Executive
Perspectives

Unlocking Impact from AI
Customer Service Operations
August 2024

Introduction
We meet often with CEOs to discuss AI—a topic that is both captivating and rapidlychanging. After working with over 1,000 clients in the past year, we are sharing ourmost recent learnings in a new series designed to help CEOs navigate AI.
With AI at an inflection point, the focus in 2024 is on turning AI’s potential into real
profit.

In this BCG
Executive Perspective,
we articulate the visionand value of the futureof customer service
with AIIn this edition, we discuss the future of customer service and the role AI will play inturbocharging growth. We address key questions on the minds of service leaders:• How will the economics of customer service change with AI?
• What will my future customer service team need to look like?
• How do I get started…and where should I focus?
This document is a guide for CEOs and customer service leaders to cut
through the hype around AI in service operations and understand what
unlocks value now and in the future.

1

Copyright © 2024 by Boston Consulting Group. All rights reserved.

• How will the customer experience evolve?

Summary | Unlocking impact from AI in customer service operations

AI impacts allelements ofcustomer service
operations

Executesuccessfully

While most companies focus on support response, transforming upstream is imperative to maximize value– including deflection, self-healing, and prevention to create a competitive edge

Unlocking the full potential of AI in customer service requires an end-to-end reshaping of the entire operationfrom prevention and self-service to service delivery, with focus dimensions being:• Team skilling and structures: Increase productivity, which will lead to fewer but multi-skilled frontline teams withredesigned agent journeys, focusing on data generation for upstream prevention• AI Ops capabilities: Establish new roles and skills that build, shape, and govern AI• Tech ecosystem: Build modular components on layered stack

Develop a value-focused AI strategy with clear and visionary roadmap to realize impact that balances
short-term benefits and unlocking of long-term value
Broad, “at-scale” enablement of service agents and overall change management (including customerfacing communication) is critical to drive adoption – starting with leader enablement
2Copyright © 2024 by Boston Consulting Group. All rights reserved.

Executives
must act on
AI now

As customers spend 14B hours/year contacting customer service, leading players set long-term ambitions toimprove service productivity by up to 60% while enhancing customer experience with positive impacts on
retention and additional sales

The baseline

The future

Value enabled byOn average,
customers spend

Leading companies
set ambition of up to~10%

from AImodels

14B

60%

Hours per year contacting
customer service

Productivity improvementfor customer service~20%

from tech/ITsolutions~70%

from people
and processtransformation

Source: BCG research

3Copyright © 2024 by Boston Consulting Group. All rights reserved.

Leading players set ambitions to improve customer service
productivity by up to 60%

Deep dive: ambition | Examples of leading playerswith high ambitions across industries
Select case examples

Globaltech company

Globalhigh street bank

Globalfinancial company~60% reduction in resolution time
~50% in volume reduction by 2030

~30% productivity improvement~50% cost savings over thenext five years

Global tech company withcontact centers serving
120 countries

Global bank operating in~20 countries, with ~15k
FTE in customer service

Private label and co-brandcredit card issuer with over
100 brands signed in the US

Embedded AI agent assist
tool into ways of working for
support agents

Designed target modelfor omni-channel customer
service, with AI at the heart

Diagnosed current state,
designed a 5-year AI visionand implementation
roadmap

New target operating
model for AI-led support andinterim states across threetime horizonsFirst wave of sprints(tech, people, processchanges) to realize earlyvalue and fund the journey

Defined service vision andstrategy with focus on thetarget customer and agent AIexperience
4Copyright © 2024 by Boston Consulting Group. All rights reserved.

over the next three years

Short-term customer service P&L impact ranges between ~10% and 20%~30-40%Individual use cases
proving uplift on productivityof ~30-40% already today
Source: BCG research

Short-term
P&L value impact

Long-term
P&L ambition~10-20%≥ 60%

Short-term, realizable
P&L impact across the functionof ~10-20%

Leading companies withambition to realize up to 60%
productivity increase long-term
5Copyright © 2024 by Boston Consulting Group. All rights reserved.

