Our analysis of seven industries’ perspectives on AI in the enterprise unpacks how business leaders are using the technologies to solve major industry problems. These include addressing the challenges brought on by COVID-19, fast-tracking vaccine development and distribution, detecting fraud, improving bureaucratic efficiency, and more. We hope you find the study findings – and our analysis – insightful and useful as you evolve your AI strategy."
Sreekar Krishna, Ph.D.
Ellen Campana, Ph.D.
Swami Chandrasekaran
survey
2021 Thriving in an AI World
By targeting key decision makers in each industry, the survey uncovered pain points, perceived risks, challenges, and opportunities of AI integration for large companies in the U.S. Our respondent criteria included these parameters:
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950 business decision makers
$1B+ in revenue
At least a moderate knowledge of AI
At least 51 full-time employees
The challenges of COVID-19 drove businesses to embrace AI, but to what effect? Nearly half of the executives we surveyed experienced what we call "COVID-induced whiplash"; they felt their industry embraced AI too quickly, despite 85% wishing their own organization would pick up the pace.
Companies know it’s vital to integrate AI and implement innovative methods to connect with customers, but they’re worried that their competitors will leave them behind by doing it faster.
Moving too fast?
INTEGRATION
31%
31%
31%
6%
12%
30%
28%
26%
4%
26%
26%
43%
4%
7 industries
7 industries, including:
27%
34%
26%
12%
17%
12%
38%
24%
9%
13%
27%
40%
16%
4%
Tech
Government
Retail
Financial
Services
Technology, financial services, industrial manufacturing, healthcare, life sciences, retail, and government.
Healthcare & Life Sciences
Industrial Manufacturing
Significantly More Value
Expected Level of Value
Significantly Less Value
Somewhat More Value
Somewhat Less Value
COVID-induced AI whiplash;
The promise is real
VALUE
Executives widely believe in AI’s ability to deliver value. 92% of respondents agree AI would make their organization run more efficiently, and individual industries report confidence in AI’s potential to solve some of their biggest challenges. Indeed, at organizations where AI has been adopted, the majority of executives say it is adding even more value than was promised.
The retail industry is a leader on this front, with 69% of retail executives saying their organization’s AI initiatives are yielding more value. But even among the industries that are not as far ahead in this area—life sciences and government—at least half report similarly favorable results (50% and 54%, respectively). Read on for more insights on how to realize AI’s promise.
The perceived value of AI across industries:
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Retail
Tech
Financial Services
Industrial Manufacturing
Healthcare
Life Sciences
Government
Percent of respondents that say AI adoption is moving faster than it should.
49%
37%
55%
37%
35%
47%
49%
+16%
ppt*
+20%
ppt*
+26%
ppt*
Percent of respondents that say AI adoption is moving at an appropriate speed.
46%
44%
53%
43%
55%
47%
47%
Security, privacy, and ethics are the top AI concerns across all industries, with cybersecurity breaches leading as most worrisome. Other findings include:
Roadblocks. Risks. Realities.
risk
Business and government decision-makers believe an AI ethics policy is necessary,
yet many organizations don’t have one
in place
69% of respondents say it is hard to keep up with the evolving AI landscape
Business leaders (especially from small companies) struggle to select the best AI technologies
Respondents in each industry were asked to select the top two potential risks for AI:
42%
63%
Cybersecurity breaches
Privacy violations
Government
Perceived pace of AI adoption across industries:
Business leaders believe machine learning will have the greatest impact on their respective industries.
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Reflections for the future
IMPACT
Reduce fraud, waste, and abuse
We see AI playing a vital role across industries. Some examples:
Sharpen sales, marketing, and customer service operations
Improve disease identification and treatment methods
Accurately predict weather patterns and analyze soil for best crop usage
Help develop better, more resilient sources of sustainable energy
16%
20%
21%
22%
22%
22%
23%
24%
35%
35%
41%
Machine learning
Robotic process automation
Artificial/virtual reality
Deep learning
Anomaly detection/
pattern recognition
Biometrics
Chat bots and intellgent agents
Digital twin/simulation
Image recognition
Natural language processing
Constraint-based optimization
The road to value in 2021 and beyond
journey
Our deep experience helping clients develop and implement their own AI strategies shows that the following steps should be considered to achieve the most value from your AI investments.
Percent of respondents that say AI is moving slower than it should.
16%
7%
12%
2%
8%
4%
7%
61%
52%
Cybersecurity breaches
Privacy violations
Tech
58%
43%
Cybersecurity breaches
Surveillance issues
Industrial Manufacturing
41% healthcare*
31% retail*
29% government*
33% tech*
45%
tech*
52% Industrial Manufacturing*
53% Tech*
51% Industrial Manufacturing*
Healthcare
Government
Life Sciences
Financial Services
Retail
Tech
Industrial Manufacturing
Government has a role to play in regulating AI, with more retail, financial services, and technology respondents interested in government involvement now than in 2019.
