June 2017, IDC #US42749217
White Paper
A Trillion-Dollar Boost: The Economic Impact of AI on
Customer Relationship Management
Sponsored by: Salesforce
John F. Gantz
Gerry Murray
David Schubmehl
Dan Vesset
Mary Wardley
June 2017
IN THIS WHITE PAPER
Artificial intelligence (AI)1, a technology almost as old as the computer industry itself, has come into
widespread awareness with the advent of personal assistants and bots (Amazon's Alexa, Apple's Siri,
Google's Assistant), image recognition (Facebook), personalized recommendations (Netflix, Amazon),
and more. These innovations have been driven by a manifold increase in processing power, lower-cost
hardware, and the exploding creation and availability of data. IDC's forecast for cognitive and AI
systems calls for the global market to jump from $7.9 billion last year to $46.3 billion in 2020.
This White Paper uses IDC market data, IDC's AI/CRM Economic Impact Survey of 1,028
organizations worldwide, and 20 years of IDC's economic impact modeling to forecast how AI will
affect the global economy. It forecasts business revenue growth and job creation (or destruction)
based on AI applied to customer relationship management (CRM) activities.
In addition to the economic impact of AI on CRM as a broad category, it also includes an estimate of
the economic impact attributable to Salesforce's customer base.
EXECUTIVE SUMMARY

 Extrapolating from survey responses and IDC's economic impact model, IDC calculates that AI
associated with CRM activities will boost global business revenue from the beginning of 2017
to the end of 2021 by $1.1 trillion.
 Net-new jobs associated with this revenue could, if respondent opinions bear out, reach more
than 800,000 by 2021 in direct jobs, and 2 million if you add in indirect and induced jobs. This
is a net-positive figure in that it includes an estimate of jobs lost to automation from AI.
 Salesforce customers should account for $293 billion of the total aggregated revenue and
more than 155,000 of those direct jobs by the year 2021.

IDC's AI/CRM Economic Impact Survey, 28% of all respondents said their organizations have
already adopted AI and another 41% said they will adopt it within two years. In addition, 34%

1 IDC classifies AI as part of a constellation of cognitive system technologies – see Table 1 for a list. For the sake of
brevity, we use the term AI to refer to them all in this White Paper.
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of Salesforce customers report they are AI adopters. The year 2018 will be a major year for AI
adoption.
 The adoption pattern mirrors IDC's forecasts that by 2018, 75% of enterprise and ISV
development will include cognitive/AI or machine learning functionality in at least one
application.2
 Underpinning the adoption of AI, 46% of AI adopters report that more than 50% of their CRM
activities are executed using the public cloud. Cloud vendors are expected to lead in the
delivery of AI to customers by embedding AI into their applications.
Economic Benefits Summary of AI Applied to CRM
Figure 1 shows the summary of economic benefits as applied to CRM, calculated by IDC based on
survey responses and its economic impact models.
FIGURE 1
Worldwide Financial Improvement and Jobs from AI-Assisted CRM, 2017–2021

Source: IDC, 2017

AI: A Market Accelerator
IDC analysts have an eye-opening forecast for AI adoption, as shown in Figure 2.
In fact, in an IDC FutureScape document, written back in 2015, entitled IDC FutureScape: Worldwide
Big Data and Analytics 2016 Predictions (IDC #259835, November 2015), IDC stated:
Cognitive systems [AI] will be the next major disruption in the world of technology and
will significantly impact businesses, healthcare, work, society, and our economies in

2 Excerpted from IDC FutureScape: Worldwide Analytics, Cognitive/AI, and Big Data 2017 Predictions (IDC
#US41866016, November 2016).
0
500,000
1,000,000
1,500,000
2,000,000
2,500,000
0
300
600
900
1,200
2017
2018
2019
2020
2021
Net increase in jobsNet increase in financials ($B)Net increase in financials ($B)
Net increase in jobs
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general. Cognitive systems will cause significant changes in the way that people get
advice, make purchases, and do their daily work.
FIGURE 2
Worldwide Spending on Cognitive/AI Systems Including
Hardware/Software/Services, 2015–2020

Source: IDC, 2017

This growth in spending will come in all technology areas. In IDC's AI/CRM Economic Impact Survey,
IDC found almost all technologies of interest, as shown in Table 1.
Note that in the survey, we prefaced the questions on AI adoption by saying:
"Artificial Intelligence (AI) comprises a set of technologies that use natural language
processing, machine learning, knowledge graphs, and other tools to answer
questions, discover insights, and provide recommendations. Systems using AI
hypothesize and formulate possible answers based on available evidence, can be
trained through the ingestion of vast amounts of content, and automatically adapt and
learn from their mistakes and failures."


