波士頓咨詢?nèi)斯ぶ悄芘c企業(yè)文化升級(jí)英文版27

商業(yè)市場(chǎng)調(diào)研報(bào)告企業(yè)行業(yè)分析方案行業(yè)文檔手冊(cè)In

collaboration

withNovember

2021The

CulturalBenefits

ofArtificialIntelligence

inthe

Enterpriseby

Sam

Ransbotham,

Fran?ois

Candelon,

David

Kiron,Burt

LaFountain,

and

Shervin

Khodabandeh商業(yè)分析研究報(bào)告文檔分析報(bào)告文檔行業(yè)文檔手冊(cè)AUTHORSSam

Ransbotham

is

a

professor

in

theinformation

systems

department

at

the

CarrollSchool

of

Management

at

Boston

College,

aswell

as

guest

editor

for

MIT

Sloan

ManagementReview’s

Artificial

Intelligence

and

BusinessStrategy

Big

Ideas

initiative.Fran?ois

Candelon

is

a

senior

partner

andmanaging

director

at

BCG

and

the

globaldirector

of

the

BCG

Henderson

Institute.

He

canBurt

LaFountain

is

a

partner

and

managingdirector

at

BCG

and

a

core

member

ofBCG

GAMMA.

He

can

be

reached

atlafountain.burt@.Shervin

Khodabandeh

is

a

senior

partnerand

managing

director

at

BCG

and

thecoleader

of

BCG

GAMMA

(BCG’s

AI

practice)in

North

America.

He

can

be

contacted

atshervin@.REPRINT

NUMBER

63270Copyright

?

Massachusetts

Institute

ofTechnology,2021.All

rights

reserved.be

contacted

at

candelon.francois@.David

Kiron

is

the

editorial

director

of

MITSloan

Management

Review

and

is

program

leadfor

its

Future

of

the

Workforce

and

ArtificialIntelligence

and

Business

Strategy

projects.

Hecan

be

contacted

at

dkiron@.SPECIAL

CONTRIBUTORSMichael

Chu,

Matthieu

Gombeaud,

Su

Min

Ha,

Allison

Ryder,

and

Barbara

SpindelCONTRIBUTORSSylvain

Duranton,

Todd

Fitz,

Carolyn

Ann

Geason-Beissel,

Michele

Lee

DeFilippo,

Janet

Parkinson,Martin

Reeves,

Lauren

Rosano,

Lu

Sun,

and

Rachel

ZhaiThe

research

and

analysis

for

this

report

was

conducted

under

the

direction

of

the

authors

as

partof

an

MIT

Sloan

Management

Review

research

initiative

in

collaboration

with

and

sponsored

byBoston

Consulting

Group.To

cite

this

report,

please

use:S.

Ransbotham,

F.

Candelon,

D.

Kiron,

B.

LaFountain,

and

S.

Khodabandeh,

“The

Cultural

Benefitsof

Artificial

Intelligence

in

the

Enterprise,”

MIT

Sloan

Management

Review

and

Boston

ConsultingGroup,

November

2021.SUPPORTING

SPONSORS商業(yè)分析研究報(bào)告文檔分析報(bào)告文檔行業(yè)文檔手冊(cè)1361317Executive

SummaryIntroduction:

