AI

A glimpse into the AI marketAI adoption is increasing across various industries worldwide. Worldwide AI revenues is forecasted to surge past $47 billion in 2020…….

…… despite having a transformative benefit on consumer, enterprise, & government markets around the world, AI brings with it various challenges such as ethical issues and the impact on jobs

…….most of the AI usage is consumer based. Enterprises

haven’t yet explored AI in their crucial workload due to

factors like cost, security around deploying AI solution

…… the AI market is dominated by start-ups. The big vendors eyeing

the AI market is on acquisition spree to

avoid being overtaken by the numerous AI

start-ups

1 2

34

Spending on AI is rapidly increasing

AI adoption trends:

− North America (the United States and Canada) is by far the largest region for cognitive/AI spending with 2016 revenues approaching $6.2 billion

− IT and Data Analytics are the popular areas for deploying AI across many organizations

Our View:

With digitization as a priority for all C-level executives worldwide, AI is an inevitable technology they need to adopt. AI empowers effective and prompt decision making which is the backbone of a digital enterpriseAI adoption requires adaptation: AI spans across the 3 main pillar of an organization: people, processes and tools. A successful AI implementation require a proper synergy across the three pillars

8

47

2016 2020

Worldwide Cognitive Systems and Artificial Intelligence Revenue (in

$Bn)

CAGR 55.1%

Consumer applications are leading the way

AI usage:

Professional services like installation, training, customization, application integration, and support and maintenance are the emerging AI-enabled professional services

Today a lot of the focus and investment in AI is around consumer applications like search, product recommendations, voice-based assistants, social media feed curation, music curation, and image recognition. However in order to keep up with the dynamic technology landscape, it is inevitable for enterprises and Institutions to embrace AI in the coming years. Many organizations are taking the advantage from the emerging AI-enabled hardware and services markets. IT, Big Data and other professional services companies should exploit this opportunity to take advantage of the emerging AI-enabled markets. They should focus on building competence across the full stack of AI services ranging from providing machine learning algorithms, data capture services, implementation frameworks, hardware, and research

Our View:

40%Of AI revenue forecast to 2025 comes from Consumer, Business Services, Advertising,

Media & Entertainment and

Investment Industries

Industries(in billion $)

Consumer3.4

Business Services3.1

Advertising2.9

Investment2.4$

Media & Entertainment2.7

Industries(in billion $)

Source: Accenture: Why artificial intelligence is the future of growth, April 2016

Computer Vision Audio Processing Natural Language Processing

Knowledge Representation Machine Learning Expert Systems

AI

Tech

nolo

gies

Illus

trat

ive

Solu

tions …

Virtual Agents

IdentityAnalytics

CognitiveRobotics

SpeechAnalytics

RecommendationSystems

Data Visualization

Emerging AI technologies

Computer vision and audio processing, for example are able to actively perceive the world

around them by acquiring and processing images, sounds and speech. The use of facial recognition

at border control kiosks is one practical example of how it can improve productivity.

Sense

Natural language processing and inference engines can enable AI systems to analyse and

understand the information collected. This technology is used to power the language translation feature of search engine results

Comprehend

An AI system can take action through technologies such as expert systems and inference engines or

undertake actions in the physical world. Auto-pilot features and assisted-braking capabilities in cars

are examples of this

Act

What is AI? – To sense, comprehend and act

• At its core, AI is about solving business problems in novel ways. It stretches across any organization from innovation, R&D and IT to data science.

• AI goes by many other names. Some vendors use variations on the term "cognitive computing.“ (Source: Gartner: Artificial Intelligence Primer for 2017)

• IDC defines cognitive/Artificial Intelligence (AI) systems as a set of technologies that use deep natural language processing and understanding to answer questions and provide recommendations and direction.

• IDC’s coverage of cognitive/AI systems examines:• Digital assistants• Automated advisors• Artificial intelligence, deep learning and machine learning• Automated recommendation systems

(Source: IDC Cognitive/AI Systems Scale Personalized Experiences)

• Forrester defines AI as a liberatory technology at its core, and businesses that integrate it will free workers to become more innovative, creative, and adaptive than ever before. But this technology is still in early stages. (Source: Forrester: TechRadar Artificial Intelligence Technologies, Q1 2017)

• Artificial intelligence (AI) is quickly emerging as a transformative technology that enables organizations to gain business advantage. Also referred to as Cognitive computing , AI augments human expertise to unlock new intelligence from vast quantities of data and to develop deep, predictive insights at scale. (Source: IBM: The cognitive advantage: Insights from early adopters on driving business value)

Artificial Intelligence Overview

©2017 Gartner, Inc.

How do others define AI?

