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Scenarios and Potentials of AI's Commercial Application in China

Scenarios and Potentials of AI's Commercial Application in China

Scenarios and Potentials of AI’s Commercial Application in

Contents

1. China’s AI industry overview 1 2. Industry-specific commercial application 5 3. Regions’ potentials of commercialization 14 Scenarios and Potentials of AI’s Commercial Application in China China’s AI industry overview

1. China’s AI industry overview

Globally, governments are mapping Figure 1. Global AI market size out national strategies on developing (RMB100 million) (AI) which 6,800 becomes the new engine in the future 7,000 of world economy. The global AI market 6,000 is estimated to reach RMB680 billion by 2020 with a compound annual growth 5,000 4,285 rate (CAGR) of 26.2%. Meanwhile, CAGR: 26.2% 4,000 China’s AI market is expected to be RMB71 billion by 20201since its growth 3,000 2,700 from 2015, with a CAGR of 44.5% from 2,307 1,684 1,971 2015 to 2020. 2,000 1,000 Despite the rapid growth, China is still young in developing AI . 0 Currently, the U.S. is way ahead of 2015 2016 2017 2018E 2019E 2020E China in several indicators of key AI Source: chyxx.com, Deloitte Research fields, such as global chip market share, number of talents and research Figure 2. China’s AI market size (2015-2020) capabilities. 800 710.0 700

600 500.0 500

CAGR: 44.5% 400 339.0 300 216.9 200 141.9 112.4 100

0 2015 2016 2017 2018E 2019E 2020E ■ China’s market size (RMB100 million)

Source: chyxx.com, Deloitte Research

1. 2017 China’s AI Industry Data Report, China Academy of Information and Communications 1 Scenarios and Potentials of AI’s Commercial Application in China China’s AI industry overview

Figure 3. The U.S. is way ahead of China in several indicators

ey fields Indicators China U.S.

Hardware Global market share of 4% 50% semiconductor products (2015)

Financing of FPGA chip USD34.4 million (7.6% of the USD192.5 million (42.2% manufacturers (2017) global total) of the global total)

Data Number of mobile 1.4 billion (20% of the 420 million (5.5% of the subscribers (2016) global total) global total)

Research capability Number of AI experts 39,200 (13% of the global total) 78,200 (26% of the and paradigm global total)

Proportion of speeches 20.5% of the global total 48.4% of the delivered at AAAI (2015) global total

Commercialization Proportion of AI 23% of the global total 42% of the global total companies (2017)

Investments gained by AI USD2.6 billion (6.6% of the USD17.2 billion (43.4% of companies (2012-2016) global total) the global total)

Investments from PEs for 48% of the global total 38% of the global total startups (2017)

Source: Public information, Deloitte Research

Scenarios and Potentials of AI’s Commercial Application in China China’s AI industry overview

Though it hasn’t been smooth sailing Category-specific problems are Practice issues are solved in for AI development, the explosive addressed in the technology layer. the application layer, in which AI growth from 2015 has been different China has experienced rapid growth provides targeted products, services from the past as AI in the new era has in the technology layer and now and solutions to industries with been commercialized, mainly driven focused primarily on , commercialization at the core. by improved computing power, top- and language Currently, this layer makes up the level design, capital support and user processing. Many giants, including largest part in China’s AI layers by demand. , and Alibaba, have the sizes and numbers of companies. so far begun to build their own AI With an advantage of data, giants AI industrial chain falls into the platforms with the aim to extend their set about building their open-source following three layers: industry advantages in the age of AI. platforms targeted on the application Start-ups, such as SenseTime and layer; among those start-ups, Computing power is provided in the Megvii, are actively setting up their unicorns represented by SenseTime basic layer, mainly including AI chip, technology platforms and extending also expands their presence in the sensor, and cloud computing, their researches into the basic layer, application layer while enhancing R&D in which China is relatively weak. such as algorithm framework. efforts in the technology layer. Tech giants represented by BATJ have started to build their own AI related basic discipline labs, increase inputs to R&D and expand investments into start-ups in the basic layer.

Figure 4. Four drivers for AI market growth

Continuous technological Capital brings industry boom advances builds a solid The global investment and foundation for AI growth financing into AI reached In the past five to ten years, AI Computing power Investment USD39.5 billion from 1,208 technology has been financing events in 2017, of commercialized largely on the which the total amount in China back of dramatically enhanced reached USD27.71 billion from computing power thanks to 369 events. The proceeds raised the integration of improved by Chinese AI companies chip processing capability, accounted for 70% of the global accessible cloud services and total and the number of declining hardware price, such financing events took up 31%. as seniors.

AI is the new engine for AI are increasingly applied the future economic growth in people’s life and Several policies have been business activities introduced to support AI since The growth of AI technologies 2015, providing large amounts satisfies the demands of of project funds for the businesses, customers and development and governments on improving implementation of AI Policy User demand living standards, business technologies and supporting AI competitiveness and talent introduction and government efficiencies. corporate innovation.

