddecision

support

systems,

andestablishing

scalableenterprise

data

architectures.IBMwatsonx™empowersorganizations

toharness

AI

forpredictive

analytics,real-timedata

processing,

and

automated

decision-making.For

more

information

about

IBM’s

data

and

AI

services,

visit

/consulting/data-aiTo

explore

AI

solutions

fromIBM

Software,

visit

/watson.For

insights

into

AI

innovations

from

IBM

Research,visit

https://re/artificial-intelligenceContentsForeword2Introduction

4Strategy:Don,tjustcollectdata.Deployitona

mission.10Scale:GiveAIagentsafasttracktodata.16Resilience:Buildunbreakabledatapipelines.22Innovation:Deliverdatatoeverydesk.26Growth:Spotbreakthroughswaitingtohappen.301ForewordThe

architecture

for

scaling

AI:Fromfragmented

to

integrated

enterprise

dataEnterprise

AI

at

scaleis

finally

withinreach.

The

technologyisready—aslong

as

organizations

can

feedit

theright

data.But

many

simply

cannot.

This

year,I’ve

personally

spoken

to

more

than150enterpriseclients,andonechallengehasemergedabove

all

others:

dataistrappedinsilos.Financehas

theirdata.HRhas

theirs.Marketing,

supplychain,legal—each

function’sdataoperatesinisolation.Nocommon

taxonomy.Noshared

standards.No

end-to-end

visibility.This

isn’tjust

an

operational

inconvenience.It’s

the

Achilles’heel

of

enterpriseAI

transformation.

Whendatalivesindisconnected

silos,every

AIinitiativebecomes

a

drawn-out,

six-to-twelve-month

data

cleansing

project.

Teams

spendmore

time

hunting

for

and

aligning

data

than

generating

meaningful

insights.This

year’sChiefDataOfficer(CDO)Studyoffersanalternative.Basedondatafrom1,700enterprise

data

leaders,

it

highlights

what

can

be

achieved

with

atruly

integrated

enterprise

data

architecture.

AI

agents

can

be

deployed

at

scale—and

fast.

Withaccess

to

therightdata,

theycangobeyondisolatedusecasesto

cross-functional,high-impact

use

cases.First,leadersmust

fundamentally

shift

theirmindset.

Stop

seeingdata

as

anapplicationbyproduct.

Start

viewingit

as

a

strategic

asset

that

flows

acrossthe

entire

value

chain.This

means

creating

data

standards

that

work

across

all

systems,not

just

withinindividualERPs.Itmeans

workingbackward

frombusiness

outcomes

toidentifythe

workflows

and

data

that

truly

matter.

It

means

treating

data

experiences

likeproduct

experiences—designed

to

attract

users,

drive

adoption,

and

deliverintuitive

value.Most

importantly,it

means

shifting

from

data

ownership

to

datastewardship,makinginformation

accessible

where

and

when

decisions

aremade.The

goal

is

federated

access

with

security

and

governance—democratizing

datain

a

safe,controlled

way.

This

will

transform

your

employees,regardless

of

theirrole,into

trustedbusiness

advisors

whocan

spend

time

generatinginsightsinsteadofchasingdata

across

silos.Get

thisright,

and

the

advantagescompoundrapidly.In

the

short

term,

you’ll

seefaster

AIdeployment,betterdecision-making,

andenhancedproductivity.Longterm?

You’ll

have

built

an

enterprise

operating

model

that

circulates

intelligencethroughout

your

organization.

While

competitors

struggle

with

siloed

AIexperiments,

you’llbe

scalingintelligent

automation

acrosseverycriticalbusinessprocess.The

companies

that

crack

this

code

won’t

just

have

better

AI—they’ll

havefundamentallydifferent

capabilities.

They’llmove

faster,decide

smarter,

andadapt

more

quickly

to

market

changes.

Will

your

enterprise

be

among

them?|

Foreword

|Introduction|

Strategy|Scale|Resilience|Innovation|GrowthEdLovelyVPandChiefDataOfficerIBM2Keytakeaways

CDOsarenavigatinginfog.92%

say

they

must

focus

on

business

outcomes

tosucceed

in

their

role.But

only29%are

confident

theyhave

clear

measures

to

determine

the

business

valueof

data-driven

outcomes.

Datademocratizationexpedites

AIefforts.80%

ofCDOs

say

giving

employees

accessto

data

helps

their

organization

move

faster. AI

agents

get

the

job

done.83%

of

CDOs

say

thepotentialbenefits

of

deploying

AIagentsin

their

organizations

outweigh

therisks—and77%say

they’re

comfortable

with

their

organization

relying

onoutcomes

from

AI

agents.

