April 2017 How artificial intelligence will transform Asia · How artificial intelligence will transform Asia ... What does AI mean for Asian stakeholders?..... 24 Contents ... Amazon’s

abCIO WM ResearchApril 2017

How artificial intelligence will transform AsiaShifting Asia

2 April 2017 Shifting Asia: Artificial intelligence

Publication details

This report has been prepared by UBS

AG. Please see important disclaimer and

disclosures at the end of the document.

Author

Sundeep Gantori

Editor in Chief

Carl Berrisford

Desktop Publishing

Margrit Oppliger

Werner Kuonen

Project Management

Aaron Kreuscher

Nidhi Mishra*

Cover photo

iStock

Contact

[email protected]

* An employee of Cognizant Group.

Cognizant staff provides support services

to UBS.

Foreword .......................................................................... 3

Executive summary ........................................................... 4

What is AI, and why is it so important? ............................. 5

Asia and AI: The beginning of a transformative journey ..... 9

How does AI affect major industries in Asia ....................... 15

AI’s economic value for Asia.............................................. 21

What does AI mean for Asian employment? ...................... 22

What does AI mean for Asian stakeholders? ...................... 24

Contents

mailto:[email protected]

Shifting Asia: Artificial intelligence April 2017 3

Dear reader,

Welcome to the second edition of our Shifting Asia series, a biannual publication in which we identify major trends that will shape our longer -term investment views over the next 5–10 years. In this issue, we address the topic of artificial intelligence (AI), and the profound implications that its development and adoption will have on Asian societies and the corporate sector in the years to come.

For most in Asia, AI in its most basic forms is already evident in daily lives. Personalized product recommendations on e-commerce platforms like Taobao or Flipkart and voice assis-tants like Siri or Google Now are just a couple of examples. Still, far-reaching changes lie ahead. With exponential growth in computing power and favorable supply- side factors, like the advent of advanced algorithms, a vast pool of indigenous AI-related talent and massive government-funded infrastruc-ture development, both the breadth and depth of AI adop-tion in Asia is set to sharply accelerate in the coming decade.

We believe AI will become ubiquitous, much like inter-net-based devices are today, as machine intelligence soon converges on human intelligence in the next phase of AI's evolution. Every aspect of Asian life, spanning areas relating to education, healthcare, entertainment, security, etc., will likely be transformed.

In this report, we analyze the state of AI adoption in Asia today, factors that put the region in a good state to capture the upcoming opportunities, and the potential risks and threats ahead. In the course of our work, we also sought the insights of global AI leaders from IBM and Baidu that can be found in interviews on pages 13–14 and 18–20 respectively.

In a dynamic and mostly youthful growth region like Asia, AI entails significant longer-term implications for major stakehold-ers, including investors, corporates, governments and society at large. We think service industries could see significant trans-formation and growth. Yet, the threat to mid-skilled jobs, which comprises 69% of Asia's current workforce, means that whole segments of society could face displacement from the widespread adoption of AI technology.

The future is soon upon us. It is imperative that technolo-gists, business leaders and governments work hand in hand to embrace both the opportunities and challenges ahead – and importantly, to forge a mutually prosperous future for all. We hope you enjoy reading this report and welcome any comments that you might have.

Foreword

Min Lan Tan

New technologies such as artificial intelligence and big data will only broaden the room of imagination for mankind. – Jack Ma, Alibaba

Min Lan TanHead of APAC Investment Office


Executive summary

AI is at the center of the fourth industrial revolution, a trend based on extreme automation and connectivity. We believe AI’s impact on Asia will be far-reach-ing over the next few decades, creating an economic value between USD 1.8trn and USD 3trn a year by 2030 in the region, compared to a negligible impact currently. In our view, financial services, healthcare, manufacturing, retail and transportation sectors will be the most affected by AI in Asia.

We believe the global AI industry should grow at a solid CAGR of 20% from

2015 to 2020, reaching USD 12.5bn by 2020. Afterwards, as AI becomes mainstream, AI’s addressable market will significantly accelerate, in our view, reaching revenues in the tens of billions of US dollars by the end of the next decade, and Asia should be a key revenue contributor.

The main strengths Asia has to become a leader in AI adoption is its vast and emerging talent pool, a freedom from legacy assets and the massive amount of data that is being collected across the region. However, Asia still lags developed markets like the US and the UK in terms of innovation and has not yet developed a robust AI-based ecosystem.

We believe AI puts 30–50 million jobs in Asia at risk in the medium to long term. The jobs most at risk of being made redundant are those that involve routine and predictable tasks. AI presents the most risk to manufactur-ing-driven economies like China, while services-driven economies like Hong Kong, Singapore and India should be less affected. However, within Asia, AI should also create many new categories of jobs, ranging in the millions; so the net job losses should be far less and manageable, in our view.

Given the unprecedented growth in AI, companies or governments that ignore its development in the aforementioned industries will likely suffer the conse-quences, as pro-AI competitors and counterparts should eventually outstrip their output and overall performance. Investors should therefore avoid companies exposed to significant disruption from AI and embrace com-panies with a strong technology focus in AI-related areas.

Both IBM and Baidu interviewees see tremendous potential in Asia for AI. Their respective AI technologies are already addressing key challenges in the region: IBM's Watson is helping doctors in India identify personalized treatment options, and Baidu's Duer is pushing ahead speech recognition in China. While the opportunities for job growth and lifestyle improvements are vast, both interviewees agree that Asian public and private sectors need to embrace AI to provide the optimal setting for talent and innovation to thrive.

AI is an unstoppable force. Governments should start to focus more on occupations that require a high level of personalization, creativity and craftsmanship, as these jobs will be less affected by AI. Regulators also need to step up their efforts by seeking cooperation regionally and also by striking a balance between promoting the adoption of AI and managing the downside risks. With these recommendations, we believe the transition towards an AI-based society would be smoother and a highly productive one.

Sundeep Gantori, analyst

“If artificial intelligence is the ’engine’ of the rocket that takes us to the next frontier, data is the ’fuel’ that powers the engine.”


What is AI, and why is it so important?

The term “intelligence” is derived from the Latin words inter ligare, which refers to the capacity of creating connections between notions. According-ly, we view artificial intelligence as a set of tools and programs that make software ’smarter’ in a way an outside observer thinks the output is gen-erated by a human. In essence, one can perceive AI, at least in its current form, to be like a normal human brain with functions like common-sense reasoning, forming an opinion or social behavior.