5
8
13
20
34
46
0
5
10
15
20
25
30
35
40
45
50
2015
2016
2017
2017
2019
2020
($B)
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TABLE 1
AI Technology Choices (% of Respondents)
Q. What type of AI are you planning to use or exploring?

All Respondents
AI Adopters
Cognitive/AI system platforms
25
29
Machine learning
28
34
AI-based data preparation and enrichment tools
35
48
Machine vision/image recognition
26
31
Voice/speech recognition
30
41
Text analysis and natural language processing
27
34
Bots and virtual digital assistance solutions
21
32
Social media pattern analysis, sentiment analysis
33
35
Advanced numerical analysis (e.g., IoT streaming, machine logs)
31
41
Supporting technologies: ontologies, knowledge base curation, dialog management,
Q&A processing, and so forth
38
40
n = 1,028 total (292 current AI adopters)
Source: IDC's AI/CRM Economic Impact Survey, 2017

While it is true that respondents were being asked specifically about their potential use of AI in CRM
activities, these activities nonetheless cover a large spectrum of activity and touch almost all facets of
an enterprise. Table 2 shows the way we broke down CRM and, for AI adopters, which activities fell
into respondents' top 4 for adoption.


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TABLE 2
Catalog of CRM Activities: Top 4 for Adoption (% of Respondents)
Q. Which categories of CRM activity do you think AI could benefit the most?

AI Adopters
Corporate marketing, branding, advertising
39
Product or service marketing
39
Marketing operations/field marketing
39
Customer support
43
Digital commerce
40
Customer analytics
38
Customer influenced product or service design
40
Product or service pricing, finance
38
Customer billing, inventory, logistics, and fulfilment support
41
Partner management
41
n = 1,028 total (292 current AI adopters)
Source: IDC's AI/CRM Economic Impact Survey, 2017

It is obvious that each AI use has its specific adherents. Most enterprises will adopt AI in a variety of
CRM areas.
The AI Adoption Curve
AI is still at the beginning of its "S curve" of adoption, but the respondents we surveyed expect this
year (2017) and the next (2018) to be watershed years — as planning and piloting turn into
implementation. In fact, more than 60% expect to have either projects or pilots in place this year, and
55% expect to have AI implementations in place by 2018.
Figure 3 shows how the respondents' plan-pilot-implement trajectory works out over the next five
years, with expectations that some of those with no plans today will join the fold in the outer years.
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FIGURE 3
Survey Respondents' AI Adoption Plans, 2016–2021

n = 1,028 total
Source: IDC's AI/CRM Economic Impact Survey, 2017

This adoption wave mirrors that of IDC's cognitive/AI systems forecast (refer back to Figure 1), which
grows by a factor of 9 from 2015 to 2020. The adoption forecast for implemented AI projects grows by
a factor of 10 from 2016 to 2021.
Is this adoption profile realistic? IDC believes it is, as analysts are reporting that vendor investment in
embedded AI for enterprise applications has picked up considerably, even just in the past six months.
By offering embedded AI, technology vendors — and especially cloud solution vendors — can make
implementation a near-automatic event for most customers.
The survey conducted for this study indicates that enterprises are ready to take advantage of AI
availability when it appears. In the document referenced in the Executive Summary section, IDC
forecasts that 2018 will be a watershed year for AI adoption in general.
In that same document, IDC predicts that "by 2018, new cloud pricing models will emerge for specific
analytics workloads, contributing to five times higher growth in spending on cloud versus on-premise
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analytics solutions." This is more corroboration for the adoption timeline predicted by survey
respondents.
The AI Economic Impact
Because AI is still early in adoption, all predictions come with a caveat that they rely on current
opinions of respondents and expectations for software, IT, cloud computing, and economic growth that
may be superseded by events.
On the other hand, IDC has been forecasting IT markets for more than 50 years, many of them at the
same place on the adoption curve as AI. This includes the internet, enterprise ERP and CRM, social
media, smartphones, business analytics, and many others. In addition, respondents surveyed
assessed their own confidence on their estimates of the financial improvement AI could provide for
CRM activities. In general, they rated themselves 3.5 on a scale of 1–5 (5 = very confident). Those that
were already AI adopters rated themselves 3.9.3 And early AI adopters in the news, such as USAA
(fraud detection), GE (jet engine blade quality control), and Under Armor (fitness optimization) are
positive on early results.
To develop an estimate of the economic impact AI technologies could have on enterprises adopting
them to improve their CRM activities, IDC relied on:
 Macroeconomic information on business revenue in a country (2016 forecast to 2021) and the
basic makeup of business expenses by major function (customer support, marketing and
sales, production, etc.)