Source: Deloitte Research

Scenarios and Potentials of AI’s Commercial Application in China China’s AI industry overview

Figure 5. China’s AI industrial chain map

Hard asy

Basic layer Technology layer Application layer

Hardware Software Hardware Software

Sensor Cloud, data Speech recognition Healthcare Hesai and algorithm iFLYTEK SoundAI Truking Radmedical Bangeyisheng 12Sigma LeiShen DeePhi Tech Sinovoice AI Speech TINAVI Jianpei Huiyihuiying.com Wingspan Intelligent CloudMinds Nanochap iFLYTEK QED Technique Infervision System Liangzijinrong. Semantic recognition and analysis Autonomous driving RoboSense com Tricorn ruyi.ai MOMENTA Uisee Technology ZongMu Technology MINIEYE SLAMTEC Toutiao.com Boson Mor.AI GTCOM Drone Customer Personalized push Mobvoi DJI Yuneec service Toutiao.com Mioji HerCamera Zerotech Xiao-I Robot Shangzhuangyuan Machine vision Yunwen Sing Palette Technology Chip SenseTime TuSimple arehousing logistics Finance MediaTek Megvii BooCax Linx Sobot Tiantiantou HiSilicon YITU Malong Technologies Libiao Robot SenseTime Horizon CloudWalk Emotibot Water Rock Technology Dingfudata Seetatech Pinguo Geek+ NBS Data Technology Cambricon Sensingtech ReadSense Industrial cooperation 10jqka.com.cn Intellifusion Tuputech LINKFACE Sublue ocean Whalestock.com Westwell Viscovery FaceThink AUBO Licaimofang Canaan VIONVISION Face all Touchnet Technology CreditX JOHAR PERCEPTIN Yi+ Technology AuthenMetric Intelligent robot Others Marketing UBTECH Xiaoyu Zaijia Prafly Jixianyuan Appier Yunnex roobo Ecovacs Zhuge.com Rokid CANBOT Others ducation Shenhao 4Paradigm IrisKing yuantiku.com Yixue SpeakIn Hongshi Technology Xiaozhi Knowbox Apogee Tech

Comprehensive company Alibaba Tencent Baidu JD 360 Sogou Cheetah Mobile

Hard Source: Public information, Deloitte Research

Scenarios and Potentials of AI’s Commercial Application in China Industry-specific commercial application

2. Industry-specific commercial application

AI technologies have developed based on the following considerations: rapidly in the past five to ten years and ••Does the industry generate large become widely known over time. The volumes of reliable and stable data? Moore’s law has slowed down and the business application of AI has come ••Tech giants do not have an absolute into focus. As tech giants are deploying advantage over start-ups in access vertical industry applications, start- to data. ups need to identify entries and focus ••Is it a hot sector attractive to on industry-specific solutions to build investors? their strengths. Deloitte expects to see the booming of AI in government ••Can the products and applications administration, financing, healthcare, properly address industry pain automotive, manufacturing and points?

Figure 6. China’s digital government market size forecasting

(RMB100 million) 3,500 3,140 3,000 2,722 2,500 2,343 2,067 2,000

1,500

1,000

500

0 2015 2016 2017 2018E

Source: qianzhan.com, Deloitte Research

Scenarios and Potentials of AI’s Commercial Application in China Industry-specific commercial application

Digital government promoting the smart governance As China is advancing digital by establishing one-stop service governance, government platforms. For example, administration becomes a major Municipal Public Security Bureau channel through which AI may has leveraged facial recognition establish its presence in use scenarios to simplify household registration of smart governance and public procedures and built a citywide security. High entry barriers resulting system for sharing governance from local governments imposing information and resources that pools strict requirements on providers over 3.8 billion pieces of data in 385 enable strong players to be stronger. categories of information from 29 As early adopters have built industry organizations2. barriers, the rest will need to address ••Public security: An AI powered the consequent data fragmentation to security system functioning secure long-term progress. intelligently in real-time. For instance, using big data and cognitive Digital governance is built on top-down intelligence technologies, such policy initiatives and the market is system can identify a crime before expected to exceed RMB300 billion by it is executed and detect other 2018 with a CAGR of 15%. potential risks, turning the focus ••Smart governance: The most from post-incident investigation to fundamental and rapidly developing proactive prediction, early warning field in smart governance. Local and prevention. governments across China are

Figure 7. “AI+” governance industrial chain

Basic layer Technology layer Application layer

Chip Machine vision Smart governance • Cambricon • Cloudwalk • Ultrapower • Horizon Robotics • Megvii • MiningLamp • HiSilicon • SenseTime

Sensor Speech recognition Public security • • iFLYTEK • Cloudwalk • • SinoVoice • Hytera •