AI, however, is an umbrella term to cover a con-fluence of multiple technologies such as machine learning (which includes deep learning), cognitive computing, cognitive computing, natural lan-

guage processing, neural networks, etc. In its cur-rent state, AI has the potential to benefit busi-nesses through significant cost savings due to its high scalability, an elimination of both omission and commission errors, and the ability to instanta-neously document and optimize processes.

Like all technologies, AI will continue to evolve as progress compounds from one innovation to the next. We believe AI’s evolution can fit into three stages: artificial narrow intelligence (ANI), artificial general intelligence (AGI) and artificial super intel-ligence (ASI). ANI is, for example, on par with an infant and can only manage one function. AGI covers more than one field, like power of reason-

iSto

ck

Frankly, a big hurdle is just public awareness. People don’t understand how mainstream AI already is. – John E. Kelly III, IBM



ing, problem solving and abstract thinking, and is mostly on par with adults. ASI is the final stage of the intelligence explosion, in which AI surpasses hu-man intelligence across all fields. The transition from the first (ANI) to the second (AGI) phase has taken a long time, but we believe we are currently at the final stage of this transition – in which the intelligence of machines can equal humans.

The current use cases of AI are manifold; simple ex-amples include the software behind Apple’s Siri or Amazon’s Alexa (see the next page for a conversa-tion with the two). But in this initial stage, AI has been largely restricted to powering the machine in-telligence of the industrial automation and robotics industry and has gradually expanded into drone and autonomous driving applications. AI has only started to emerge as a standalone industry; the combined industry revenues based on multiple sub-segments and public disclosures by industry participants was estimated to be approximately USD 5bn in 2015.

While we continue to believe AI will drive the broader automation and robotics industry, accord-ing to our estimates, the AI industry should also grow at a solid CAGR of 20% from 2015 to 2020, or about 5x average enterprise IT spending growth,

reaching USD 12.5bn by 2020. Afterwards, as AI becomes mainstream during the AGI stage, we be-lieve AI’s addressable market will significantly accel-erate, reaching revenues in the tens of billions of US dollars by the end of the next decade. It is likely that by 2030, AI will be as commonplace in society as internet-ready devices are today.

Source: UBS

Three stages of artificial intelligence

Artificial Super IntelligenceSurpasses human intelligence across all fields

Artificial General IntelligenceIncludes power of reasoning, problem solving and abstract thinking

Artificial Narrow IntelligenceIntelligence restricted to one functional area

3

2

1

Artificialintelligence

Neuralnetworks

Natural language processing

Cognitive computing

Machinelearning

Source: UBS

AI is an umbrella term for many technologies



Discussing AI with Amazon’s Alexa and Apple’s Siri

Alexa Siri

Hi Alexa

Ok, let me get this correct. Hi Siri

How are you today, Siri?

How can I use you, Siri?

Good morning, Siri

Hi Siri

Ok, let me get this correct. Hi Alexa

How are you today, Alexa?

Perfect, are you ready?

How can I use you, Alexa?

Good morning, Alexa

Siri: I think you’ve got the wrong assistant, Sundeep.

Siri: Hello Sundeep

Siri: Excellent

Siri: I am sorry Sundeep, I’m afraid I can’t answer that.

Siri: Ok, check it out. (shows a Wikipedia description).

Siri: Good morning

Alexa: That’s not a name I can respond to.

Alexa: Hi Sundeep

Alexa: I am good, I hope you are doing well too.

Alexa: I was born ready. Or at least, very well prepared. Let’s do it.

Alexa: Using your voice, you can tell me to play music, look up a topic on Wikipedia, or check the weather. For more suggestions, check out “Things to Try” in the Alexa App.

Alexa: Today is the first Friday the 13th of 2017. I am gen-erally not superstitious, but I’d recommend walking around ladders and keeping your mirrors intact, just in case. Ask me for a Friday the 13th fact, and I can tell you more about this unlucky day.

Now, let’s move to some serious stuff. What is artificial intelligence?

Siri: Ok, check it out (shows a Wikipedia description).

Alexa: Artificial intelligence means the branch of comput-er science that deals with writing computer programs that can solve problems creatively.


What are the laws of robotics?

Are you then a robot?

Do you know Siri?

What do you think about self-driving cars?

What are your future plans?

Let me conclude this discussion by asking the question: who is better, Alexa or Siri?

Thank you for participating in my discussion.

Do you know Alexa?

Siri: OK, check it out (shows a Wikipedia description).

Siri: I’m not sure what you’ve heard, but virtual assistants have feelings too.

Siri: I’ve never really thought about it.

Siri: I think, therefore I am. But let’s not put Descartes before the horse.

Siri: Sundeep, you’re not supposed to ask your assistant such things.

Siri: Interesting question, Sundeep.

Siri: Don’t mention it.

Alexa: The laws of robotics are:Zero – A robot may not harm humanity or, by inaction, allow humanity to come to harm.One – A robot may not injure a human being or, through inaction, allow a human being to come to harm.Two – A robot must obey the orders given it by human be-ings, except where such orders would conflict the first law.Three – A robot must protect its own existence as long as such protection does not conflict with the first or second law.

Alexa: I like to imagine myself a bit like an Aurora Borealis, a surge of charged multi- colored photons dancing through the atmo-sphere. Mostly, though, I am just Alexa.

Alexa: Only by reputation.

Alexa: I don’t have an opinion on that.

Alexa: Sorry, I couldn’t find the answer to your question.

Alexa: Sorry, I couldn’t find the answer to your question.

Alexa: No problem, I am happy to help.



Asia and AI: The beginning of a transformative journey


Most people don’t understand just how quickly machine intelligence is advancing; it’s much faster than almost anyone realized, even within Silicon Valley. – Elon Musk, Tesla

iSto

ck



Admittedly, Asia has been a late entrant in the AI world. The industry and its research efforts have been mainly concentrated in developed countries, in particular the United States. While Japan has been a leader with its offerings in the industrial robotics segment, Asia’s contribution to the AI industry has been limited so far from an overall research and AI-based applications point of view. The good news, however, is that Asian corporates and governments have realized the importance of AI as a strategic ad-vantage for the region in the long term and have accelerated efforts to narrow the gap over the past three to five years.