Dataproductsgiveorganizations

thehighground.78%

ofCDOs

sayleveragingproprietary

datais

a

top

strategic

objective

to

differentiate

their

organizationin

themarket.CDOswhotapintotheirorganization’smostvaluable

data—andhaveaclearvision

of

whattheywanttoachieve—

deliverbetterAI-poweredbusinessresults.|

Foreword

|Introduction|

Strategy|Scale|Resilience|Innovation|Growth3|

Foreword|

Introduction|Strategy|Scale|Resilience|Innovation|Growth

IntroductionInan

AI-firstenterprise,datamakes

the

differenceAI-first

enterprises

are

redefining

market

mechanics.They’regaininggroundwithunprecedentedvelocity,creatingawinner-takes-mostdynamic.It’snot

justproducts

or

services

that

set

thesedisruptors

apart.It’sdata.Organizations

thatcan

tapinto

theirmost

valuabledata—andhaveaclearvisionof

what

they

want

to

achieve—can

trainmore

targeted

AI

thatdeliversbetter

business

results.AI

agents,or

software

systems

thatcanlearn

from

theirenvironments

and

actautonomouslyto

achieve

specific

goals,can

translate

data

into

revenue,profit,and

productivity.

Whether

agents

are

adjusting

processes

based

on

market

signals,optimizing

energy

usage,or

developing

software

features,high-value

data

is

whatbrings

them

tolife.Yetnotallorganizationsare

seeingresults.Lackofdatais

theculprit.But

solving

theproblem

isn’t

as

simple

as

opening

the

floodgates

and

giving

every

employeeunfettered

access

to

everything.

That

could

be

a

costly

mistake.Instead,organizations

must

identify

which

data

is

worth

most

in

each

business

context,

thenmake

that

information

accessible

to

the

right

teams

at

the

right

time—in

the

right

way.“LeadingCDOsarenot

justoptimizingfunctionalcapabilities,ratherenablingtheirorganizationstoreimaginetheirend-to-endworkflowspoweredbydataand

AI.”VikrantBhan,GlobalHeadofAnalytics,Data,andIntegration,Nestlé4|

Foreword|

Introduction|Strategy|Scale|Resilience|Innovation|Growth

AI

amplifies

all

outcomes,both

positive

and

negative,so

good

governance

mustbe

topofmind.

With

scoresofemployees—andexponentiallymore

AIagents—nowcreatingandusingdataacrossevery

functioneveryday,

successfullyharnessingits

flowis

essential

to

accelerate

AI-poweredimpact.What

does

that

mean,practically,

for

enterprises

that

want

to

lead

the

future?

Toidentify

best

practices,

the

IBM

Institute

for

Business

Value(IBM

IBV)conductedin-depth

proprietary

research

in

partnership

with

Oxford

Economics,

surveying

morethan1,700CDOsacross19industriesand27geographies.

We’vealso

comparedthoseresults

with

findings

from

the2023CDOStudy

topaintapictureofhow

theCDOrolehasevolved.The

biggest

shift

has

been

clarity

of

focus.In2023,CDOs

knew

theyneeded

topivotfrom

strictlymanagingdata

todeliveringmeaningfulbusiness

value.But

that

valuewas

broadly

defined,

with

only58%of

CDOs

saying

their

data

investments

acceleratedbusiness

growth.Today,

AIhasmade

theCDO’smandatemuchclearer—theyneed

todrive

thebusinessforwardbyusingenterprisedata

topower

AI.In

this

vein,81%ofCDOsnow

saytheorganization’sdata

strategyisintegrated

withits

technologyroadmap

andinfrastructure

investments,compared

to

just52%in2023(see“The

CDO

Mandate”onpage8).CDOs

now

agree

that

deploying

data

for

competitive

advantage

is

their

top

priority,aheadofevengovernanceand

securityascoreresponsibilities(see“Thepathto

data-driven

AI

dominance”on

page6).But

there’s

a

roadblock.Only26%areconfident

theirdatacapabilitiescan

supportnew

AI-enabledrevenue

streams.In

a

winner-takes-most

market,

this

barrier

seriously

compromises

an

organization’s

growthprospects.Ourresearchhasidentified

fivedata

focusareas—strategy,

scale,resilience,innovation,and

growth—that

help

organizations

deliver

greater

business

value.