Productivity uplift onindividual use cases today

Deep dive: short-term impact | Initial productivity uplift
for tech company already achieved today
BCG case example

What are they doing?

Large tech company with initial AI
deployment for their support agentsfocused on auto-case summarizationand knowledge mgmt. for cases

Defined North Star vision to inform
ambition and direction of the customer
support organization

No unified vision for the desired
outcomes of AI

Stood up an AI-focused program office
to ensure priority activities are executed
againstInconsistent user experience andsiloed, uncoordinated efforts toimplement AI use cases across teams

Developed a detailed impact model toinform savings potential and help
prioritize use cases

Limited enablement plan andchange management efforts leading
to poor adoption

Launched a change management
program to ensure feedback is received
and key messages are disseminatedUnclear use case prioritization
approach for informing the engineeringroadmap

Designed and launched continuous
improvement process of AI-assistantdeployed use cases~80%

Reduction in averagetime agents spend on
case summaries

10-15%

Decrease in needof expert help tosolve cases~10%

Increase in volumeof cases handledby agents
6Copyright © 2024 by Boston Consulting Group. All rights reserved.

Where did they start?

What impact do they
already see today?

In addition to productivity, AI can radically enhance Customer experience…
To-be vision
AI-augmented agent

Fixed, linear processes,“one size fits all”
response, high variancein quality depending on
individual agent

Customer

Solve the 1storder problemCustomer

Explain the bill

“Why is mybill so high?”“Why is mybill so high?”
Commercialthinking

Make across-sell offer

AI augmentation goes beyond
just automating this process“Customer need”
thinking

Is customer on theright plan?

End-to-end process
thinking

Has customer called
before?

Risk-based thinking

Has customer beenscammed?

Personalization

How much detailis needed?

Situational thinking

What is customer’scontext?

Solve the 1st orderproblem

Explain the bill

Commercial thinking

Make a relevant offer

Root-cause thinking

Improve welcome
communications

Optimizedconversation
based onreal-time
context

7

Copyright © 2024 by Boston Consulting Group. All rights reserved.

Dynamic process based on multiple parallel
predictions improving average service quality

As-is
Human agent

… with benefits on both customer satisfaction
and commercial performance
Stronger commercial excellencePre-empt calls and foster self-help

Foster sales excellence• Prevent issues and requests from arising in the first place• Generate proactive actions resolving issues before need for call
• Steer customers to self-service (voice/digital self-help)• Identify real-time sales opportunities• Offer successful selling arguments and provide personalized
sales pitch to agents• Use virtual avatar that proactively engages with customers in asales funnel to close the sale

Make interactions more seamless• Use AI-powered assistants (chat, voice, or virtual [avatar]) tooffer quick, accurate, round-the-clock support across service andsales processes• Generate more personalized answers• Enable more engaging conversational interactions (e.g.,generative self-service IVR)

+10-20 NPS
1. Customer Lifetime Value

Increase cross-/upsell performance• Identify most appropriate by-product and provide sale details• Enrich recommendations with personalized sales arguments

Reduce churn• Spot customers at risk with predictive analysis• Identify root causes of customer dissatisfaction• Guide agents with ladders and personalized scripts+20-35% CLTV1
8Copyright © 2024 by Boston Consulting Group. All rights reserved.

Better customer experiencePre-empt

Self-heal

Self-help

Support response

Leveraging AI toprevent issues
and requests fromarising in thefirst place

Using AI to fixissues before thecustomer notices
them and without
customer effort

Empowering
customers with
AI-based tools andinformation toself-solve their issues

Enabling support
teams and agents toresolve customer
issues in the mostefficient manner

Typical starting point
9Copyright © 2024 by Boston Consulting Group. All rights reserved.