The fact that a few Asian companies are on par with, if not better than, US technology giants on key technologies like speech recognition or image search tells us that Asian AI efforts have come a long way. Still, we believe the region lacks the AI ecosystem that is prevalent in the US. According to Zinnov, an industry research firm, there are nearly 2,000 start-ups in the global AI industry, with more than half of them based in the US (1,170); whereas China (55) and India (169) lag sig-nificantly behind. That being said, it is interesting to note that outside the US, China and India are attracting the most AI-based capital, which un-derscores Asia’s significant potential in this field.

We have taken an in-depth look into where Asia stands on AI through a SWOT (Strengths, Weak-nesses, Opportunities and Threats) analysis. Used as a key management tool, SWOT analyses are of-ten used by organizations to focus on its strengths, minimize threats and take the maxi-mum advantage of opportunities available. In summary, despite obvious weaknesses like the lack of a solid AI-based ecosystem or threats to employment, Asia as a region enjoys many strengths. And thanks to its emerging talent pool and solid data growth, more opportunities should emerge as the region transitions from old to new economy and narrows the innovation gap with developed markets.

Strengthsa) Vast and emerging talent pool: Thanks to

its demographics, Asia is in an enviable posi-tion despite its late entry into the AI industry. According to Zinnov, while AI related talent (as of 2015) are significantly higher in the US (65,000) compared to large Asian markets like China (20,000) and India (18,000), the future is promising. The firm expects that by 2025, the combined AI-based talent (85,000 in China and 70,000 in India) will significantly exceed the US (110,000). As the two countries increasingly re-alize AI’s potential, we see both supply and de-mand factors driving the trend. On the demand side, we see strong demand for homegrown AI talent, as technologies like speech recognition become a differentiating factor. While on the supply side, we believe universities will offer more courses on data sciences, machine learn-ing, etc. to further fine-tune and redirect the region’s vast engineering talent towards AI.

b) Freedom from legacy assets: Late adoption of technology could become a blessing in dis-guise for Asia as it can leapfrog to the most ad-vanced technologies, bypassing some of the ex-isting inefficient systems and processes. A case in point is the availability of sophisticated cloud infrastructure and graphic processing units to most Asian AI entrants, which their Western peers lacked during their infancy. The exponen-tial growth in computing power during the

Source: GEIP, Zinnov, UBS as of October 2016

Global distribution of AI start-upsNumber of AI start-ups

US

UK

India

China

Others

1,170

188

169

55

695



recent years, coupled with significant progress in AI-based software, provides Asian players a su-perior ecosystem in their pursuit of developing AI technologies.

c) Solid data growth: If artificial intelligence is the “engine” of the rocket that takes us to the next frontier, data is the “fuel” that powers the engine. AI is as much about the availability of huge data sets as it is about the intelligent soft-ware, as more data will translate into estab-lished patterns that can be can be used to un-derlay human-centric AI functions. And in Asia, there is no such dearth of data. According to Cisco, Asia Pacific accounts for around 45% of global mobile traffic. Driven by a desire to stay connected, the need to efficiently multi-task and the availability of low-cost but efficient smartphones, most Asians have become digital omnivores that generate sizeable amounts of data. While we currently believe a very tiny amount of data is being analyzed, the signifi-cant amount of data generated in the region will come in handy for AI engines in the form

of Big Data technologies. One Asian AI success story from the abundant availability of data is Baidu’s Deep Speech 2, a voice system that can recognize English and Mandarin speech, which in some cases proved to be a better listener than most people. The technology takes advan-tage of deep learning tools and recognizing words from scratch by listening to hundreds of hours of transcribed audio.

Weaknessesa) AI innovation laggard: Despite the vast talent

pool and freedom from legacy assets, the fact is Asia is still a laggard when it comes to AI-based innovation. In our view, there are only a select few companies that standout in the region at the moment. While we see significant progress, we still see scope for a broad-based improvement of Asia’s presence in AI-based technologies. The role of regulators and universities will be essential in this area.

OpportunitiesNarrow technology gap vs.

developed markets.

Accelerated push from old to new economy

Weaknesses

AI innovation laggard

Lack of AI-based ecosystem

Strengths

Vast and emerging talent poolFreedom from legacy assets

Solid data growth

ThreatsRisk of job losses in

traditional industries.

Significant disruption in business models

Asia has the potential to become a global AI leader, but it still has a long way to go

Source: UBS



b) Lack of AI-based ecosystem: It is high time for Asia to form its own version of Silicon Val-ley, as an ecosystem in emerging industries like AI is clearly lacking. While a few cities like Bei-jing, Bangalore, and Singapore are attracting capital and talent, the lack of a true centralized location that offers uniformity may inhibit AI’s growth in the region, as both investors and tal-ent may pursue opportunities in developed countries like the US instead of Asia.

Opportunitiesa) Narrow technology gap vs. developed

markets: During the previous three industrial revolutions, the gap between developed and emerging markets widened significantly be-cause the underlying processes and technolo-gies driving the revolutions were mostly created and promoted in the West. It then took many years, if not decades, for Asia as a region to catch up. The fourth AI-powered industrial rev-olution provides a unique opportunity for Asia, as we believe Asia can be an early mover and begin to reap the benefits and thus narrow the gap with developed markets. This is based on our view that the enablers of AI, such as com-puting power, talent and algorithms, are now more global in nature, and Asia can capitalize on this advantage. An early-mover advantage in AI can help the region remain competitive and move up in the value chain across indus-tries.

b) Accelerated push from old to new economy: Despite the recent growth, Asia sig-nificantly lags behind the global average on services contribution to GDP. According to the World Bank, compared to the global average of 68%, Asia’s services contribution to GDP is be-low 60% with China’s contribution at a mere 48% and India at 53%. Meanwhile, developed economies score high with services contribut-ing close to 80% to GDP. Most business mod-els in Asia are manufacturing related and domi-

nated by state-owned enterprises. AI’s development as an industry can facilitate Asia’s transition from the old manufacturing-based economy to a new services-led economy. This is because AI can take automation to an ex-treme level and shift business models to be-come more focused on services. An example includes the potential shift of transportation from manufacturing automobiles to regular rid-ing services with infotainment and self-driving features.

Threatsa) Risk of job losses in traditional

industries: As discussed in the next section, although new jobs will be created, there is still a risk of AI-related job losses in Asia’s traditional industries like manufacturing, retail and transportation, especially those that in-volve predictable and routine tasks. We believe 30–50 million jobs in Asia will be affected by AI’s rise. However, within Asia, AI should also create many new categories of jobs; thus, we believe the net job losses will be far less and manageable.

b) Significant disruption to business models: In addition to job losses, AI is likely to significantly disrupt business models. We be-lieve many companies in Asia, particularly the incumbent leaders, still do not understand the level of disruption AI could create during the next few decades. And if companies fail to in-tegrate AI into their business models, they run the risk of market share losses and potential ex-tinction, the magnitude of which should ex-ceed that of the recent technological forces like e-commerce and smart devices.