Cultural

Benefits

of

AITeam-Level

Cultural

BenefitsOrganization-Level

Cultural

BenefitsConclusion商業(yè)分析研究報(bào)告文檔

CONTENTS分析報(bào)告文檔商業(yè)市場(chǎng)調(diào)研報(bào)告是指調(diào)查和收集有關(guān)商業(yè)市場(chǎng)需求、消費(fèi)者行為、競爭狀況、市場(chǎng)趨勢(shì)等方面的信息，從而為企業(yè)決策者提供有助于確定市場(chǎng)方向和制定營銷策略的實(shí)用數(shù)據(jù)和建議。在當(dāng)今商業(yè)競爭日益激烈的環(huán)境下，商業(yè)市場(chǎng)調(diào)研報(bào)告對(duì)企業(yè)的發(fā)展至關(guān)重要。商業(yè)市場(chǎng)調(diào)研報(bào)告的形式和內(nèi)容可因行業(yè)和目標(biāo)而異，通常包括市場(chǎng)情況、產(chǎn)品特色、消費(fèi)者行為和需求、競爭對(duì)手及其策略等方面的信息。針對(duì)不同的信息，企業(yè)可以采用各種方式來獲取市場(chǎng)數(shù)據(jù)，如調(diào)查問卷、訪談、觀察等方式。在調(diào)研報(bào)告中，企業(yè)需要對(duì)市場(chǎng)數(shù)據(jù)和信息進(jìn)行分析，得出結(jié)論和建議，并據(jù)此提供具體的市場(chǎng)營銷策略和行動(dòng)方案。此外，企業(yè)還應(yīng)該對(duì)己行動(dòng)的效果及時(shí)追蹤和評(píng)估，并針對(duì)性地調(diào)整和完善市場(chǎng)策略。商業(yè)市場(chǎng)調(diào)研過程中，我們首先需要考慮的是需要確定的目標(biāo)。調(diào)研目標(biāo)應(yīng)據(jù)此制定市場(chǎng)調(diào)研方案。通常包括需求滿足度、市場(chǎng)規(guī)模、產(chǎn)品可行性和客戶類型等。調(diào)研計(jì)劃的其他方面包括調(diào)研方式、調(diào)研時(shí)期和成本等。商業(yè)調(diào)研分析報(bào)告作用行業(yè)文檔手冊(cè)商業(yè)分析研究報(bào)告文檔分析報(bào)告文檔行業(yè)文檔手冊(cè)The

Cultural

Benefits

of

Artificial

Intelligence

in

the

Enterprise1

商業(yè)分析研究報(bào)告文檔

Executive

Summary

The

benefits

of

artificial

intelligence

go

well

beyond

improved

efficiency

and

decision-making.AI

can

also

improve

organizational

effectiveness

and

strengthen

teams

and

enterprise

cultures.

Artificial

intelligence

can

generate

cultural

as

well

as

financial

benefits

for

organizations.With

AI

systems

in

place,

teams

can

perform

tasks

with

more

pride

and

confidence

and

collaborate

more

effectively:They

can

actually

get

stronger.

These

cultural

benefits

can

penetrate

the

foundation

of

business

operations,

improving

assumptions

that

drive

organizational

behaviors

and

ensuring

the

pursuit

of

smarter

goals.

When

conducting

our

research,

we

heard

story

after

story

from

executives

familiar

with

AI

implementations

in

their

organizations.

The

overarching

message

was

clear

and

backed

up

by

survey

data:

Business

culture

affects

AI

deployments,

and

AI

deployments

affect

business

culture.

This

MIT

SMR-BCG

report

—

based

on

a

global

survey

of

2,197

managers

and

interviews

with

18

executives

—

identifies

a

wide

range

of

AI-related

cultural

benefits

at

both

the

team

and

organizational

levels.

Among

survey

respondents

with

AI

implementations

that

improved

efficiency

and

decision-making,

for

example,

more

than

75%

also

saw

improvements

in

team

morale,

collabora-

tion,

and

collective

learning.

Culture

change

from

using

AI

transcends

the

legitimate,

but

myopic,

promise

that

AI

will

liberate

workers

from

drudgery.

These

cultural

changes

are

more

than

a

side

benefit.

AI-related

cultural

and

financial

benefits

build

on

each

other.

Survey

respondents

who

saw

signifi-

cant

financial

benefits

from

their

AI

initiatives

were

10

times

more

likely

to

change

how

they

measure

success

than

those

who

saw

no

such

benefits.

In

some

cases,

AI

helped

leaders

identify

new

performance

drivers,

which

led

to

new

assumptions,

objectives,

measures,

and

patterns

of

behavior,

along

with

new

areas

of

accountability.

AI

also

helped

these

organizations

realign

behaviors

and

become

more

competitive.

Building

a

culture

that

supports

innovation

with

AI

has

an

effect

on

com-

petitiveness.