IDC analysts' estimates of the percentage of revenue (and expenses) that might be affected by
CRM activities by category
 Survey results on how much AI could improve CRM activities in the first year of AI
implementation, and what this improvement could mean in terms of efficiencies for a company
in cost savings and new potential revenue
 An economic impact model that pulls all the underlying data together and forecasts the results
out to 2021 (The model is based on IDC's Economic Impact of IT model, which has been
updated yearly since 2002. It includes IT spending by 54 countries, GDP and population
estimates and forecasts, revenue per employee, and ratios of IT spend to GDP.)
Table 3 shows the results of the IDC economic modeling and some of the underlying assumptions.


3 One could argue that AI adopters rate themselves more highly because they are already invested, but IDC
believes it is more likely because they have hands-on experience with the technology.
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TABLE 3
Forecast Results — AI Impact
1. Results are projected from surveys and rely on estimates made by respondents on the expected financial improvements in
key categories of AI-assisted customer relationship management activities. The forecast assumes that these estimates are
correct.
2. Financial estimates are based on estimates of "first year" improvement from full AI implementations; forecasts are
extrapolated across expected migration from planning to pilot to implemented projects.
3. The improvement forecast is of categories of activity (e.g., corporate marketing, digital commerce, and customer analytics).
They are not estimates of ROI for the AI software. They rely on conservative estimates by IDC of the extent to which each of
these entities might affect company revenue, expenses, or productivity. They also rely on estimates of the penetration of
software in customer relationship management activities.
4. Net-new jobs created are based on the ratio of new revenue to jobs required to support that revenue. They assume that 50%
of the net-new revenue will support increases in labor and the rest will go for capital and other operating expenses that may
replace jobs lost to automation; IDC understands that there is significant debate about the long-term impact of AI on jobs but
presents the data here as based on opinions of surveyed respondents.
5. By way of comparison, IDC forecasts that the worldwide market for cognitive/AI systems — including software, hardware,
and services — will surpass $46 billion in 2020; the worldwide CRM software (only) market is expected to surpass $44 billion
by 2020.
6. The estimate of the economic impact of AI in customer management among Salesforce customers relies on survey results
and modeling that allocates Salesforce's share of the economy by its share of the CRM software market.
Worldwide financial improvement from AI in
customer management activities
2017
2018
2019
2020
2021
Five-Year
Sum
Increased revenue ($B)
26
112
154
196
237
726
Lowered expenses ($B)
9
41
58
72
85
265
Improved productivity ($B)
4
19
26
33
39
121
Worldwide: increased revenue, lowered
expenses, improved productivity ($B)
40
172
238
301
362
1,112
% of business revenue
0.0
0.1
0.1
0.2
0.2
0.1
Worldwide net increase in direct jobs
50,287
315,079
166,013
148,704
143,651
823,734
Worldwide net increase in indirect/induced jobs
75,203
471,819
254,784
228,582
219,859
1,250,247
Worldwide net increase in direct and
indirect/induced jobs
125,490
786,897
420,797
377,286
363,510
2,073,980
Source: IDC's AI/CRM Economic Impact Survey, 2017