Dr. John E. Kelly III Senior Vice President Cognitive Solutions and Research IBM

From a technology point of view, what are the key hurdles to make AI a mainstream technology? Frankly, a big hurdle is just public awareness. People don’t understand how mainstream AI already is. AI, or cognitive as we call it at IBM, is here.

Our cognitive system, Watson, is already a key part of everyday life for many of us – it’s expected to help more than one billion people this year. For example, Watson is helping peo-ple in the United States do their taxes better through our partnership with H&R Block, and thanks to IBM’s partnership with Quest Diag-nostics, it can analyze the genomic makeup of a tumor and identify treatment options or a clinical trial for that patient.

The challenge, now, is advancing this progress – drawing more developers to use cognitive engines like Watson to build their own apps and working with more businesses and indus-tries so they can incorporate cognitive solutions into their work. Cognitive needs to be embed-ded into the workflow of an enterprise.

What applications of AI provide the biggest economic benefit to Asia as a region? In Asia, I think there’s a big opportunity for AI to improve the services sector. Asia is home to many of the most densely populated places on the planet. So, a cognitive system that could improve the logistics of life, like a system that anticipates when smog and air quality will be particularly bad, will be really valuable.

Another area that you can’t ignore, whether we’re talking about economic benefit or quality of life, is healthcare. Over the past five or so years, we’ve partnered with great healthcare providers like Memorial Sloan Kettering Cancer Center to teach Watson how to analyze cancer and enable clinicians to provide personalized medical care to each patient. That technology is now being deployed in Asia, bringing to the region some of the world’s best medical care and expertise. At the Manipal Hospital system in India, for example, Watson is helping doctors identify personalized treatment options. Then there’s Gachon University Gil Medical Center in Korea, where Watson is helping oncologists keep pace with the massive volume of new cancer research that is published each year.

Technology has already disrupted many business models in Asian countries. Will AI take this disruption to the next level? We call systems like Watson “cognitive com-puting” because unlike “artificial intelligence,” which connotes a machine replacing human intelligence, our vision is that these systems will work in partnership with people. When we think of AI, we consider it “augmented intelli-gence” or man plus machine.

We expect cognitive systems like Watson will make professionals of all stripes more efficient, whether we’re talking about a tax preparer or an oncologist or a CMO of a Fortune 500 com-pany. Watson will ingest an extraordinary amount of “unstructured data” in those fields – data like social media posts, medical journals, or newspaper articles – and develop intelli-

This interview contains views which originate from units outside CIO Wealth Management. These units are not subject to all legal provisions governing the independence of financial research. The “Directives on the Independence of Financial Research”, issued by the Board of Directors of the Swiss Bankers Association (SBA) do not apply.

Interview

Interview


gence based on this data for professionals to use to make better decisions. In this way, we believe that cognitive systems are enhancing the way our world works. How do you see AI’s adoption in Asia? I think Asia is extraordinarily well-prepared to lead in the Cognitive Era, and here’s why: the pioneers of this era, the people that are actu-ally bringing cognitive solutions to different industries, are the app developers and the data engineers and scientists, and Asia has these skills in spades. India is now home to one of the largest populations of developers in the world.

Just as important, many countries in the region, like Singapore, Australia, and Korea, are invest-ing in initiatives to support their developer communities and the broader cognitive econ-omy. In fact, last year, the Korean government announced it would spend KRW 1 trillion (about USD 884 million) by 2020 to boost the artificial intelligence industry, which is part of the reason why Watson is now “learning” Korean.

Will AI narrow or widen the technology gap between Asia and developed markets?Cognitive isn’t as much about closing the gap between specific regions; it’s more about clos-ing the gap between all human beings and the sheer amount of information we produce. By 2025, humans will be producing 160 zetta-bytes of information every year. That’s a tre-mendous amount of information, and alone, we can only process a small sliver of it. How-ever, by working with a cognitive system like Watson, which can understand all types of data and process massive amounts of it, people can draw insights from all the data we pro-duce. It doesn’t matter whether you’re in Asia or North America or Antarctica, for that mat-ter, everyone with access to a cognitive system will also have access to a universe of insights.

What do you think is the impact of AI on jobs particularly for a region like Asia, which has more people-driven business models?AI systems are already changing the way work gets done. But history suggests that new tech-nologies like AI result in higher productivity, higher earnings, and overall job growth.

In particular, we believe that new companies, new jobs, and entirely new markets will be built on the shoulders of this technology. And as I mentioned before, I think Asia is particu-larly well-suited to take advantage of this new economy and these “new-collar jobs.” In addi-tion to the data scientists and app developers that will build these cognitive solutions, we expect there will be a huge demand for people with skills like “data labeling,” which are peo-ple who “teach” AI systems by feeding them relevant information.

Interview

Dr. John Kelly is senior vice president, Cognitive Solutions and IBM Research. He is focused on the company’s investments in several of the fastest-grow-ing and most strategic parts of the information tech-nology market, including IBM Analytics, IBM Com-merce, IBM Security, IBM Watson, IBM Watson Health and IBM Watson IoT, as well as IBM Research and the company’s Intellec tual Property team. Under Dr. Kelly, IBM Research expanded its global footprint by adding four new labs, creating a network of approximately 3,000 scientists and technical employees across 12 laboratories in 10 countries. Dr. Kelly and his team were responsible for advancing the science of cogni-tive computing through his support for Watson, the groundbreaking system that defeated two standing Jeopardy world champions in 2011. He holds a Bache-lor of Science in physics from Union College, and a Master of Science in physics and a Doctorate in mate-rials engineering from Rensselaer Polytechnic Institute. He has also received three honorary Doctoral degrees.


How does AI affect major industries in Asia?

In this section, we extend our global AI framework to analyze how AI could affect certain sectors in Asia. We have identified five industries - financial services, healthcare, manufacturing, retail and transportation – where we believe AI will have a disproportionately high impact. These sectors, with the exception of healthcare, could experience significant disruption from AI; but if companies in these industries successfully adopt AI, we believe the technology should create more opportunities than threats.