84%
82%
86%
86%
87%
86%
94%
97%
Life Sciences
Government
Industrial Manufacturing
Financial Services
Healthcare
Tech
Retail
Business leaders and government decision-makers agree companies should implement an AI ethics policy, yet not all organizations currently have one.
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78%
95%
71%
93%
67%
92%
65%
92%
89%
92%
53%
86%
59%
+22 ppt*
+1 ppt*
+17 ppt*
+7 ppt*
+34 ppt*
+7 ppt*
Believe companies should implement an AI ethics policy to help govern AI work
Currently has a code of AI ethics in place
54%
50%
Privacy violations
Potential bias in AI technology
Healthcare
51%
44%
Cybersecurity breaches
Potential bias in AI technology
Life Sciences
50%
44%
Cybersecurity breaches
Privacy violations
Financial Services
47%
45%
Cybersecurity breaches
Potential bias in AI technology
Retail
Click each circle for more detail
1.
Invest in comprehensive data and robust data infrastructure for ultimate effectiveness.
2.
Hire AI and data science talent, either internally or through partnerships outside of the organization.
3.
Create a workplace culture invested in AI's success. Start by educating and upskilling employees.
4.
Devise AI strategy driven by business needs, ensuring use across the full organization.
5.
Develop an AI ethics policy with clear guidelines on how AI will be deployed. Commit to ethical and unbiased use of AI.
6.
Help shape the budding regulatory framework for AI, such that government actions promote the use of AI and do not hinder progress.
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Listen to our audio commentary
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Listen to our audio commentary
Download paper
Listen to our audio commentary
Download paper
Listen to our audio commentary
National Leader of Artificial Intelligence and Head of Data Engineering, KPMG
Head of Enterprise
Artificial Intelligence
Head of Digital Solutions Architecture, KPMG
Thriving in an AI World
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Journey
Impact
Risk
Integration
Value
Intro
Journey
Impact
Risk
Integration
Value
Intro
Journey
Impact
Risk
Integration
Value
Intro
Journey
Impact
Risk
Integration
Value
Intro
Journey
Impact
Risk
Integration
Value
Intro
Government
Life Sciences
Retail
Healthcare
Industrial Manufacturing
Financial Services
Tech
Government
Life Sciences
Retail
Healthcare
Industrial Manufacturing
Financial Services
Tech
KPMG
survey.
KPMG Thriving in an AI World
Our insights are derived from the
Our insights are derived from the
Each organization represented was required to have annual revenue of at least $1 billion, except in healthcare and life sciences, where the threshold was $100 million.
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Each organization represented was required to have annual revenue of at least $1 billion, except in healthcare and life sciences, where the threshold was $100 million.
(Click for more detail)
53%
Tech*
*Results comparable to "KPMG 2020 Living in an AI World," January 2020
*Results comparable to "KPMG 2020 Living in an AI World," January 2020
Government
Life Sciences
Retail
Healthcare
Industrial Manufacturing
Financial Services
Tech
Government
Life Sciences
Retail
Healthcare
Industrial Manufacturing
Financial Services
Tech
*Results comparable to "KPMG 2020 Living in an AI World," January 2020
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*Results comparable to "KPMG 2020 Living in an AI World", January 2020
Click for more detail
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Thriving in an AI World
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+17 ppt*
+24 ppt*
+27 ppt*
*Results comparable to "KPMG 2020 Living in an AI World," January 2020
+17 ppt*
*Results comparable to "KPMG 2020 Living in an AI World," January 2020
Click for more detail
+24 ppt*
+27 ppt*
Take a deeper dive into the impacts of AI on each industry by viewing the full findings below.
Technology
Retail
Financial Services
Life Sciences
Government
Industrial Manufacturing
Healthcare
Journey
Impact
Risk
Integration
Value
Intro
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Intro
Thriving in an AI World
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Thriving in an AI World
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Thriving in an AI World
Hear from Sreekar Krishna on this topic
Hear from Sreekar Krishna on this topic
Hear from Swami Chandrasekaran on this topic
Hear from Swami Chandrasekaran on this topic
Hear from Ellen Campana on this topic
Healthcare
Government
Industrial Manufacturing
Life Sciences
Financial Services
Retail
Technology
Take a deeper dive into the impacts of AI on each industry by viewing the full findings below.
View PDF
Thriving in an AI World
Government
Industrial Manufacturing
Healthcare
Life Sciences
Financial Services
Retail
Technology
Take a deeper dive into the impacts of AI on each industry by viewing the full findings below.
Hear from Sreekar Krishna on this topic
View PDF
Thriving in an AI World
Hear from Sreekar Krishna on this topic
View PDF
Thriving in an AI World
Hear from Swami Chandrasekaran on this topic
View PDF
Thriving in an AI World
Hear from Swami Chandrasekaran on this topic
View PDF
Thriving in an AI World
Hear from Ellen Campana on this topic