TheCDOs

thatexcelin

theseareasareable

todomore

with

theirmoney—deliveringhigherROI

on

both

data

projects

andAI

investments.

They

demonstrate

that

driving

morevalue

isn’t

about

accessing

more

data.It’s

about

using

the

most

valuable

data

todeliver

specificbusinessoutcomes.

That’s

what

setsleaders

apart.1.

Strategy:Don’t

just

collect

data.Deploy

it

on

a

mission.2.Scale:Give

AI

agents

a

fast

track

to

data.3.Resilience:Build

unbreakable

data

pipelines.4.Innovation:Deliver

data

to

every

desk.5.Growth:

Spot

breakthroughs

waiting

to

happen.5|

Foreword|

Introduction|Strategy|Scale|Resilience|Innovation|Growth

PerspectiveThe

pathtodata-drivenAIdominanceCDOs

sayleveragingdata

forcompetitiveadvantage

is

their

top

priority.But

they

seeseveralobstaclesin

theirpath.Fouroutoftheir

five

topchallenges

are

also

their

toppriorities,revealing

aclear

strategic

focus.Rather

than

shying

away

from

the

mostdifficult

tasks,CDOs

are

tackling

themhead-on—because

they

know

that’s

theonly

way

to

achieve

the

organization’s

AI

ambitions.Tohelpenterprisesgainanedge,

CDOsmustprioritize

data

democratization—giving

morepeoplemoreaccess

todata—whichleadsto

innovation,

agility,

and

empowerment.Combined

withefforts

to

securedata,ensurecompliance,

andmaintainquality,

that’s

the

path

todeliveringdata-led

value

with

AI.12345Implementingeffectivedatagovernanceandmanagement

practicesImplementingeffectivedatagovernanceandmanagement

practicesAttracting,developing,

and

retaining

talent

withadvanceddataskillsGeneratingactionableinsights

throughadvancedanalyticsGeneratingactionableinsights

throughadvancedanalyticsLeveragingdataforcompetitive

advantageEnsuringdatasecurityandprivacyEnsuringdatasecurityandprivacyFosteringadata-drivencultureFosteringadata-drivenculture>TopchallengesToppriorities6|

Foreword|

Introduction|Strategy|Scale|Resilience|Innovation|Growth

“Thecruxisintrust.Igiveourcustomers,

i.e.,citizensorcompanies,theconfidence

thatwehandletheirdataproperly.So,IamnotaChiefDataOfficeratall.IamaChiefTrustOfficer.”WimStolk,CDO,DutchMinistriesofEconomicAffairs;ClimateandGreenGrowth;andAgriculture,Fisheries,FoodSecurity,andNature7|

Foreword|

Introduction|Strategy|Scale|Resilience|Innovation|Growth

PerspectiveTheCDOmandateThe

role

of

the

CDO

has

never

been

more

pivotal—or

more

strategic.Twoyearsago,CDOs

weremostconcerned

withissues

surroundingdatareliabilityandcompliance.Butqualitycontrolisnolongerenough.CDOsmustnowdeliverquality

at

scale.

That

requires

the

right

IT

infrastructure—less

data

warehouse,moredatapipeline—but

that’sonlyonepieceof

thepuzzle.CDOs

must

also

become

AI

product

partners,enabling

the

innovation

that

providesacompetitiveedge.

Thatmeansknowing

what

AIusecasesaremost

valuableandwhat

data

is

required

to

power

them.

And

then

making

sure

the

data

can

be

usedrepeatedly

todrive

targetedoutcomes

across

theenterprise.Ourresearch

shows

thatCDOs

areup

for

the

challenge.But

they’llneed

to

focus

on

three

core

strategic

tasks

whereprogressislagging:–Business

focus:

Todeliveronenterprisegoalsin

theageof

AI,CDOsmustbuildastronger

link

between

data

and

business

objectives.

An

overwhelming92%ofCDOs

say

theymust

focusonbusinessoutcomes

to

succeedin

theirrole(seeFigure1).–C-suitecommunication:CDOsknow

theycan’tcreate

valueon

theirown.Butonlyone-third

strongly

agree

that

they

clearly

convey

how

data

drives

business

results.When

data

leaders

struggle

to

articulate

the

value

of

their

role,86%ofCDOs

sayitjeopardizes

the

organization’s

success.–Metrics:Only29%ofCDOs

stronglyagree

that

theyhaveclearmeasuresto

determine

the

value

of

data-driven

business

outcomes.Explore

the

following

sections

for

specific

actionsCDOscan

take

todeliveron

their

evolving

mandate.“TheroleoftheChiefDataOfficerisstillevolving.Therearenosettemplatesfortheoperatingmodel,

whichposessignificantchallengesintermsof

how

weapproachcentralization

versusdecentralization

andtheremitof

governance

versusdeliveryofdata

andAIasapractice.”VikrantBhan,GlobalHeadofAnalytics,Data,andIntegration,Nestlé本报告来源于三个皮匠报告站（）,由用户Id:349461下载,文档Id:983521,下载日期:2025-12-088|