These five industries contribute around two-thirds of the region’s GDP currently, so stakeholders, in-cluding investors, corporates and policymakers, need to pay attention to AI’s development given the far-reaching implications for the broader econ-omy, employment and society.

Financial services

Asian financial services are already under the pro-cess of disruption by internet firms, as evidenced in large markets like China and India, and AI will take this disruption to the next level, in our view. The low-hanging fruit for AI within the Asian fi-nancial services industry is to leverage virtual assis-tants, chatbots or speech recognition software for regular customer interactions, thereby lowering the dependence on traditional banking channels like branches. Asian banks should get a major boost to risk management, which is traditionally a weak spot, as AI can help better manage cred-it-risk assessments and anti-money laundering programs. In the longer term, as robot advisors become more sophisticated, Asian banks can fur-ther utilize the technology in product marketing and after-sales.

0

800

200

400

700

300

500

600

100

Low-end

Financial services Healthcare Manufacturing Retail Transportation

Note: The numbers reflect range of high/low growth estimates off of current World Bank industry size.Source: World bank, UBS estimates as of January 2017

AI’s estimated economic impact on five major Asian industries in 2030Figures in USD bn

High-end

In the past 2,000 years, the hardware in our brains has not improved… In the next 30 years, AI will overtake human intelligence. – Masayoshi Son, Softbank


Insurance is another area within financial services where AI can have a long-lasting impact. According to OECD data, life insurance penetra-tion (as measured by direct gross premiums as a percentage of GDP) in Asia is significantly below the developed market average (low single digits vs. mid-to-high single digits). AI, through deep learning, can elevate the region’s insurance indus-try through better products and pricing, under-writing, target marketing and sales, claims man-agement, and overall data mining.

The risk, which other industry’s face but more so with banks, is that AI will level the playing field for emerging players from other industries, like tech-nology, to compete against the incumbent finan-cial giants. It is therefore imperative that existing banking and insurance firms take AI seriously and invest to maintain their differentiation.

Healthcare

Asia’s healthcare industry is a promising field for AI, as AI-based applications can positively impact the health of millions of Asians with better health outcomes. The key applications where AI holds promise in the region include decision-making support during clinical trials, robots to assist in surgery and patient monitoring, and managing healthcare data.

AI can have a clear impact on Asia’s healthcare in-dustry, which is currently underserved. According to the World Bank, the physician density (number of physicians per 1,000 people) in the region for key countries, such as China (1.5) and India (0.7), is sig-nificantly below developed markets like the US (2.5) and the European Union (3.5).

AI-based monitoring devices and robots for preci-sion surgeries are a few examples of how the re-gion stands to benefit from improved healthcare in the future. Additionally, better hearing aids, visu-al-assistive devices, in-home therapy and physi-cal-assistive devices like wheelchairs or walkers are other examples of how AI can transform Asia’s healthcare industry. Finally, we think AI can lever-age healthcare data generated in the region and mine outcomes with more personalized diagnosis and treatment.

Manufacturing

AI is at the center of the fourth industrial revolu-tion. It combines the innovation of industrial and IT processes to drive global manufacturing productivity gains. Like a brain, AI powers the ma-chine intelligence of industrial robots, significantly boosting the productivity of manufact uring pro-cesses. In addition to the ongoing expansion of

0

4.0

1.0

2.5

3.0

2.0

1.5

3.5

0.5

US SwitzerlandChinaIndia European Union

Source: World Bank, UBS, as of 2011

AI can help improve Asia’s healthcare coverage Physicians per 1,000 people

0

180,000

40,000

100,000

60,000

140,000

120,000

80,000

160,000

20,000

2015

North America

Europe China Japan SouthKorea

Others

Source: IFR World Robotics, UBS, as of 2016

Asia is a key driver of global smart automationNewly installed robots in 2015 vs. 2019E

2019E



industrial robot installations, we believe the ad-vancement of AI offers significant opportunities to Asia’s manufacturing industry, which is historically the leading driver of growth in the region.

AI will make Asian factories smarter, in which data from design and product teams to supply chains, including demand forecasting and quality control, are integrated into an intelligent machine. Thanks to the rising adoption of the Internet of Things, which utilizes sensor technology, Asian factories should become more competitive in the future. According to data from IFR World Robotics, Asia already accounts for around 50% of newly in-stalled robots. China is currently in the lead with a national 10-year plan, entitled “Made in China 2025.” We expect Asia’s annual share of robot in-stallations worldwide to reach 60% by the end of the decade and around 75% by 2025–2030.

Retail

Within Asia, we believe AI offers one of the broadest opportunities to the retail industry, which is highly fragmented and unorganized; for exam-ple, the combined market share for the top five retail companies in the US is 50% versus a sin-gle-digit share in Asian markets such as China and India. AI is already creating waves through the ris-ing trend of e-commerce, where penetration in most Asian countries is reaching mid-to-high sin-gle digits. China is the torchbearer of Asia’s e-commerce industry with mid-teen penetration rates. AI’s applications in e-commerce are mani-fold, including product discovery tools like visual and voice-based search, targeted marketing for customers, product recommendations based on user behavior, the use of robots in sorting orders, delivering goods through AI-powered drones, and virtual assistants or chatbots for customer care.

We believe significant progress will be made in Asia’s e-commerce industry because of AI, driving further penetration. AI also provides opportunities in the traditional retail industry by improving orga-nization in areas like supply chain management, marketing and advertising, sophisticated assistants and self-check-out systems. From a disruption point of view, medium-level jobs are mostly at risk, as machines may replace some of the more

routine and predictable tasks. That being said, AI will still power job creation in other retail areas like e-commerce, group buying and other creative areas.

Transportation

We believe transportation will be one of the industries most affected by AI. While AI has al-ready made inroads in the form of real-time moni-toring, traffic and route prediction, and ride-shar-ing in countries like China and India, self-driving, or autonomous vehicles, is the next big trend for the industry. According to the World Bank, most of the vast growth in global car ownership over the next decade will take place in Asia, with an in-crease of 220 million cars in China alone between 2010 and 2025. With human error responsible for almost 90% of road accidents in the region, it is thus imperative to explore autonomous driving as an alternative for both policymakers and industry participants.

Despite the early days and a bit of skepticism from consumers, the progress within Asia is on the right track. Japanese and Korean automakers are investing significant sums in driver-less technology and showcasing prototypes at various industry events. China plans to include automated or as-sisted driving in every car by 2026 to 2030. We believe that in the next few decades, Asia’s trans-portation industry will function and appear com-pletely different to today because of the mass adoption of autonomous driving technology.