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While the aggregate numbers look large — billions to a trillion — note that the net figure is still just a
small increase to global revenue — 0.13%. This reflects the early stages of the AI revolution on global
businesses.
For those who still believe the number seems large, consider what is entailed in an IT implementation.
The spending on IT software, services, and hardware itself is often small compared with spending on
staff (IT and operational), operations, non-IT capital goods, and more. In fact, spending on external IT
— which now permeates most enterprises in the world — represents less than 1% of the world's
business revenue and generally less than 5% in even the most IT-rich enterprises.
IDC research shows that even in cloud-based solutions, any single implementation will require
additional spending — on other cloud services, consulting, networking, security, and more.
In short, IT represents a leveraged investment — paying back many times its base costs. A new
technology, like AI, could be even more leveraged. IDC itself classifies cognitive systems/AI as an
"innovation accelerator" on its website.
Some of the ways AI is expected to impact CRM activities are:
 Speeding up sales cycles

Improving lead generation and qualification
 Solving customer support problems faster
 Helping companies improve brand campaigns and recognition
 Lowering costs of support calls while increasing resolution rates
 Lowering the cost of recruiting employees and partners

Increasing revenue from optimized product marketing
 Optimizing pricing
 Optimizing distribution logistics
 Preventing loss through fraud detection
What about the impact of AI on jobs? IDC is well aware there is significant debate about the long-term
impact of AI on jobs and presents the forecast here as based on the opinions of surveyed respondents.
It also represents a conservative view of how the additional revenue from the forecast financial
improvements will be put to use. The forecast embodies an assumption that AI will lead to net-positive
financial benefits, which will drive job growth. Some roles may be eliminated, and others will be
created or enhanced, not unlike the change in jobs in IT departments during the advent of the cloud.4

4 Students of the subject may wish to view this article in The Wall Street Journal, published December 11, 2016,
entitled “Automation Can Create More Jobs” at www.wsj.com/articles/automation-can-actually-create-more-
jobs-1481480200. A countering view can be found in an article in The New York Times, published March 17, 2017,
entitled “Evidence that Robots are Winning the Race for U.S. Jobs” at
www.nytimes.com/2017/03/28/upshot/evidence-that-robots-are-winning-the-race-for-american-
jobs.html?_r=1
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The Salesforce Economic Impact
With Salesforce as the market leader in CRM software in general and cloud-based CRM in particular,
and as a proponent of AI-assisted solutions, its customers should drive a noticeable portion of the
benefits and jobs coming from AI in CRM.
By design, the survey conducted for this study included more than 400 Salesforce customers, enough
to allow us to project their economic impact.
Table 4 shows the results of the IDC economic modeling.
TABLE 4
The Economic Impact of AI-Assisted Customer Relationship Management of
Salesforce Customers, 2017–2021
Worldwide Financial Improvement from AI in Customer
Management Activities
2017
2018
2019
2020
2021
Five-Year
Sum
Increased revenue ($B)
7
29
41
53
66
195
Lowered expense ($B)
2
10
14
18
23
68
Improved productivity ($B)
1
5
6
8
10
30
Worldwide: increased revenue, lowered expenses,
improved productivity ($B)
10
43
61
79
99
293
% of business revenue
0.0
0.1
0.2
0.2
0.2
0.2
Worldwide net increase in direct jobs
9,569
55,814
29,539
28,821
31,554
155,298
Worldwide net increase in indirect/induced jobs
14,310
83,580
45,335
44,303
48,295
235,822
Worldwide net increase in direct and indirect/induced jobs
23,879 139,394
74,874
73,124
79,849
391,121
Note: Totals may not be exact due to rounding. The survey included 429 Salesforce customers.
Source: IDC's AI/CRM Economic Impact Survey, 2017

Specific Use Case Adoptions
In addition to surveying about AI adoption to support the various components of CRM, the survey also
polled about some specific use cases of AI. Figure 4 shows the percentage of respondents who said
they use or are planning to use each case.
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FIGURE 4
Specific AI Use Cases

n = 1,028 total (292 current AI adopters)
Source: IDC's AI/CRM Economic Impact Survey, 2017