Cloud service Semantic recognition Others • Alibaba Cloud • Turing Robot • Ping An Technology • Sugon • Alibaba Cloud • Tencent Cloud • NetEase

Integrated solutions Alibaba Tencent Baidu HIKVISION Percent Huawei

Source: Public information, Deloitte Research

2. Understanding the fundamental significance of sharing government services resources through Shenzhen’s experience, Xinhuanet Scenarios and Potentials of AI’s Commercial Application in China Industry-specific commercial application

Finance ••Smart investment advisory: ••Smart customer service: AI technologies are disrupting pivotal expands financial services to responds to simple questions areas of the traditional financial groups beyond the traditional using technologies such as natural industry. As consumer behavior and wealthy. As an online tool, it can language processing and knowledge needs evolve, traditional players are automatically evaluate clients’ graph, and resolve users’ product pressed to reshape various areas and financial positions and employ big or service-related issues through parts of their businesses. data analytics to provide customized human-computer interaction. In recommendations, manage finance, smart customer service is Currently in the finance industry, AI investment portfolios and invest in mainly applied to subsectors like is most widely applied to investment quality products. banking, insurance and Internet advisory, customer service and risk financing. control.

Figure 8. AI technologies are transforming the whole operational process

Businesses Transformation Cases Outcomes

Services •• Online intelligent ICBC’s intelligent customer service robot “Gongxiaozhi” •• Reduce labor costs customer services provided over 100 million services in 2017 •• Improve service efficiency •• Customer service robots •• Enhance customer experience for bank outlets

Front Marketing •• Targeted marketing Tencent Cloud employs marketing-related big data •• Increase ad conversion rate generated from Tencent ecosystem for accurate user and reduce marketing costs profiling and labelling and advertises by modelling based on self-developed advantageous advertising algorithm

Product •• Customized and mjzt.com, an intelligent investment advisory service of •• Targeted product pricing personalized products , has over 150,000 users worth •• Engage “long-tail” customers •• Intelligent investment more than RMB10 billion and expand businesses advisory services

Risk •• Credit rating With an intelligent risk control brain based on massive •• Reduce risk compensations Middle control •• Risk-based pricing data, Ant Financial is able to bring Alipay’s asset loss rate •• Reduce risks of bad debts •• Dynamic monitoring below 0.001% and make it a world leader •• Quickly identify financial frauds

Management •• Internal risk control Ping An Group implements intelligent remote •• Improve management •• Intelligent office management based on data modeling and visualization efficiency and costs

Back Data •• Data analytics Tencent collaborates with Beijing Municipal Bureau of •• Improve data security level •• Proactive data security Financial Work to develop a Beijing-based financial and lower business risks protection security big data monitoring platform that identifies, monitors and warns against financial risks

Source: Public information, Deloitte Research

Scenarios and Potentials of AI’s Commercial Application in China Industry-specific commercial application

••Smart risk control: using tools finance. With technological advantages, like big data and knowledge AI companies are able to provide graph, financial organizations can hardware devices or software systems address traditional problems such for traditional financial institutions, as transaction fraud, credit risk yet still rely integrated solutions and management and credit default in data acquisition on other players; a more effective manner. Asset loss Internet companies, with strengths in rate is a key indicator to measure the data acquisition and engagement in risk control capabilities of financial Internet finance, can offer experience organizations. With smart risk and technical support for traditional control, Alipay is able to achieve a financial institutions along their globally competitive asset loss rate of journeys of transformation; traditional lower than 0.001%. financial service providers also start to reshape themselves by building Businesses engaging in the AI-driven their own technological departments financial services market mainly come to protect data confidentiality and from the sectors of AI, Internet and security.

Figure 9. “AI + finance” industrial chain

Basic level Technology level Application level

Chip Machine vision Smart investment advisory • Cambricon • Megvii • CMB • 10jqka.com • • Cloudwalk • Tianhong Asset • NOVUMIND • SenseTime Management • ICBC Sensor Speech recognition Smart customer service • Inspur • iFLYTEK • Xiao-i • eGOVA • NUANCE • Sobot • BOSCH • Yunwen Technology

Cloud service Semantic recognition Smart risk control • Alibaba Cloud • Turing Robot • Tongdun • Ant Financial • Tencent Cloud • ruyi.ai • Rong360 • 360jie.com • JD Cloud

Integrated solutions JD.com Tencent

Source: 36kr.com, public information, Deloitte Research

Scenarios and Potentials of AI’s Commercial Application in China Industry-specific commercial application