Our

research

found

that

respondents

who

use

AI

primarily

to

explore

new

ways

of

creating

value

are

far

more

likely

to

improve

their

abil-

ity

to

compete

with

AI

than

those

who

use

AI

primarily

to

improve

existing

processes.

Respondents

who

said

they

use

AI

primarily

to

explore

were

2.7

times

more

likely

to

agree

that

their

company

captures

opportunities

from

adjacent

industries

—

because

of

AI

—

than

respondents

who

use

AI

primarily

to

improve

existing

processes.

Whether

it’s

reconsidering

business

assumptions

or

empowering

teams,

man-

aging

relationships

among

culture,

AI

use,

and

organizational

effectiveness

is

criticaltoincreasingAI’svaluetoanorganization.Thisreportoffersadata-driv-

en

analysis

of

these

relationships

at

both

the

team

and

organization

levels.分析報(bào)告文檔行業(yè)文檔手冊(cè)MIT

SLOAN

MANAGEMENT

REVIEW?

BCG2

商業(yè)分析研究報(bào)告文檔分析報(bào)告文檔一、市場(chǎng)調(diào)研報(bào)告是企業(yè)了解市場(chǎng)動(dòng)態(tài)的窗口。它有利于企業(yè)掌握市場(chǎng)動(dòng)態(tài)，如市場(chǎng)供求情況、市場(chǎng)最新趨勢(shì)、消費(fèi)者的要求以及本企業(yè)產(chǎn)品的銷售情況等方面的市場(chǎng)動(dòng)態(tài)。二、它為企業(yè)客觀判斷自身的競爭能力，調(diào)整經(jīng)營決策、產(chǎn)品開發(fā)和生產(chǎn)計(jì)劃提供了依據(jù)，企業(yè)在市場(chǎng)競爭中要想明確自身所處的位置，就要做市場(chǎng)調(diào)查，從市場(chǎng)調(diào)查報(bào)告中獲取準(zhǔn)確的信息。企業(yè)領(lǐng)導(dǎo)層在考慮開發(fā)新產(chǎn)品，決定產(chǎn)品的生產(chǎn)數(shù)量、品種、花色時(shí)也要先做市場(chǎng)調(diào)查。三、有助于整體宣傳策略需要，為企業(yè)市場(chǎng)地位和產(chǎn)品宣傳等提供信息和支持。四、通過市場(chǎng)調(diào)查所獲得的資料，除了可供了解目前市場(chǎng)的情況之外，還可以對(duì)市場(chǎng)變化趨勢(shì)進(jìn)行預(yù)測(cè)，從而可以提前對(duì)企業(yè)的應(yīng)變作出計(jì)劃和安排，充分地利用市場(chǎng)的變化，從中謀求企業(yè)的利益。商業(yè)調(diào)研分析報(bào)告作用行業(yè)文檔手冊(cè)The

Cultural

Benefits

of

Artificial

Intelligence

in

the

Enterprise3

商業(yè)分析研究報(bào)告文檔

Introduction:

Cultural

Benefits

of

AI

AI

implementations

that

improve

effectiveness

often

strengthen

team

and

enterprise

cultures.

Executives

intimately

involved

with

developing

and

im-

plementing

AI

solutions

offered

numerous

examples

of

how

artificial

intel-

ligence

helped

their

organizations

become

more

efficient

and

make

better

decisions.

What’s

more,

their

team

cultures

were

changing

in

response

to

these

new

levels

of

effectiveness;

the

cultural

changes

encompassed

what

teams

learned,

how

they

learned,

how

they

worked

together,

and,

in

some

instances,

what

they

enjoyed

about

their

work.

Many

teams

that

used

AI

became

stronger

teams.

Pierre-Yves

Calloc’h,

chief

digital

officer

at

Pernod

Ricard,

the

world’s

sec-

ond-largest

seller

of

wine

and

spirits,

offers

a

case

in

point.

The

company

began

using

AI

technology

to

optimize

salespeople’s

store

visits.

Historically,

the

sales

staff

had

relied

heavily

on

their

own

experience

to

decide

which

stores

to

visit.The

company

expected

that

its

new

AI-based

system

of

digital

assistants,

which

uses

data

to

prioritize

stores,

would

encounter

resistance.