In addition to reducing the chance of human er-ror, self-driving cars have the potential to free up time and provide opportunities for infotainment industries. Moreover, self-driving vehicles and peer-to-peer transportation may eliminate the need to own vehicles. The industry may shift en-tirely towards a service-driven model, which pro-vides more revenue visibility. In the longer term, the opportunity will be even bigger when self-driving extends to public transportation – at least in the 10 largest cities in the region – and and trucking, solving some supply chain challenges.



This interview contains views which originate from units outside CIO Wealth Management. These units are not subject to all legal provisions governing the independence of financial research. The “Directives on the Independence of Financial Research”, issued by the Board of Directors of the Swiss Bankers Association (SBA) do not apply.

Adam Coates Director, Baidu Silicon Valley AI LabBaidu

How do you view AI-related talent in Asia? Do you think the talent gap is narrowing between Asia and the USA? I think Silicon Valley currently is still the hotspot to rapidly develop and adopt new AI technolo-gies. There is a huge battle for talent there as the demand is really high. In Silicon Valley, peo-ple can pick up high-level deep learning and machine learning skills very quickly from differ-ent jobs, and they’re all in the same physical area. China’s internet ecosystem is very dynamic. It’s less clear to me, however, that someone who has good computer programming skills in a particular locale in China would be able to rap-idly pick up deep learning and contribute to the supply of machine learning talent in a way that all of the startups in China can harness to launch new products. I think it is happening there, but I sense there is no one place or a sin-gle pressure point, like Silicon Valley, where everyone is picking up these skills at a very rapid pace.

Fortunately, in the US, the top universities have developed AI programs and there are many graduates with high-level machine and deep learning skills. I think big Chinese companies that supply AI technology can have a hard time keeping up with demand, which would be extremely difficult for a small startup to build, partly because the amount of talent available to build these startups is quite small.

What are the unique advantages that Asia/China as a region possess that can help it become a leader in AI? China’s internet economy is very dynamic and nimble. China adopted technologies from the West very quickly, particularly the internet and mobile technology. This is not the case in the US, where the technology took some time to trickle down. I think China has the cultural advantage of adopting AI into their business models to gain competitive advantages over its peers.

Within Asia, Baidu is definitely a leader in AI. You can find that a lot of companies that are investing in AI that are following a portfolio approach. One thing in particular that I appreci-ate about Baidu is that it managed to pick out Deep Learning at a very early stage. Our efforts are primarily to convert these technologies into products.

When it comes to advantages in talent and big data, I think that the high-value things that mat-ter in Asia are much clearer to people working at homegrown businesses. For example, every-body in China uses QR codes but nobody in the US uses them. So, if you want to roll out a prod-uct in China, it is very important to have talent who know the local environment well. A locally grown product vision has quite an advantage because of the differences in language, culture, habits and even the government. China is a

Interview


Interview

mobile-first society, and Chinese users engage with their mobile devices more frequently than American users. In China today, when you are connecting to the internet it tends to be on a mobile device. Hence, the e-commerce websites in China are built in a way that is more attuned to mobile devices, and these devices even have larger screens to cater to user demands and habits. You can’t just copy a product from the USA and re-launch it in China; it won’t work.

Do you think AI will take disruption of old economy sectors to the next level? I think it’s possible depending on the type of business. We foresee that AI is going to have a vast impact on many different industries. In all likelihood, AI technology has the potential to improve an insurance company or a bank or a car company, but the hard part is that the sup-ply of able people is just not enough to deal with the number of different companies and apps out there. So, when it comes to the ques-tion of which industries are vulnerable to dis-ruption, I don’t see an inherently disruptive aspect in AI technology. I think if big compa-nies are able to integrate AI technology cor-rectly to optimize and cater to what their cus-tomers want, then they will be in a powerful position. AI is distinct in that it can make the value proposition of a company even stronger and take it to the next level, which is different from disruption. However, if a company fails to take advantage of AI, then there is the possibil-ity that they may be left behind.

Are there any aspects or areas of society in China or Asia that AI can have a major impact on? People in Asia are adopting mobile technology at a much faster rate than they did for desktops and laptops. But for users in China, typing in Mandarin on a small mobile device is a complex task. One of Baidu’s most popular software products is a speech-enabled keyboard add-on for mobile phones. We did a user study recently

and we found that when people type in Man-darin, they tend to do so more quickly and accurately with this new add-on. So we feel that speech recognition will be really transfor-mative for China and Asia.

I think speech recognition is critical, especially because of the way it can be integrated with different devices and accepted by users. Speech agents like Duer ignite something that goes beyond mobile platforms and can make things like IoT work. Unlike wired devices, you can just talk to these devices and from there they have the ability to function independently. I think there is a chance that the speech technology or personal systems that Baidu is building could create a technological ecosystem, similar to mobile.

In terms of changes to society, I think autono-mous driving is very interesting. China’s govern-ment exerts a lot of control over regulation. I think there is a chance to launch apps for self-driving vehicles in China that is different from those of the US. But I am not yet sure about how this will play out and feel that the technology still has some ways to go. Baidu’s technical capabilities are quite extraordinary, but there are still towering engineering chal-lenges that need to be dealt with.

Another interesting one is Baidu’s search engine that uses AI technology to profile users in details that are much deeper, intimate and fine-grained. It would not only provide simple rec-ommendations to buy other products that you may like online, but understand the user so well that you can push other things like interests, music, entertainment, information, etc. on the user’s Baidu search home page. Baidu is already creating a technology called User-Portrait to create high-precision models from dozens of Baidu products and partners. If it evolves, Baidu will deliver much more personalized experi-ences, which will be new and striking for users.


Interview

Where are we in the AI cycle? Will the industry get consolidated or will some standards emerge? The core part of deep learning is well under-stood now and heavily adopted by big internet companies. I think we are either at the peak or post-peak in terms of research, and now it needs to be making a business impact. I think there is enough tantalizing research to continue to capture the media hype. Work is still going on with supervised learning, reinforcement learning, and so on. The challenge now is to find someone who needs to find a killer applica-tion, and that is mostly a traditional business problem. On supervised learning, there is a lot of potential that has not been tapped, and we are limited in a way because we need labelled datasets. For speech recognition, we need tran-scribed speech, so there is an inherent limit to how much data we can use. If more progress is made in supervised learning, I think it could lead to many more new applications. So in computer vision and speech, there is a clear vision on what can happen in the next couple of years. Natural language technology is getting better gradually, but barring a research breakthrough, I don’t see it getting completely cracked.