• APAC, North America and Western Europe are projected to be generating maximum revenue from AI• On a geographic basis, North America (the United States and Canada) is by far the largest region for cognitive/AI spending with 2016 revenues

approaching $6.2 billion. • Europe, the Middle East and Africa (EMEA) will remain the second largest region throughout the forecast, • But cognitive/AI revenues from Asia/Pacific including Japan will nearly close the gap with EMEA by 2020.

Source: IDC worldwide semiannual cognitive artificial intelligence spending guide, Oct 2016, Tractica

AI Revenue by regions, World Market: 2015-2024 Cognitive Artificial Intelligence systems spending guide (CAGR)

Top region based on 5 Year CAGR -2020

Japan APAC(ex.Japan)

Latin America USA Western

Europe

114.9%63.9% 56.2% 54.5% 50.1%

North America & APAC are expected to lead AI adoption

Source: IBM: The cognitive advantage: Insights from early adopters on driving business value

AI adoption pattern across organizations differ based on the stages or degrees of AI adoption

IT

Data Analytics

Customer service

Operations

Corporate Strategy & Management

Finance

Human Resource

Product Development

Communications/PR

Sales

Marketing

Beginner PatternThe top 5 functional areas for AI initiative

among organizations who are in their nascent stage of AI adoption are: IT, Data Analytics, Finance, Customer service and

operations.

23%

23%

19%

16%

18%

25%

20%

24%

24%

37%

39%

47%

47%

46%

56%

47%

42%

52%

53%

48%

46%

47%

Already Using Planning on Using

Organizations planning to adopt AI has an unique pattern of AI adoption. They deploy AI mainly for IT, Data analytics, Operations, Marketing, Customer Service and Corporate

Strategy & Management

Planner Patterns

58%

48%

38%

47%

31%

34%

53%

60%

53%

69%

70%

Planning on Using

Advanced users patternsMajority of organizations who are strong adopters of AI, deploy it for Information Technology (IT) initiative. Data Analytics,

Customer service, Operation and Corporate strategy management are the top 5 functional areas IT for AI initiative

deployment.

40%

41%

42%

44%

47%

48%

48%

50%

51%

59%

66%

48%

45%

41%

44%

35%

42%

43%

41%

38%

36%

23%

Already Using Planning on Using

Pattern of AI adoption: IT and Data Analytics are the popular areas for deploying AI across many organizations

Pervasive data

Cloud compute

AI advancements

estimated additional revenue/shifting revenue driven by AI in three years$40B

By 2022, one in five workers engaged in mostly nonroutine tasks will rely on AI to do a job. (*)20%

By 2021, AI augmentation will generate $2.9 trillion in business value and recover 6.2 billion hours of worker productivity. (*)

$2.9T

* Gartner, December 13th, 2017

Why now?

Classified as Microsoft Confidential

Why AI – Why NowDigital Transformation within customers is now required to maintain their competitive edge. AI that combines Big Data, robust Cloud Networking and Advanced Algorithms is now driving this Digital Transformation.

AI empowers employees and customers to optimize their interactions, how they communicate and helps transform products.

“The AI revolution is set to take the service industry by storm, with the potential to change the role of the white-collar worker irreversibly” - Imam Hoque, Chief operating officer and head of product, Quantexa

Transform process and products through us of AI capabilities

Infrastructure speed, availability, and sheer scale has now enabled bolder algorithms to tackle problems.

Open source technologies, such as Spark and Hadoop, allow speedier development of scaled AI technologies

Customer expectation and acceptance now drive more AI enabled applications

Culture and Governance Process & Tools People and Skills Data MaturityPlatform

AI Infused Experiences• Personalized & Intelligent• Conversational & Natural

AI Infused Processes• Core Business• Operational Efficiencies

AI Infused Products & Services• Innovative & Cross-Channel• Customized & Transformative

Y o u r s t r a t e g i c p r i o r i t i e s

AI Capabilities

Best Customer & ecosystem Value

IndustryLeadership

Best Place to work

What does an AI company do?

Source: IBM: The cognitive advantage: Insights from early adopters on driving business value

Challenges for AI adoption

Cost of technologies/solution development

Security concerns Less advanced or immature

technologies and tools for implementing

cognitive solutions

Insufficient skills Data issues (i.e. quality of data integrating &

converting data. Volume of data)

62% 57% 55% 54% 54%

But there are challenges that prevent many companies from adopting AI

Build AI Maturity Capabilities

Prescriptive and automated decision support

Data and Knowlege Foundation

Hardware/Platform & ArchitectureModern and Standardized

Skills & CompetenciesRelevant and deep

CapabilitiesStrategic, Cross-company, shared

Organization & CultureLearning, Sharing, Agile,

Data Driven

Process and MethodsContinuous Value

AI TransformationCustomer centric, business aligned

Building an AI Strategy

Essential Ingredients – 4 key enablers of AI

16