Perhaps the strongest conclusion that can be drawn from Figure 4 is that those using and planning to
use AI are doing so in many different ways. And those closest to implementation are doing so even
more so. These forward-looking companies are planning, piloting, implementing, optimizing, and
improving.
The Nature and Attitudes of AI Adopters
IDC's AI/CRM Economic Impact Survey of 1,028 enterprises in Australia, Canada, France, Germany,
Japan, the United Kingdom, and the United States probed not only estimates of value creation from AI
but also behaviors and attitudes of those knowledgeable about CRM in their enterprises and the future
of AI in them.
Some stats on the respondents themselves:
 The average enterprise polled had 1,966 employees; AI adopters (28% of the sample) had
2,521.
87
61
64
68
75
83
87
80
83
74
55
57
51
47
59
61
63
66
0
10
20
30
40
50
60
70
80
90 100
Email marketing
Credit risk scoring
Fraud detection
Cross-selling and upselling
Chatbots for customer service or product
selection
Customer service case classification/routing
Sales forecasting
Sales opportunity scoring
Sales and marketing lead scoring
(% of respondents)
All respondents
AI adopters
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 Respondents were polled from a cross section of industries, with none accounting for more
than 20% of the total.
 42% of the sample were Salesforce customers, which accounted for 50% of AI adopters.
 29% of the total sample said that 50% or more of their CRM activities were public cloud based;
46% of AI adopters said so.
 77% of the total sample said they were either decision makers about AI adoption or on a team
that made those decisions; 84% of AI adopters said so.
 87% of the total sample were in management positions or higher.
 When asked about potential data sources for the AI systems, respondents rated data from
their CRM systems highest (not surprisingly) and data from third parties lowest. Stack-ranked
in the middle was data from ERP systems, data from data warehouses, and data from social
media. But all were seen as potential data sources.
The respondents also tended to be positive on AI. In one question, they rated their agreement with
several statements about AI — on a scale of 1 to 6, with 6 being the highest level of agreement — as
shown in Figure 5.
FIGURE 5
Attitudes on AI

n = 1,028 total (292 current AI adopters)
Source: IDC's AI/CRM Economic Impact Survey, 2017

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In another question, they reported their opinions of AI on jobs as shown in Figure 6.
FIGURE 6
Attitudes on AI and Jobs

n = 1,028 total (292 current AI adopters)
Source: IDC's AI/CRM Economic Impact Survey, 2017

Note that AI adopters are much more bullish about the net impact of AI on labor.
ESSENTIAL GUIDANCE
Lessons from the Data and a Call to Action

It is clear from IDC's forecasts — and the survey for this project — that AI adoption is about to
begin in earnest.
 As with the adoption of any "innovation accelerator" technology, early adopters and fast
followers will gain early, critical experience, which should lead to a competitive advantage.
 The prevalence of cloud-based AI solutions in the CRM space expresses a strong relationship
— if not symbiosis — between enterprises and their cloud providers. This, in turn, puts a
responsibility on the vendor to be trusted and innovative and on the enterprise to manage the
relationship at a high level.
 Further speaking to cloud solutions, IDC analysts believe that they may lead the way in
delivering AI to customers, often embedded into solutions and user interfaces, making
adoption easy as an add-on to existing applications and perhaps even free at the entry level.
0
10
20
30
40
50
60
All respondents
AI users
(% respondents)AI will create a net increase in jobs
AI will create a net decrease in jobs
The impact will be neutral
There is no way to tell
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 The choices listed and rated throughout the survey indicate that this year and the next few
following will see an incredible amount of experimentation with AI. Enterprises for which such
IT and operational experimentation is second nature will reap benefits others won't.
This need for organizations to deal with disruption and change can be seen in the question asked of
respondents on how AI would impact their organizations that had the highest rating for level of
agreement (4.7 worldwide, 4.9 AI adopters, where 6 was the highest level).
This was the statement, which can be interpreted as a word to the wise:




METHODOLOGY
To develop an estimate of the economic impact AI technologies could have on enterprises adopting
them to improve their CRM activities, IDC relied on:
 Macroeconomic information on business revenue in a country (2016 forecast to 2021), based
on third-party GDP, gross output, and employment estimates

IDC estimates of IT penetration of businesses, based on more than 15 years of analysis of and
publications on the economic impact of IT on local economies and also estimates of the basic
makeup of business expenses by major function (customer support, marketing and sales,
production, etc.) to allocate benefits across enterprises by function

IDC analysts' estimates of the percentage of revenue (and expenses) that might be affected by
CRM activities by category based on CRM's share of IT impact on enterprises
 Survey results on how much AI could improve CRM activities in the first year of AI
implementation and the timeline for adoption
 An economic impact model that pulls all the underlying data together and forecasts the results
out to 2021 (The model is based on IDC's Economic Impact of IT model, which has been
updated yearly since 2002. It includes IT spending by 54 countries, GDP and population
estimates and forecasts, revenue per employee, and ratios of IT spend to GDP.)