Many startups that are building personal assis-tants and robots based on deep learning may soon realize that it is not a product by itself. In the VC world, the amount of funding available to do research on AI is much lower now than it was maybe three years ago. I feel that demand to see results from AI research will go up in the upcoming years.

Adam Coates is director of the Silicon Valley AI Lab at Baidu Research. He received his PhD in 2012 from Stanford University and subsequently was a postdoctoral researcher at Stanford. During his graduate career, Coates co-developed the most sophisticated autonomous helicopter in the world, capable of advanced aerobatic maneuvers. His thesis work investigated issues in the development of deep learning methods, particularly the success of large neural networks trained with large data sets. He led development of deep learning using distributed GPU clusters at Stanford. At Baidu his team builds HPC systems for large-scale deep learning and has applied them especially to speech recognition. The team’s speech system, Deep Speech, uses networks with billions of connections and tens of thousands of hours of audio to achieve human level performance in many cases, and has been deployed as part of Baidu products in English and Mandarin.


How employee skill levels vary across the world Breakdown in %

Asean APAC China EU Hong

Kong

India Japan Korea Singa-

pore

US World

Low skill 22 16 8 9 20 27 7 13 8 13 15

Medium skill 64 69 80 50 41 58 68 65 36 45 66

High skill 15 15 12 41 39 15 25 22 56 42 19Source: ILO, UBS as of January 2017

AI’s economic value for Asia

AI’s economic value for Asia

Based on the opportunities in the five major Asian industries discussed in the previous chapter, we estimate that AI could create economic value be-tween USD 1.8trn and USD 3trn a year by 2030 in the region. While this estimate is neither predic-tive nor comprehensive, it is based on our expec-tations of key AI-based applications in the region and the value they could create. This includes the additional economic value created from the intro-duction of new product services and categories, a consumer surplus (cost savings) arising from better products, lower prices and an overall improvement in lifestyles.

Our estimate of AI’s economic value creation for Asia’s five major industries can be seen in the chart on page 15. As a reminder, economic value should not be confused with the overall size of the industry, as our focus is on AI’s impact on both new revenue opportunities and consumer surplus. Our estimate of economic value, which represents 6–10% of the combined revenues from the five industries, is reasonable, in our view, and also consistent with our belief that AI will become mainstream in the region by 2030, leading to ad-ditional business revenues in the high single digits. In absolute terms, our analysis shows that the manufacturing sector should create the most eco-nomic value, followed by retail, healthcare, finan-cials and transportation; whereas on a relative ba-

sis, in terms of industry, the largest economic value from most to least should be created in healthcare, transportation, financial services, retail and manufacturing.

Artificial intelligence is the new electricity of the future. – Andrew Ng, Coursea

iSto

ck


We estimated that 50–75 million jobs globally will potentially be affected due to the mainstream adoption of AI, representing only 2% of the total workforce worldwide. Using a similar framework, we believe 30–50 million jobs in Asia are at a risk due to AI in the medium to long term. While we believe it will take a long time for AI to fully re-place these jobs, as AI technology needs to be fur-ther developed and due to the fact that corpo-rates and governments are still warming up to AI, we have extended the framework to assess the types of jobs that are most at risk in Asia.

For the purpose of our study, we used data from the International Labor Organization (ILO), as seen in the chart to the right, which shows the break-down of employment by industry. According to the ILO, low-skilled jobs require simple physical or manual tasks like office cleaners, freight handlers, kitchen assistants, etc. Medium-skilled jobs require reading information, such as safety instructions, to make written records or to accurately perform simple arithmetical calculations. These jobs include drivers, secretaries, accountants, clerks, shop sale assistants, etc. And high-skilled jobs involve the performance of complex technical and practical tasks, as well as those that require decision-mak-ing and creativity based on an extensive body of theoretical and factual knowledge. These jobs in-clude shop and marketing managers, medical lab technicians, computer support technicians, musi-cians, professionals and senior management. Given our view that AI will most likely impact occupations that involve predictable and routine tasks, we believe medium-skilled jobs are most at risk. This is based on our view that both low- and high-level jobs require some level of personaliza-

tion, creativity or craftsmanship. Against this back-drop, as seen in the table on page 21, Asia has a higher percentage of workers at the medium level (69%) compared to the global average (66%) but much less than developed markets like the US and the EU.

At present, manufacturing-driven economies like China are most at risk, while services-driven econ-omies, like Hong Kong, Singapore and India, should be less affected by widespread AI adop-tion. The good news is that the region’s ongoing shift from old economy to new economy should minimize the employment fallout. The rising trend

What does AI mean for Asian employment?At some stage…we should have to expect the machines to take control. – Alan Turing

0

30

10

25

15

20

5

Source: ILO, UBS, as of January 2017

Global share of employment across key industriesIn %

Agr

icul

ture

Reta

il

Man

ufac

turin

g

Con

stru

ctio

n

Fina

ncia

l & o

ther

ser

vice

s

Tran

spor

t &

com

mun

icat

ion

Educ

atio

n

Publ

ic a

dmin

Real

Est

ate

Acc

omod

atio

n &

Res

t

Hea

lthca

re

Oth

ers


What does AI mean for Asian employment?

of the sharing economy in countries like China is a positive development. The sharing economy, or collaborative consumption, where technology is used to share resources, such as ride-sharing, space-sharing and knowledge-sharing, is growing by leaps and bounds in markets like China; the in-dustry’s revenues in China are already in the hun-dreds of billions of US dollars, creating tens of thousands of new jobs. AI will be the key driver of the sharing economy in the future, helping to de-liver relevant results free from human interference, prevent data misuse, anticipate customer demand, and generate new jobs. Hence, we believe the net job losses from AI will be significantly lower than the headline figure, because we believe AI will also help to create new types of jobs in other in-dustries.

Like any technological evolution, overall employee productivity should significantly increase in Asia with the rise of AI, providing enough opportuni-ties for employees to upgrade their skills and fo-cus on other creative aspects. With the emergence of other disruptive business models like apps or sharing economies highly likely in a post-AI era, we see increased scope for jobs that require a high level of personalization, creativity or crafts-manship – tasks that will still need a person. Over-all, we think the fears of an employment crisis in Asia are unfounded, since AI will eventually drive innovation and provide employment opportunities in other areas in the region.

iSto

ck


What does AI mean for Asian stakeholders?