Foreword|

Introduction|Strategy|Scale|Resilience|Innovation|Growth

Figure1CDOsare

focusedonoutcomes—butmanystruggle

tomeasuredata’s

valueImust

be

businessoutcomes-orientedtosucceedinmy

roleIactivelycollaboratewithourbusinessleaderstodefine

and

prioritize

whatwe

need

from

our

dataWhendataleaderscan'tarticulate

the

value

ofdata,it

jeopardizes

theorganization'ssuccessI

can

clearly

articulate

howourdataprioritiesfacilitate

key

business

outcomesI

have

clear

measures

todetermine

the

value

ofdata-driven

business

outcomesIhavetheresourcesandauthority

to

execute

ourstrategicdata-driventransformationThere

is

no

set

templatethat

defines

the

mandateofa

CDODataleaders

havestruggled

to

clearlyarticulatethebusinessvalue

of

their

role45%92%35%86%34%85%41%84%29%78%29%77%26%74%24%

71%Agree+StronglyagreeStronglyagree9|

Foreword

|Introduction|

Strategy|

Scale|Resilience|Innovation|

GrowthStrategyDon’t

justcollectdata.Deployiton

amission.EnterprisedatastrategyrevolvesaroundpoweringAI.81%oftheCDOsinourstudyprioritizeinvestments

thataccelerateAIcapabilitiesandinitiatives.As

data

becomes

more

central

to

competitive

advantage,organizations

areincreasingly

investing

in

data

strategy

to

fuel

better

AI

outcomes.

Today,13%of

a

typical

organization’s

IT

budget

is

allocated

to

data

strategy,upfrom

just

4%in2023.1

But

these

funds

shouldn’t

be

spent

in

a

vacuum.CDOs

fromorganizations

thatdeliverhigherROIonbothdataand

AIinvestmentsare

distinct

in

their

commitment

to

delivering

on

business

strategy.

They’re25%

morelikely

to

say

theycanclearly

articulatehowdatapriorities

facilitatekeybusiness

outcomes—and

they

have

clear

measures

to

determine

the

value

ofdata-driven

results18%more

often

than

their

peers.Plus,

they’re

more

likelyto

say

theyintegratedata

strategy

with

theorganization’s

technologyroadmapandinfrastructureinvestments.With

therighthybrid-by-designcloud

strategyinplace,CDOscancreateadatamanagement

framework

thatis

optimized

for

AI,

with

the

ability

tohandlemassive

volumesofdata

andprovidereal-time

analytics.

This

allows

them

todeploy

AIworkloads

wherever

they’re

needed,

whether

that’s

in

the

cloud,on

premises,

orat

the

edge.To

point

the

entire

technology

estate

toward

this

purpose,CDOs

need

to

partnercloselywith

other

C-suite

leaders,including

Chief

Information

Officers(CIOs),Chief

TechnologyOfficers(CTOs),andChiefInformationSecurityOfficers(CISOs).(See“Data’spowercouple”onpage14).

Thatincludesongoingconversationsabout

whichemployeesand

AI

systems

shouldhaveaccess

to

whichdata—andhowtechnology

could

better

support

that

access.Because

conditions

change,83%of

theCDOs

in

our

study

say

their

teams

are

continuously

asking

what

additional

data

pointstheir

organization

needs.10|

Foreword

|Introduction|

Strategy|

Scale|Resilience|Innovation|

Growth“You’renot

justdeliveringtheservice.You’renot

justanenablingfunction.You’repartandparcelofsettingupastrategytogether

withthosestakeholders.”VikrantBhan,GlobalHeadofAnalytics,Data,andIntegration,NestléAI