IDC market forecasts, including for AI and cognitive systems, CRM software, cloud computing,
Salesforce market share, and many others
 Key assumptions behind the model (refer back to Table 3) (In short, the forecast of economic
impact is based on the assumptions made by respondents of AI adoption plans and the benefit
gained during the first full year of implementation.)
IDC's AI/CRM Economic Impact Survey
Early in 2017, IDC surveyed enterprises having more than 10 employees with responses by country,
as shown in Table 5.
Implementing AI could change our organization's
culture, workforce, and operations entirely

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TABLE 5
Survey Respondents

Total
AI Adopters
Salesforce
Customers
United States
408
151
212
Canada
106
29
41
Australia
100
24
45
Japan
100
11
27
France
109
35
34
Germany
101
19
27
United Kingdom
104
23
43
Total
1,028
292
429
n = 1,028 total (292 current AI adopters)
Source: IDC's AI/CRM Economic Impact Survey, 2017

Characteristics of the respondents have been previously discussed in the document. The survey was
conducted online (supplemented by phone when necessary) of executives who were familiar with their
enterprises' CRM activities and felt competent to have an informed opinion on how AI might affect their
organizations.
Country-Level Data
Table 6 shows the results in terms financial improvement and net jobs created by the countries
surveyed. It also includes the estimate for the rest of the world used to come up with the global totals.


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TABLE 6
The Economic Impact of AI-Assisted Customer Relationship Management by
Country Surveyed — Worldwide Financial Improvement from AI in Customer
Management Activities, 2017–2021

2017
2018
2019
2020
2021
Five-Year
Sum
United States






Increased revenue ($B)
15
63
84
105
128
394
Lowered expenses ($B)
5
22
30
37
44
139
Improved productivity ($B)
2
10
14
17
20
63
Increased revenue, lowered
expenses, improved productivity ($B)
22
95
127
159
192
596
% of business revenue
0.0
0.2
0.3
0.3
0.4
0.2
Net increase in direct jobs
19,022
122,088
52,854
52,226
52,774
298,964
Net increase in indirect/induced jobs
25,641
165,820
74,073
73,193
73,961
412,689
Net increase in direct and
indirect/induced jobs
44,663
287,908
126,927
125,420
126,734
711,653
Canada






Increased revenue ($B)
1
3
4
6
7
21
Lowered expenses ($B)
0
1
2
2
2
7
Improved productivity ($B)
0
0
1
1
1
3
Increased revenue, lowered
expenses, improved productivity ($B)
2
5
7
8
10
32
% of business revenue
0.1
0.1
0.2
0.2
0.3
0.2
Net increase in direct jobs
2,213
7,860
3,787
4,079
3,720
21,660
Net increase in indirect/induced jobs
3,456
12,416
6,217
6,696
6,106
34,890
Net increase in direct and
indirect/induced jobs
5,669
20,276
0,004
10,775
9,825
56,550
Australia






Increased revenue ($B)
1
3
4
5
6
19
Lowered expenses ($B)
0
1
1
2
2
6
Improved productivity ($B)
0
1
1
1
1
4
Increased revenue, lowered
expenses, improved productivity ($B)
1
4
6
8
9
29
% of business revenue
0.0
0.1
0.2
0.2
0.3
0.2
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TABLE 6
The Economic Impact of AI-Assisted Customer Relationship Management by
Country Surveyed — Worldwide Financial Improvement from AI in Customer
Management Activities, 2017–2021

2017
2018
2019
2020
2021
Five-Year
Sum
Net increase in direct jobs
899
6,910
3,044
3,124
2,738
16,714
Net increase in indirect/induced jobs
1,835
14,300
6,624
6,798
5,959
35,518
Net increase in direct and
indirect/induced jobs
2,734
21,210
9,668
9,922
8,698
52,231
Japan






Increased revenue ($B)
2
8
12
15
18
55
Lowered expenses ($B)
1
4
5
7
8
24
Improved productivity ($B)
0
2
3
3
4
12
Increased revenue, lowered
expenses, improved productivity ($B)
3
13
20
25
30
91
% of business revenue
0.0
0.1
0.1
0.2
0.2
0.1
Net increase in direct jobs
3,696
26,881
16,586
12,297
11,902
71,364
Net increase in indirect/induced jobs
4,495
32,915
20,923
15,512
15,014
88,859
Net increase in direct and
indirect/induced jobs
8,191
59,797
37,509
27,809
26,916
160,223
France