However,

salespeople

embraced

the

technology,

which

augments

rather

than

replaces

their

own

knowledge.

Calloc’h

fostered

trust

in

the

system

by

involving

recognized

business

experts

in

the

tool’s

design

and

gathering

extensive

feedback

from

pilot

users.

His

team

ensured

that

the

reasons

for

the

AI

system’s

recommendations

were

clear,

and

clearly

communicated,

to

the

salespeople.

In

addition,

his

analytics

team

used

interviews

with

the

business

experts

to

explore

unexpected

insights

and

feed

those

insights

into

the

recommendation

engine.That

bolstered

the

tool’s

credibility

among

the

experts

and

improved

the

effectiveness

of

the

tool

itself.

According

to

Calloc’h,

salespeople

told

him,

“There’s

no

way

I’m

going

back

to

my

previous

way

of

doing

things.

I

trust

that

the

system

has

been

looking

at

a

lot

of

options

when

recommending

the

20

stores

that

I

should

visit

this

week.

I’ll

add

some

because

there

is

outside

information

that

I

have

and

the

tool

doesn’t

have.”

The

technology

also

provides

employees

with

new

recommendations

that

strengthen

their

sales

pitches.

“The

system

is

recommending

listing

only

relevant

products

matching

the

store

profile,

for

instance,

because

of

the

category

of

consumers

living

around

the

store

and

other

factors.

That

gives

salespeople

more

confidence,

more

clarity,

and

higher

morale,”

says

Calloc’h.

UsingAInotonlydirectlyimprovedefficiencyanddecisionqualitybutindirectly

changed

team

culture

through

its

effects

on

confidence,

clarity,

and

morale.分析報(bào)告文檔行業(yè)文檔手冊(cè)But

AI’s

effects

on

culture

don’t

stop

at

the

team

level.Our

research

further

suggests

that

the

cultural

benefitsof

AI

adoption

can

extend

to

organizations

as

a

whole.For

example,

we

found

that

some

executives

employ

AIto

reassess

strategic

and

operational

assumptions.

In-creasingly,

executives

are

recognizing

that

they

can

useAI

to

discern

performance

drivers

that

they

themselvescannot

identify

through

intuition

and

experience

alone.Radha

Subramanyam,

president

and

chief

research

andanalyticsofficeratCBS,describesthebroadcastnetwork’sefforts

to

critically

assess

long-standing

organizationalassumptions

about

how

it

measures

the

success

of

TVshows.

“I

gave

our

AI

teams

50

years

of

KPIs

[key

perfor-mance

indicators]

and

50

years

of

consumer

research,”ABOUT

THE

RESEARCHThis

report

presents

findings

from

the

fifth

annualresearch

effort

between

MIT

Sloan

Management

ReviewandBostonConsultingGrouponartificialintelligenceandbusi-nessstrategy.Inthespringof2021,wefieldedaglobalsurveyand

analyzed

records

from

2,197

total

respondentsrepresenting

29

industries

and

111

countries.

We

theninterviewed

18

executives

researching

or

leading

AI

initia-tives

in

large

organizations

in

a

broad

range

of

industries,including

financial

services,

media

and

entertainment,retail,

travel

and

transportation,

and

life

sciences.

Ourresearch

offers

a

detailed

analysis

of

a

dynamic

betweenculture,AIuse,andorganizationaleffectiveness.Inadditionto

our

own

field

research,

we

used

existing

organizationalculture

research

to

inform

our

use

of

the

term

“culture.”MIT

SLOAN

MANAGEMENT

REVIEW?

BCG4商業(yè)分析研究報(bào)告文檔

Our

global

survey

attests

that

Pernod

Ricard

isn’t

alone

in

experiencing

AI’s

effect

on

team

culture:

Many

respon-

dents

who

saw

improvements

in

efficiency

and

decision

quality

because

of

AI

also

saw

team-level

improvements

in

morale

(79%)

and

other

cultural

areas.

she

recalls.

“I

said,

‘Here

are

the

things

that

we

believe

are

important

in

this

consumer

research

—

quantitative

and

qualitative.

I’m

giving

you

all

the

raw

data.