demands

that

CDOs

work

closely

with

business

units,as

they

ultimately

own

dataand

best

understand

its

value.In2023,CDOs

said

they

leaned

on

top-down

decisionstructures

to

make

the

best

use

of

data—but81%now

say

data

isprimarilypreparedfor

AI

at

the

functional

or

project

level.In

some

cases,CDOs

need

to

provide

the

databusinessleadersrequire,

whileother

times

they

willneed

tominedata

toidentifyopportunities

the

business

can

capitalize

on.In

either

case,

they

need

to

tap

intoproprietary

enterprisedata.Proprietary

data—the

structured

and

unstructured

data

that

an

organizationintentionallycollects

and

stores

foritsoperational

anddecision-makingprocesses—can

provide

a

significant

strategic

advantage.It

can

be

used

to

develop

data

products,such

aspersonalizedproductrecommendations,predictivediagnostics

andtreatment

plans,or

optimized

logistics

and

route

planning,

that

allow

both

employeesand

AIagents

todeliverbetterbusinessoutcomes.72%ofCEOsgo

so

faras

to

saythat

proprietary

data

is

key

to

unlocking

the

value

of

generative

AI.211|

Foreword

|Introduction|

Strategy|

Scale|Resilience|Innovation|

GrowthYet,manyorganizationsstruggle

touse

theirdata

topower

AI.CDOsagree

that

thetopdatabarriers

they

faceon

this

front

are

accessibility,completeness,integrity,accuracy,andconsistency(seeFigure2).Fortunately,

AIagentscanhelpaddressthese

challenges.For

example,

they

can

autonomously

cleanse

data,detectanomalies

andpotentialerrors,

and

validateit

againstpredefinedrules

andstandards

toboost

accuracy.AI

agents

can

also

enhance

data

integrity

by

using

end-to-end

lineage

trackingthroughout

the

data

lifecycle—tracing

origin

and

movement

to

provide

transparencyandaccountability.

And

they

can

improve

consistency

by

applying

unified

data

modelsand

synchronizinginformationacross

systems.Unleashing

AI

on

an

optimized

data

estate—rather

than

accepting

today’s

fragmentedlandscape—unlocks

theenterprise’smost

valuabledata.

WhenCDOsenable

teamsand

the

AI

systems

they

rely

upon

to

use

data

more

confidently,

they

can

deliver

AIoutcomes

thatleave

thecompetitionbehind.“Inthelasttwoyears,technologyhasgivenustheability

totreatunstructureddataalmostlikestructureddata—

includingcustomercommunicationsfromcallcenters

andWhatsAppormessages.”IreneYustaMartín,CDO,MasOrange12|

Foreword

|Introduction|

Strategy|

Scale|Resilience|Innovation|

GrowthCDOsthatdeliverhigherAIanddataROI

canbetterarticulatehowdatafacilitateskeybusinessoutcomes—andmoreclearly

measurethe

valueofdata-drivenresults.Figure2Topchallengeslimiting

theuseof

enterprise

data

by

AIAccessibilitySlowresponsetimestodatarequestsbyauthorizedusersand

low

user

satisfactionCompletenessNulloremptyfieldpercentages,missingdatarates,andlowmandatoryfield

compliance

rateIntegrityLimiteddatalineagetrackingand

inconsistent

dataentryacrosssystemsAccuracyHigherrorrates,percentageofincorrectdata,anddatavalidation

failure

ratesConsistencyInconsistentdataformats,including

codeand

nomenclature13|

Foreword

|Introduction|

Strategy|

Scale|Resilience|Innovation|

GrowthPerspectiveData’spowercouple:TheCDO–CISO

alliancecanmakeor

break

your

AIstrategyTo

deliver

value

with

AI

at

scale,

speed

and

security

must

go

hand

in

hand.

Accordingto

recent

IBM

IBV

research,87%of

executives

say

effective

data

security

is

essentialfor

making

the

most

of

AI

investments.But

only

half

say

they

can

protect

sensitivedataandpreventdataleakageinmost

AIusecases.3TherelationshipbetweenCDOsandCISOsaligns

twocoreimperatives:maximizingthe

valueofdataandprotectingitasacritical

asset.

CDOs

focus

on

enablingdata-driven

innovation,improving

decision-making,

and

unlocking

business

growth,

whileCISOs

safeguard

theconfidentiality,integrity,

and

availabilityof

thatdataagainstevolving

threats.

Withoutcoordination,

securitycontrolscan

slowdatainitiatives—or

data

initiatives

can

expose

organizations

to

cybersecurity

complianceorprivacyrisks.An

effective

collaboration

between

CDOs

and

CISOs

helps

ensure

that

data

strategiesare

securebydesign—balancingaccessibility,governance,andprotection.

Thisbuildstrust

with

stakeholders,reducesregulatory

andreputationalrisk,

andenables

theorganization

toconfidentlyleverage