To realize full potential, transformation of the entire customer service
value chain required, with support response being the typical starting point

ProblemPre-empt

Self-heal

Fixed without
customer realization
Prevent
problem fromever existingFix error
before customernotices

Phone

Web
Product/service
problem

Customer
identifies
problemAIidentifies
problemContacts
customer
service
EmailBranchAI

Human

Self-help

Support response

Automation
without humans

Attended byhumans

AI voice bot

Human agent
call

AI chat bot

Human agent
chat

Email form

Human agent
email

Self-service
kiosk

Human agent
meeting

10Copyright © 2024 by Boston Consulting Group. All rights reserved.

Deep dive | AI transforms the entire customer journey,
including upstream prevention

Majority of value is unlocked by upstream prevention and realized
by transforming both technology and people and processes
Illustrative
Self-heal

Self-help

Support response

20%

Upstream prevention(-30%)% productivity benefit

15%

100%

40%

70%

30%

20%

Pre-empt

5%30%
Self-heal

Digitalself-help

Voice
self-help

Handling time
reduction

Multi-skillingand smartrouting

Inefficiencies
from scaling~70%

People andprocesstransformation~30%

Standalone tech

Productivity
benefit

Note: As visualized, productivity benefit per use case often driven by combination of people and process transformation plus standalone tech; Source: BCG research

11Copyright © 2024 by Boston Consulting Group. All rights reserved.

Pre-emptMany have started implementing AI in customer service – we identified
five common pitfalls that prevent value from being realized
Three key success factors

Technologydriven

Limited focus on people, process and change
management leading to low adoption

Fragmentation

Individually built use cases that don’t re-use
common components

Use casecentric

Improving status quo w/o leveraging transformative
power to change the whole service function

POC-focused

Implementation w/o pathway to scale and realize
business value

Perfectionism

Striving for AI to be perfect vs. providing a better
customer experience than the average agent (whileof course still ensuring factually correct responses)

Focus on end-to-end
transformation

Set an ambitious
top-down target

Measure P&L
impact from “day 1”
12

Copyright © 2024 by Boston Consulting Group. All rights reserved.

Common pitfallsAI-driven transformation impacts all elementsof customer service operations

Pre-empt

Self-heal

Self-help

InhouseDemand management and orchestration

Support response|OutsourcedTeam skilling and structures
Workforce management and scheduling
Recruitment and retention
Learning and development (L&D)

Quality assurance (QA)
Knowledge management
AI Ops (new capability)
Tech (partner) ecosystem
Leadership ways of working
Change management
Deep dives

13

Copyright © 2024 by Boston Consulting Group. All rights reserved.

Outsourcer management

Deep dive: team skilling and structures | Three key shifts
Illustrative – not to scale

Service
DeliveryTeamsize

FutureServiceDelivery

Ops Management

Supervisors

Second Line/Back Office

Experts

First LineFirst LineTeam
composition

Operations
Support1

Second Line/Back OfficeCore functions

ServiceDelivery

Ops Mgmt.
Supervisors

Time spent on activities:

Customer Service Technology

AIOpsOPS
Support1AIOpsOPS
Support1

Ops Mgmt.
Supervisors

Operations
Support1Experts
First LineFirst LineRun

Move from people-heavy teams to20-40% smaller frontline teams in 2-3years and 60-70% smaller frontline
teams in the long-term

ServiceDelivery

Core functions

Teamfocus

Ops Mgmt.

Supervisors

ServiceDelivery

ServiceDelivery

Key changes

AI OPS to be included as central
element of the Service Delivery (withlimited role of Operations Support inthe future)

Shift from high share of time spent
on run activities to continuous
improvement and delivery oflong-term change

Customer Service Technology and Data

Continuous improvement and delivery of long -term change

1. Functions including : WFM, knowledge management, partner management, training, QA, etc.

14

Copyright © 2024 by Boston Consulting Group. All rights reserved.