Are

the

things

that

I

habitually

look

at

the

right

KPIs

to

drive

my

mega-KPI,

or

are

they

wrong?’”

The

analysis

affirmed

the

utility

of

two

historical

KPIs

but

also

added

two

new

KPIs

to

the

set.

“We

got

better

by

going

through

this

AI

exercise,”

Subramanyam

not-

ed.

“The

analysis

changed

what

we

were

looking

for

and

helped

improve

our

performance.”

For

CBS,

AI

provided

both

the

opportunity

and

the

means

for

reexamining

fundamental

assumptions

about

business

operations

and

organizational

effectiveness.

The

assumptions

that

guide

team

behaviors

and

enterprise

goals

are

central

to

organizational

culture.1

Revising

organizational

assumptions

and

measurements

is

fairly

typical

of

organizations

that

adopt

AI:

64%

of

companies

that

have

integrated

AI

into

their

processes

say

that

their

use

of

AI

led

to

changes

in

their

KPIs.

In

some

cases,

AI

solutions

directly

reveal

new

performance

drivers,

as

at

CBS,

where

they

led

to

new

KPIs.

In

other

cases,

using

AI

enables

stronger

performance,

which

obsolesces

legacy

measurements

that

no

longer

reflect

desired

goals.

Realigning

behaviors

to

achieve

new

ob-

jectives

often

has

a

direct

effect

on

culture.分析報(bào)告文檔OVIMPRPRIMOVE行業(yè)文檔手冊(cè)O(shè)ur

research

identifies

a

continuous

dynamic

amongculture,

AI

use,

and

organizational

effectiveness.

(seefigure

1.)We

use

this

Culture-Use-Effectiveness

(C-U-E)dynamic

to

explain

mutually

reinforcing

relationshipsat

both

the

team

and

organization

levels.These

relation-ships

offer

a

useful

perspective

on

how

AI

adoption

caninfluence

managerial

assumptions,

team

behaviors,

andoverall

organizational

competitiveness.The

C-U-E

dynamic

is

difficult

to

achieve

at

scale.

Exec-utives

need

to

learn

what

AI

can

do

for

teams

and

theorganization,

and

develop

a

common

language

for

deci-sion-makingwithAI.Managersneedtoelicitactivesupportfrom

employees

who

must

work

with

AI

solutions

thatreplace

or

augment

existing

practices.

After

AI

solutions’initial

implementation,

organizations

must

continuouslyadapt

them,

which

requires

ongoing

participation

fromAI

teams

and

end

users.

Once

AI

solutions

prove

to

beeffective,

the

resulting

cultural

and

productivity

benefitsencourage

even

more

AI

use

throughout

the

enterprise.AI

that

is

effective

at

the

team

level,

however,

doesn’talways

yield

financial

success

at

the

organization

level.Only

11%

of

organizations

in

our

survey

attributed

sub-stantial

financial

benefits

to

their

AI

initiatives,

which

isthe

same

result

we

obtained

from

our

survey

last

year.2

ItmaybethatfewcompaniesareimplementingAIatascalesufficient

to

generate

“substantial”

financial

benefits.

Butanother

possible

explanation

is

that

those

organizationsthat

obtain

substantial

financial

benefits

have

begun

tomaster

the

C-U-E

dynamic.

They

learned

both

how

toculturally

adopt

and

benefit

from

AI,

and

how

to

use

AIto

glean

financial

rewards.

Our

research

suggests

thatthese

are

connected,

not

separate,

activities.EFFECTIVENESSCULTURE

EAI

USEFIGURE

1The

Culture-Use-Effectiveness

DynamicImproving

each

component

of

the

C-U-E

dynamic

canlead

to

a

virtuous

cycle

of

cultural

improvement.