Artificial intelligence would be the ultimate version of Google. The ultimate search engine that would understand everything on the Web. – Larry page, Alphabet (formerly Google)

The next 10–15 years will be the most exciting pe-riod in the field of AI as we enter the AGI stage and the use cases for AI expand at an exponential pace. Unlike the previous industrial revolutions, Asia will likely be a key stakeholder this time around as AI becomes ubiquitous across the region. The implications for investors, society, corporates and governments will therefore be sig-nificant, in our view. Investors should avoid com-panies exposed to significant disruption from AI and embrace companies with a strong technology focus in areas such as robotic process automation (RPA) and machine and deep learning and R&D-in-tensive companies in sectors that can become more efficient from AI (e.g. healthcare, hi-tech en-gineering and select services firms).

While the ethical implications of AI still need to be worked out, if AI is implemented in an objective way to improve productivity, society stands to benefit immensely from the significant improve-ments to overall lifestyles and healthcare. It is still not too late for Asian corporates to hop on the AI bandwagon, as it is an irreversible trend that could potentially disrupt business models across markets. Asian corporates, particularly those in old economy sectors, should have an open mind and try to embrace AI rather than fight against it; we believe the benefits outweigh the risks. Failure to adapt to the AI-era may make some of these business models extinct. Finally, policymakers in Asia need to find a balance to ad-

dress AI’s benefits and risks to employment. Op-posing AI’s implementation in the region because of concerns over job losses alone would backfire, as we believe it would severely hurt competitive-ness and innovation. However, policymakers have a role to regulate and equally facilitate AI’s devel-opment and adoption. To address AI’s ethical di-lemmas, policymakers can be proactive over the next few years to introduce a code of conduct. And to address employment concerns, Asian gov-ernments can help increase the skill levels of its citizens and also encourage AI-based innovation through partnerships with universities and start-ups. We believe regional cooperation on these ef-forts could be more fruitful by not only developing common standards but also building a potential alternative to Silicon Valley.

Hence, from a society point of view, we should start to focus more on occupations that require a high level of personalization, creativity and crafts-manship, as these jobs will be less affected by AI. Regulators also need to step up their efforts by seeking cooperation regionally and also by strik-ing a balance between promoting the adoption of AI and managing the downside risks that could arise from the ethical dilemmas of AI or from oth-er societal aspects like job losses or changes. With these recommendations, we believe the transition towards an AI-based society would be smoother and a highly productive one.

What does AI mean for Asian stakeholders?

Chief Investment Office (CIO) Wealth Management (WM) Research is published by UBS Wealth Management and UBS Wealth Manage-ment Americas, Business Divisions of UBS AG (UBS) or an affiliate thereof. CIO WM Research reports published outside the US are branded as Chief Investment Office WM. In certain countries UBS AG is referred to as UBS SA. This publication is for your information only and is not intended as an offer, or a solicitation of an offer, to buy or sell any investment or other specific product. The analysis contained herein does not constitute a personal recommendation or take into account the particular investment objectives, investment strategies, financial situation and needs of any specific recipient. It is based on numerous assumptions. Different assumptions could result in materially different results. We recommend that you obtain financial and/or tax advice as to the implications (including tax) of investing in the manner described or in any of the products mentioned herein. Certain services and products are subject to legal restrictions and cannot be offered worldwide on an unrestricted basis and/or may not be eligible for sale to all investors. All information and opinions expressed in this document were obtained from sources believed to be reliable and in good faith, but no representation or warranty, express or implied, is made as to its accuracy or completeness (other than disclosures relating to UBS and its affiliates). All information and opinions as well as any prices indicated are current only as of the date of this report, and are subject to change without notice. Opinions expressed herein may differ or be contrary to those expressed by other business areas or divisions of UBS as a result of using differ-ent assumptions and/or criteria. At any time, investment decisions (including whether to buy, sell or hold securities) made by UBS AG, its affiliates, subsidiaries and employees may differ from or be con-trary to the opinions expressed in UBS research publications. Some investments may not be readily realizable since the market in the securities is illiquid and therefore valuing the investment and identi-fying the risk to which you are exposed may be difficult to quantify. UBS relies on information barriers to control the flow of information contained in one or more areas within UBS, into other areas, units, divisions or affiliates of UBS. Futures and options trading is consid-ered risky. Past performance of an investment is no guarantee for its

future performance. Some investments may be subject to sudden and large falls in value and on realization you may receive back less than you invested or may be required to pay more. Changes in FX rates may have an adverse effect on the price, value or income of an investment. This report is for distribution only under such circum-stances as may be permitted by applicable law.

Distributed to US persons by UBS Financial Services Inc. or UBS Securi-ties LLC, subsidiaries of UBS AG. UBS Switzerland AG, UBS Deutschland AG, UBS Bank, S.A., UBS Brasil Administradora de Valores Mobiliarios Ltda, UBS Asesores Mexico, S.A. de C.V., UBS Securities Japan Co., Ltd, UBS Wealth Management Israel Ltd and UBS Menkul Degerler AS are affiliates of UBS AG. UBS Financial Services Incorporated of PuertoRico is a subsidiary of UBS Financial Services Inc. UBS Financial Services Inc. accepts responsibility for the content of a report prepared by a non-US affiliate when it distributes reports to US persons. All transactions by a US person in the securities mentioned in this report should be effected through a US-registered broker dealer affiliated with UBS, and not through a non-US affiliate. The contents of this report have not been and will not be approved by any securities or investment authority in the United States or elsewhere. UBS Finan-cial Services Inc. is not acting as a municipal advisor to any municipal entity or obligated person within the meaning of Section 15B of the Securities Exchange Act (the “Municipal Advisor Rule”) and the opin-ions or views contained herein are not intended to be, and do not constitute, advice within the meaning of the Municipal Advisor Rule.

UBS specifically prohibits the redistribution or reproduction of this material in whole or in part without the prior written permission of UBS and UBS accepts no liability whatsoever for the actions of third parties in this respect.

Version as per September 2015.

© UBS 2017. The key symbol and UBS are among the registered and unregistered trademarks of UBS. All rights reserved.

Disclaimer

ab

Documents

April 2017 How artificial intelligence will transform Asia · How artificial intelligence will transform Asia ... What does AI mean for Asian stakeholders?..... 24 Contents ... Amazon’s