TodayDeep dive: team skilling and structures |Shift to multi-skilled second- and third-level support
Illustrative
Japanese language

ProductSpanish language
A
Product
Mass Market
Product
A
B
Product
AProduct
Product
B
C
Product
Product
B
C
Product
C

ProductSpanish language
A
Product
Mass Market
ProductA
B
Product
Product
Product
B
A&B
C
Product
C
Product
CPremiumStarting point: many discrete
teams in contact center, split by:• Product• Contact reason• Customer segment• Language• Etc.

B2B

Mass Market
and Premium

Prem.

B2B

B2B

Product
A,B,C

Customerprofile I,
issue X

Customerprofile II,
issue Y

Next 2-3 years:

Target state:• Lower volumes handled• Mix of contacts is more complex• Agents assisted by AI co-pilot• Teams become more multi-skilled
and fungible• AI-augmented agents handle broad
set of requests, customers,
languages, etc.
• Routing based on individual best
match, not job title= single-skilled teams= multi-skilled team15

Copyright © 2024 by Boston Consulting Group. All rights reserved.

Japanese language

Deep dive: AI Ops capability | New capabilities and roles
build, shape, and govern AI

Technology specialists whobuild and monitor AI models
and support technology platforms,
leveraging advanced technicalcapabilities

Illustrative
split ofresponsibilities:

10%

CS

90%

Tech

Roles that
SHAPE AIBusiness and functional experts
who collaborate with customerfacing agents to articulate businessneeds and integrate models intobusiness processes

40%

CS

60%

Tech

Roles thatGOVERN AI
Professionals who monitor AI
outputs to ensure software is
driving returns while verifying
technology is being used safely
and ethically

80%

CS

20%

Tech16

Copyright © 2024 by Boston Consulting Group. All rights reserved.

Roles that
BUILD AIEnablementof leaders

AI adoption
by customers

AI adoption
by agents

Agents’ skillset
and capability mix

Build case for change
and narrative, incl.
benefits and metrics
to provide leaderswith tactics for leading
the change anddriving adoption

Nudge customers
to use AI-enabled
self-service throughsuggestions andadjustments totheir options

Establish training
programs, change
networks andfeedback loops todrive adoption

Drive change inworkforce capabilities
through agent
upskilling, new hiring,and cultural change

17Copyright © 2024 by Boston Consulting Group. All rights reserved.

Deep dive: change management | Focus on increasing leadership,
customer, and agent engagement

Long-term ambition of value realization requires time horizonof over 24 months with first benefits possible after 3 months

Boosting impact ofearly use cases

Unlocking AI impact
through new use cases

Reimagining service
experience with AI

Increased adoption andsuccess of early use cases driving
measurable and marketableperformance impact

Initial unlocks of full AI
potential via new high-impact
and moderate-effort use cases

Fundamental shift of entire
service function thattransforms the experience forcustomers and employees

Incremental benefits withincurrent service model

Step-function change inexperience and efficiency

Watershed leap: Radical change
in experience and efficiency(at ~3-24 months)(at ~6-24+ months)

18

Copyright © 2024 by Boston Consulting Group. All rights reserved.

(at ~0-12 months)

Deploying and scaling AI effectively demands an optimized
technology stack tailored to support and expand AI use cases

Copilot

Conversational App

Text

Enterprise System

OtherCaseexample

AI Layer
Guardrails and1monitoring

Content moderation

2 Orchestration

Prompt flow

4

ModelgardenFirst party - Foundationalmodels and pre-trained APIs

Other small
modelsChainsOpen-source
modelsOther small
modelsEmbeddings

5 Model platform

Feature store

1

Guardrails and Monitoring

2

Orchestration

3

Ops and Monitoring

4

Model Garden

5Model Platform

6Integration

7

Infra and CloudTransparency andethical guidelines

Observability/feedback mgmt.
Agents

Key considerations

Ops monitoring
PromptOps
3

LLMOps
MLOps

Model hosting/activation

FMOps

Integration Layer
6
Data Layer
Callrecordings

Accountsandcontracts

ClientprofileProducts

CRMOthers

Internalpolicies

OtherCore Transaction Layer
ERP

C360

Infra and Cloud Layer
7

Public Cloud

Private Cloud

Developed and implemented by BCG

GPU

TPU

The layer will
facilitate
access to theclient system
for retrieving
relevant dataand otherknowledge
resources