IMPROVEThe

Cultural

Benefits

of

Artificial

Intelligence

in

the

Enterprise5商業(yè)分析研究報(bào)告文檔分析報(bào)告文檔商品和服務(wù)是由生產(chǎn)者轉(zhuǎn)移到消費(fèi)者而形成市場(chǎng)行銷活動(dòng)的鏈接方式，或投資者對(duì)自己確立的項(xiàng)日存有疑惑，而委請(qǐng)專業(yè)的調(diào)查人員或第三者，作有系統(tǒng)地、客觀地、廣泛地且持續(xù)地搜集相關(guān)資料，加以記錄，分析，衡量與評(píng)估，提供相關(guān)分析，結(jié)論與建議，以供企業(yè)經(jīng)營者決策參考之行為。市場(chǎng)調(diào)研范圍1·市場(chǎng)研究：市場(chǎng)潛在需求量，消費(fèi)者分布及消費(fèi)者特性研究。2.產(chǎn)品研究：產(chǎn)品設(shè)計(jì)，開發(fā)及試驗(yàn)；消費(fèi)者對(duì)產(chǎn)品形狀、包裝、品味等喜好研究；現(xiàn)有產(chǎn)品改良建議，競爭產(chǎn)品的比較分析。3,銷售研究：公司總體行銷活動(dòng)研究，設(shè)計(jì)及改進(jìn)。4.消費(fèi)購買行為研究：消費(fèi)者購買動(dòng)機(jī)，購買行為決策過程及購買行為特性研究。5.廣告及促銷研究：測(cè)驗(yàn)及評(píng)估商品廣告及其它各種促銷之效果，尋求最佳促銷手法，以促進(jìn)消費(fèi)者有效購買行為。6.行銷環(huán)境研究：依人口、經(jīng)濟(jì)、社會(huì)、政治及科技等因素變化及未來變化走勢(shì)，對(duì)市場(chǎng)結(jié)構(gòu)及企業(yè)行銷策略的影響。7.銷售預(yù)測(cè)：研究大環(huán)境演變，競爭情況及企業(yè)相對(duì)競爭優(yōu)勢(shì)，對(duì)于市場(chǎng)銷售量作長期與短期預(yù)測(cè)，為企業(yè)擬定長期經(jīng)營計(jì)劃及短期經(jīng)營計(jì)劃之用。商業(yè)調(diào)研分析報(bào)告作用V冊(cè)業(yè)文檔手行OIMPRPRIMOVEAI-based

solutions

that

generate

new

ways

of

workingcan

incite

resistance

from

teams

entrenched

in

existingcultures.

Anju

Gupta,

vice

president

of

data

science

andanalyticsatNorthwesternMutual,acknowledgesthatwhencompanies

introduce

new

AI

initiatives,

“there

is

this

cultivate

team

acceptance

of

AI,

such

as

by

including

end

users

in

the

development

process,

building

trust

in

AI

system

performance,

and

encouraging

teams

to

be

open

to

changing

their

work

processes.

(see

the

sidebar“building

trust

to

cultivate

ai

benefits,”

page

7.)each

element

in

the

dynamic.FIGURE

2TheTeam

Culture-Use-EffectivenessDynamicAsAI

helps

improve

efficiency

and

decision

quality,team

culture

benefits.TrustUnderstandingCollective

learningClarity

of

rolesCollaborationMoraleFIGU

R

Ee

and

decision

teamnatural

resistance

that

you’ll

bump

up

against.”

Culture

quired

to2adopt

AI

from

cultural

changes

that

emerge

after

adopting

AI.

Figure

2

shows

the

C-U-E

dynamic

at

the

team

level:

Team

culture

can

improve

AI

adoption,

AsAI

helps

improvewhich

ciency

turn

improvesquality,

effectiveness,

which

in

turn

team

improves

bene

team

culture.

Learning

is

a

key

component

ofculture

ts.AI

USEEFFECTIVENESSTEAMCULTURE

IMPROVE

E

ciencyDecision

qualityEMIT

SLOAN

MANAGEMENT

REVIEW?

BCG6商業(yè)分析研究報(bào)告文檔

Team-Level

Cultural

Benefits分析報(bào)告文檔行業(yè)文檔手冊(cè)FIGURE

3AIAdoption

Depends

onTrustAI

Adoption

Depends

on

TrustInsufficient

understanding

and

training

are

the

greatestdata

used,obstacles

to

building

trust

inAI.you’re

starting

small,

you’re

building

confidence.And

Itook

on

quite

a

large,big-bang

approach

with

this

thing,BUILDING

TRUST

TO

CULTIVATEAI

BENEFITSBoth

financial

and

nonfinancial

benefits

fromAI

dependonemployeesworkingwithandtrustingAI.Yetoursurveyrespondentsdescribednumerousreasonswhyendusersmay

mistrust

AI

solutions.