Increased revenue ($B)
1
4
6
8
10
30
Lowered expenses ($B)
1
2
3
4
4
14
Improved productivity ($B)
0
1
1
2
2
6
Increased revenue, lowered
expenses, improved productivity ($B)
2
7
10
13
16
50
% of business revenue
0.0
0.1
0.2
0.2
0.2
0.2
Net increase in direct jobs
2,603
12,022
7,122
6,624
6,548
34,918
Net increase in indirect/induced jobs
4,404
20,534
12,164
11,313
11,183
59,599
Net increase in direct and
indirect/induced jobs
7,006
32,556
19,286
17,937
17,731
94,516
Germany






Increased revenue ($B)
1
6
8
11
13
40
Lowered expenses ($B)
0
2
3
4
5
15
©2017 IDC
#US42749217
18
TABLE 6
The Economic Impact of AI-Assisted Customer Relationship Management by
Country Surveyed — Worldwide Financial Improvement from AI in Customer
Management Activities, 2017–2021

2017
2018
2019
2020
2021
Five-Year
Sum
Improved productivity ($B)
0
1
1
2
2
7
Increased revenue, lowered
expenses, improved productivity ($B)
2
9
13
18
21
62
% of business revenue
0.0
0.1
0.1
0.2
0.2
0.1
Net increase in direct jobs
4,138
17,632
10,226
11,408
7,801
51,204
Net increase in indirect/induced jobs
6,538
28,100
16,924
18,879
12,911
83,353
Net increase in direct and
indirect/induced jobs
10,675
45,732
27,151
30,287
20,712
134,557
United Kingdom






Increased revenue ($B)
1
6
8
10
12
37
Lowered expenses ($B)
0
2
3
3
4
13
Improved productivity ($B)
0
1
1
1
2
5
Increased revenue, lowered
expenses, improved productivity ($B)
2
9
12
15
18
55
% of business revenue
0.0
0.1
0.2
0.2
0.3
0.2
Net increase in direct jobs
2,690
15,274
7,327
6,770
5,979
38,040
Net increase in indirect/induced jobs
4,792
27,474
13,753
12,708
11,223
69,950
Net increase in direct and
indirect/induced jobs
7,482
42,749
21,080
19,478
17,202
107,990
ROW






Increased revenue ($B)
4
19
28
36
43
130
Lowered expenses ($B)
1
7
10
13
16
47
Improved productivity ($B)
1
3
5
6
7
22
Increased revenue, lowered
expenses, improved productivity ($B)
6
29
43
55
66
198
% of business revenue
0.0
0.0
0.1
0.1
0.1
0.0
Net increase in direct jobs
15,026
106,412
65,066
52,176
52,189
290,869
Net increase in indirect/induced jobs
24,042
170,259
104,106
83,482
83,502
465,391
©2017 IDC
#US42749217
19
TABLE 6
The Economic Impact of AI-Assisted Customer Relationship Management by
Country Surveyed — Worldwide Financial Improvement from AI in Customer
Management Activities, 2017–2021

2017
2018
2019
2020
2021
Five-Year
Sum
Net increase in direct and
indirect/induced jobs
39,069
276,670
169,173
135,658
135,691
756,260
Worldwide






Increased revenue ($B)
26
112
154
196
237
726
Lowered expenses ($B)
9
41
58
72
85
265
Improved productivity ($B)
4
19
26
33
39
121
Worldwide: increased revenue,
lowered expenses, improved
productivity ($B)
40
172
238
301
362
1,112
% of business revenue
0.0
0.1
0.1
0.2
0.2
0.1
Worldwide net increase in direct jobs
50,287
315,079
166,013
148,704
143,651
823,734
Worldwide net increase in
indirect/induced jobs
75,203
471,819
254,784
228,582
219,859
1,250,247
Worldwide net increase in direct and
indirect/induced jobs
125,490
786,897
420,797
377,286
363,510
2,073,980
Note: Totals may not match as a result of rounding.
Source: IDC's AI/CRM Economic Impact Survey, 2017


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