Capabilities to ensure correct behavior of AI (e.g., RLHF,
red-teaming, constitutional AI)

New capabilities expected to coordinate different models andcalls to internal and external APIs

New capabilities to ensure correct operation of AI use cases(including models, pipelines, and data)

Model capabilities required for use cases may impact nearterm platform selection. Open source for build use cases.
(expect multiple)

Support multiple models, privacy controls, performance(1-2 preferred platform(s) in short-run)Integrate AI use cases to client enterprise systems to leverageclient knowledge base, CRM system, ERP systems, etc.

Ensure AI choices align with overall hosting strategy(multi/hybrid cloud); plan for higher infra consumption

19Copyright © 2024 by Boston Consulting Group. All rights reserved.

Smart Business Layer

Reusable modules are key to achieve scale at pace

Reusable MODULES …

… that can be integrated into SOLUTIONS

Product modules rely on reusable sub-components that combine to enable
desired functionalities

Product modules integrate into Deep.ai solutions,combined with proven UX/UI

Reusable code assets are bundled into reusable modules …

… enabling sophisticatedcustomer servicerelevant solutions

Silence batch slicing

M1

Call transcription

P2

Whisper on-prem integration

M2

Transcription post-processing

P3

Transcription cleaning

M3

Call summarization

PX

Speaker parser

M4

Parameters extraction

VirtualAssistants… that constitute larger tech capabilities. Combinations ofmultiple modules augment each other's capabilities

AI - MLmodels
Providing featuresand feedback

Real-time
Insights

Input for real-timeand update of batch
for future interactions

BatchcommercialscriptingEnterprise
Knowledge
Base Mgmt.
ExampleReal-time
Insights
SearchEngines

ContentCreation

Cognitive
Reporting

20

Copyright © 2024 by Boston Consulting Group. All rights reserved.

P1

Way forward to a value-focused AI transformation of customer service• Baseline starting point andorganizational challenges today(including baselining of as-is,narrative, tech foundation, etc.)• Define North Star vision/AI
ambition and align key stakeholders• Prioritize and design use cases• Conduct high-level impact
assessment• Set up roadmap for transformationand tech rollout

PoC and value
potential testing• Build and launch PoCs and capture
learnings• Evaluate technical architecture, data
options and build tech readiness
plan• Create detailed impact assessment
and test future value potential• Build out operationaltransformation plans for further
rollout and scale-up

Transformation andchange management• Drive and manage tech rollout• Execute operationaltransformation at scale, e.g.,
integrate AI into key processes,
establish op. model• Drive change management andcommunications plan, e.g., change
agent and customer adoption, etc.
• Select and onboard further techpartners, as needed• Capture learnings and benefits

While some companies currently focus on PoCs, the full potential will be unlocked
through a strong, tailored vision and a successful transformation and change management

21

Copyright © 2024 by Boston Consulting Group. All rights reserved.

AI visionand roadmap

BCG experts | Key contacts for customer service
operations AI transformation
EMESA
Alfonso
AbellaIgnacio
HafnerYasmineHamri

HrvojeJenkač

AnneKleppe

Alexander
Noßmann

Nicholas
Clark

Simon
Bamberger

Kirti
Choudhary

Varun
Khurana

Juan Martin
Maglione

NAMR

22

Copyright © 2024 by Boston Consulting Group. All rights reserved.

MarcusWittig