(SEE

FIGURE

3.)people

themselves

are

part

of

the

process

rather

thanbeing

subjected

to

it.”Buttheamountofuserinvolvementisn’taneasydecision.Too

little

context

behind

decisions

(34%)

or,conversely,too

much

information

(17%)

can

erode

trust.

SanderStomph,former

head

of

operational

excellence

at

Dutchairline

KLM,

recognizes

that

tension

in

working

with

AIsolution

users.“What

we

did

the

past

couple

of

years

isdevelop

shoulder

to

shoulder

with

the

people

who

areactually

going

to

use

these

things,

up

to

the

customer,”he

explained.

“If

it

impacts

a

customer,

you

develop

italso

with

customers.If

it

impacts

a

planner,you

developit

with

planners

and

you

explain

it

to

them,

even

up

tothe

point

that

you

say,‘Hey,

we

don’t

know

the

price

ofthis,

but

we’re

going

to

put

an

amount

of

200

euros

asData

of

can

only

happen

ifexpectations

(20%),or

just

incorrect

solutions

(14%)

allcancontributetomistrustinthesystem.ColinLenaghan,senior

vice

president

of

global

net

revenue

managementatPepsiCo,recognizeshowsmallimprovementscanaddup.PepsiCo

believes

that

working

to“prove

stuff

out

andvery

overtly

socializing”cumulatively“builds

confidence,builds

trust,and

helps

you

to

move

from

one

step

to

thenext.”

Lenaghan

describes

how

the

early

“capabilitiesimmediately

inspired

trust

and

credibility”among

thosewho

used

PepsiCo’sAI-based

promotional

optimizationtool.“That’s

a

really

important

process

for

us,becauseSystem

DesignToo

much

or

too

little

contextData

quality

and

performance

concernsusersInsu

cienttraining

(end

think

that’s

going

to

be

important,because

if

you

reallyand/or

executives)

I

just

think

it’s

overwhelming.”

a

proxy.

Do

you

agree

that

we

put

in

200

euros?

As

theClose

to

half

the

respondents

believed

that

mistrustof

AI

stemmed

from

a

lack

of

understanding

(49%)

ortraining

(46%).

Paul

Pallath,

global

technology

head

ofdata,

analytics,

and

AI

at

Levi

Strauss

&U

Co.,

said

that

technology“becomes

more

than

just

a

vague

tool

andthe

company

invested

widely

to

improve

understanding;

Stomphseesthetemptationto“dumbitdown”andsimplyfrom

the

retail

store

to

people

in

ITto

people

in

business,

says

that

KLM

works

“to

be

genuine

and

connect

with

people,to

make

sure

that

they

really

like

these

solutionsMay

2021,consisted

of

more

than

40

employees

from

14locations

around

the

world.

Pallath

believes

the

invest-ment

was

worth

it

because“they

need

to

have

trust.And

Still,no

amount

of

user

education

can

overcome

a

poorbuilding

trust

inAI/MLand

machinesUnderstanding

and

tool.

Training

insufficient

quality

(31%),

failure

to

meetF

I

G

RE

3

31%Quality

of

datanot

trustedby

users

20%Performancedoes

not

meetuser

expectations

14%AI

solutionsappear

incorrect50%46%

34%AI

solutionprovides

toolittle

contextbehinddecisions

17%AI

solutionprovides

too

muchinformation

andoverwhelms

usersSystem

DesignToo

much

or

too

little

contextFIGURE

3

Insu

cient

understanding

of

theAI

solution

(e.g.,

KPIs

targeted)Insu

cient

understanding

and

training

arethe

greatest

obstacles

to

building

trust

inAI.

