james manyika at ai frontiers: sizing up the promise of ai

November 2017

Artificial Intelligence The next digital frontier?

JAMES MANYIKA

CONFIDENTIAL AND PROPRIETARYAny use of this material without specific permission of McKinsey & Company is strictly prohibited

Rated #1 Think Tank 2016 (private sector category) by the Global Think Tank Index, University of Pennsylvania

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Machines can now match and even exceed human performanceImage recognition accuracy rate

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Present2010

70%

80%

90%

100%

Human performanceMachine performance

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Who is investing and where?1

Who is adopting AI today and how?2

Where can AI improve business performance?3

What do we need to do tomorrow morning?4

Four key questions for AI today

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Investments in AI include several types of technologies

Computer vision

Natural language

Machine learning

Virtual assistants

Robotics and autonomous vehicles

28%

56%

7% 6%4%

EXTERNAL INVESTMENTS

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There is increasing interest from VC and PE funds

Electric vehicles

+285%

Biotech

IT

Total VC

Energy

AI

AI investments in 2016 VC investment growth, 2013–16

External investments (VC, PE )

$6–9B

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Tech giants are the primary investors

AI investments in 2016

External investments (VC, PE )

$6–9B

$20–30B

Corporate investments (tech giants) 42

19

1413997

2010 20122011 20162013 2014 2015

Number of AI acquisitions

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China and the United States dominate the investment scene, while Europe is lagging

North America$15–23B Europe

$3–4B Asia$8–12B

AI investment in 2016

External investments (VC, PE, M&A)

Internal corporate investments

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Higher potential

Media

Consumer

Energy

Agriculture Manufacturing

Public/socialHealth careAutomotive

Finance TelecomPharmaceuticals

0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9

Impact score

Travel, transport, and logistics

Volume

Identifyfraudulent

transactions

Personalizefinancialproducts Identify

and navigate roads

Personalizeadvertising

Optimize pricingand schedulingin real time

Predict personalizedhealth outcomes

Optimize merchandising strategy

Discover newconsumer trends

Personalize crops to individual conditions

Predictive maintenance(manufacturing)

Diagnose diseases

Optimize clinical trials

Predictive maintenance(manufacturing)

Lower priority

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Yet adoption at scale is limited, even among AI-aware firms

20%early adopters

%

40

Contemplators

40

Experimenters

2 technologies

1 technology

3+ technologies

73

10

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What about the non-adopters?

28%don’t have the technical capabilities to implement AI effectively

Technical capability

Return on investment

41%of AI-aware firms are uncertain about AI’s ROI

30%of AI-aware firms can’t see a business case for AI

Business case



Sectors leading in AI adoption today look set to pull away further from slower adoptersFuture AI demand% ∆ AI spending 2017–20

Current AI adoption% of firms who are early adopters

Sloweradopters

Frontier sectors

5

0

10

15

25 3010 2015

Automotive

Tech andtelco

Finance

Construction

CPG

Transport

Retail

Media

Health care

Energy

Education

Professional services

Travel



Digitally mature industries lead in AI adoption

AI Index

Digitization Transformation Index80

40

20

100

0 60

60

40

80

Travel

Construction

Finance

Retail

Tech and telco

Transport

Health care

Media

Professional services

Energy

Education



The early adopters of AI have five distinctive characteristics


Digitally mature1

Larger businesses2

Adopt AI in core activities3

Focus on growth over savings4

C-suite level support for AI5


AI can more than double the impact of other analytics across industries

Publicandsocialsector

100%

Travel, transport,andlogistics

Telecom, media,andtechnology

Pharmaandmedical products

Healthcare systemsandservices

Globalenergyandmaterials

Advanced manufac-turing industries

Consumer FIG

Additional AI impact Analytics impact

~60%

~40%

PRELIMINARY

SOURCE: McKinsey analysis


AI use cases have the potential to materially impact corporate performance PRELIMINARY


Potential impact as % of revenue

Advanc-ed elec-tronics aero

PMPTele-com

InsLogis-tics

Media Auto Basicmate-rials

Oil and gas

PSSHSS Trans-port

TravelCPGHigh tech

Chem andagri-culture

Retail Banking

Average~10%


AI use cases have the potential to materially impact corporate performance


PMPTele-com

InsLogis-tics


Oil and gas

PSSHSS Trans-port

TravelCPGHigh tech


Retail Banking

Average~10%


PRELIMINARY

High data availability, particularly labelled and structured data





PMPTele-com

InsLogis-tics


Oil and gas

PSSHSS Trans-port

TravelCPGHigh tech


Retail Banking

Average~10%


PRELIMINARY

Operationally oriented manufacturerscan realize significant improvements in supply chain and production





PMPTele-com

InsLogis-tics


Oil and gas

PSSHSS Trans-port

TravelCPGHigh tech


Retail Banking

Average~10%


PRELIMINARY

Pharma and med products companies can unlock additional R&D productivity





PMPTele-com

InsLogis-tics


Oil and gas

PSSHSS Trans-port

TravelCPGHigh tech


Retail Banking

Average~10%


PRELIMINARY

Industries with significant physical plant and equipment assetscan optimize their capital expenditures



Potential AI impact by function varies by industry

Travel, transport,andlogistics

Telecom,media, andtechnology

Public and socialsector

Healthcaresystemsandservices

FIGConsumerGlobalenergy, andmaterials

Advanced industries

100%

Pharmaceu-ticals andmedicalproducts

OrganizationOtherOther operations

RiskStrategy and corporate financeService operationsManufacturing

Marketing and salesSupply chain managementProduct development

PRELIMINARY



Techniques and tools

Open organization

Workflow integration

Data ecosystem

Use cases/sources of

value


There are five pragmatic steps businesses can take to start adopting AI tomorrow


Governments need to act now to promote AI development


RegulationSkillsSupport and

incentives

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james manyika at ai frontiers: sizing up the promise of ai

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