50%Insu

cientunderstandingof

theAI

solution(e.g.,data

used,KPIs

targeted)

46%Insu

cienttraining

(end

usersand/or

executives)Understandingand

TrainingUnderstanding

and

TrainingSystemDesign

(multi-select

question;

responses

Benefits

Artificial

100%)

Intelligence

in

the

EnterpriseData

quality

and

performance

concernsThe

Cultural

mayof

exceed7商業(yè)分析研究報(bào)告文檔分析報(bào)告文檔

(multi-select

question;

responses

may

exceed

100%)行業(yè)文檔手冊(cè)After

implementingAI

solutions,teams

report

improvedcollective

learning,clarity

of

roles,collaboration,and

morale.17%said

they

have

seen

either

noimpact

or

a

decrease

in

e

ciencyand

decision

quality

since

theirteams

implemented

AI.

FIGURE

4E

ective

Use

of

AI

Changes

Team

Culture

After

implementingAI

solutions,respondents

report

improved

collective

learning,

clarity

of

roles,collaboration,and

morale

on

their

teams.58%agree

teams

saw

improvementsin

both

e

ciency

and

decisionquality

since

their

teamsimplemented

AI.

21%Morale

20%Collaboration

36%Collectivelearning

8%Clarityof

roles

79%Morale

78%Collaboration

87%Collectivelearning

65%Clarityof

rolesMIT

SLOAN

MANAGEMENT

REVIEW?

BCG8

商業(yè)分析研究報(bào)告文檔FIGURE

4ImprovingTeam

EffectivenessWithAI

BolstersTeam

Culture

(percentage

of

respondents

reporting

improvement

in

both

e

ciency

and

decision

quality

or

neither

e

ciency

nor

decision

quality)

(percentage

of

respondents

reporting

improvement)分析報(bào)告文檔隨著各種問題的不斷出現(xiàn)，對(duì)策建議類調(diào)研報(bào)告成為了越來越重要的工具，可以幫助企業(yè)和組織制定有效的戰(zhàn)略和方案。本次調(diào)研共收集了31篇有關(guān)對(duì)策建議類調(diào)研報(bào)告，發(fā)現(xiàn)了一些有趣且關(guān)鍵的共性和差異。首先，從研究內(nèi)容來看，這些報(bào)告所關(guān)注的問題是非常多樣化的。其中有些報(bào)告關(guān)注的是社會(huì)問題和政策，如貧困和教育問題，而另外一些報(bào)告則更加關(guān)注企業(yè)和組織的內(nèi)部問題，如管理和市場(chǎng)營銷。這種多樣性并不能算是這些報(bào)告的缺陷，相反，它說明我們的社會(huì)和組織面臨的挑戰(zhàn)十分繁多，需要我們從各個(gè)方面入手才能夠解決問題。其次，這些報(bào)告在調(diào)查方法和數(shù)據(jù)分析方面也存在差異。大部分的報(bào)告采用了定性和定量結(jié)合的方式，通過問卷調(diào)查、實(shí)地考察和專家訪談等方式收集數(shù)據(jù)。然而，也有一些報(bào)告采用了更為創(chuàng)新的技術(shù)，如大數(shù)據(jù)分析和人工智能技術(shù)。這些新技術(shù)雖然還處于試驗(yàn)階段，但它們可能會(huì)以越來越多的方式成為調(diào)研方法的重要組成部分。最后，這些報(bào)告在對(duì)策和建議方面表現(xiàn)出了不同的風(fēng)格和實(shí)用性。有些報(bào)告提出了具有長遠(yuǎn)發(fā)展戰(zhàn)略的行動(dòng)方案，而另外一些則更注重于針對(duì)特定問題提供現(xiàn)實(shí)可行的解決方案。這些不同的風(fēng)格反映了報(bào)告的作者們的不同經(jīng)驗(yàn)和專業(yè)背景，并吸引了各個(gè)方面的讀者。商業(yè)調(diào)研分析報(bào)告作用冊(cè)行業(yè)文檔手Certainly,

culture

influences

AI

adoption.

This

well-re-searched

connection

usually

involves

team

memberslearning

about,

and

coming

to

trust,

AI

outcomes.

Inearlier

research,

we

identified

mutual

learning

as

a

valu-able

contributor