Figure 10. Smart healthcare industrial chain

Smart healthcare industrial chain

eeh Speech input, speech to text etroni edia • Unisound conversion reord • Huiyihuiying.com atura anuae Structured and classifiable • iFLYTEK roessin medical records Couter Influence preprocessing and edia iain • Infervision • YIDUCLOUD • iFLYTEK vision extract eigenvalues Food image recognition for eath • More Health • Airdoc • iCarbonX balanced diets anaeent

oot Smart-phone robot, Assisted dianosis • TINAVI • Smarobot • SIASUN robot guide for patients and treatent

ahine DNA sequencing Disease isease ris • Berry Genomics • BGI earnin prevention analysis assessent • PrecisionMDX Drug R&D and screening, side ru disovery • Cipher Gene • 3DMed • Ribo effects forecasting and tracking Power medical data mining and osita • Medbanks decisions with anaeent • Guangzhou Ruida Medical Instrument Technical platform to assist osita anaeent • Infervision • LinkDoc • Synyi AI medical researches using AI ator

Source: Public information, Deloitte Research

Healthcare by analyzing images. The second is AI in healthcare is facing regulatory Diagnosis and treatment, medical , which is used in the and technical challenges. From the imaging and health management are processes of learning and analyzing, regulatory aspect, as the healthcare the three areas that pioneered the use where large volumes of image and industry deals with people’s life safety, of AI products in healthcare. diagnostics data are used to train patients’ data must be kept with the deep learning capabilities of absolute security and confidentiality ••Smart diagnosis and treatment: the neural network for it to acquire and safeguarded under rigorous applies AI technologies in diagnosis diagnostics skills. In China, several legal regulations. From the technical and treatment assistance by making AI healthcare platforms including perspective, smart healthcare requires the computer “learn” medical iFLYTEK and Tencent have completed troves of data and complex training knowledge from medical experts clinical trials of smart medical framework, but few companies have and doctors and imitate how doctors imaging in collaboration with medical both technology capabilities; the think and make diagnosis, so as organizations. algorithms for combined diagnostics to provide reliable diagnosis and of complex disciplines are shackled treatment plans. Several projects ••Health management: Currently, it by technical bottlenecks; and the have been implemented in China, is primarily applied to risk detection, technologies and products are most notably solutions like IBM virtual nursing, mental health, markedly homogenous. Watson Health. online medical consultation, health intervention and health management ••Smart medical imaging: AI based on precise medicine. The technologies in this area mainly fall emphasis on prevention and into two categories. The first is image conditioning and individualized recognition. Applied to the process management is driving health of sensing, it serves primarily to management to become popular in generate meaningful information preventive medicine.

Scenarios and Potentials of AI’s Commercial Application in China Industry-specific commercial application

Smart mobility Autonomous driving will be applied ••Shared driverless cars: Traditional In the era of AI, the value of smart to driverless delivery and shared carmakers’ model of selling car mobility ecosystem which affects driverless cars: ownership will be challenged by the automotive industry is being service-sharing platforms, self-driving ••Driverless delivery: Once redefined. The three essentials of software and the Internet of Things commercialized, driverless heavy mobility, namely “human”, “vehicle” (IoT). The emergence of autonomous trucks will set drivers free and and “road are changing dramatically driving will lead to the continued achieve companies’ goals of as AI enables humanlike decisions and expansion of shared automotive energy consumption and emission behaviors, and the entire ecosystem products. In the future, car’s role as reduction, contributing to global will also change remarkably. Strong a personal property will be a thing of warming control. But no technology computing power and massive data the past while the concept of shared comes without limitation. Due to with high values are at the core of transportation rise to take its place. high electricity consumption, it is a multidimensional, coordinated Traditional carmakers who are eager economically unfeasible to extend mobility ecosystem. As the application for transformation are thus pressed battery life during long-distance of AI technologies in transportation to accelerate their cooperation with transports for now. The emergence is becoming more intelligent, AI technology providers and Internet of driverless cars will give rise to car electrified and shared, an intelligent giants that have massive user data. sharing scenarios and transform the transportation industrial chain automotive ecosystem. centered on autonomous driving will emerge.

Figure 11. Autonomous driving industrial chain

Intelligence Chip Communication

aidu eehi Internet of ehicles Carion High-precision map enseie orion ootis evii estwe aidu a I Inteiusion avino Idriverus tar aviation Aiaa Aa Autonomous enent driving industrial Control chain ehicle AIC otor Braking System Throttle inuato Steering system Brake aidu autonoous drivin AIC inuato honyunhihe .o autonoous drivin AC rou AIC otor Sensing I Camera Millimeter wave Lidar Ultrasonic radar

eiin eretion ehnooy eeteh enewae eeteh heyia.o awye ehnooy

Source: Public information, Deloitte Research

1 Scenarios and Potentials of AI’s Commercial Application in China Industry-specific commercial application

Figure 12. Smart manufacturing industrial chain

Product Manufacturing and production Supply chain

Generative Product quality Production resources Prediction of design inspection allocation resources demand • AUTODESK • Aqrose • and sales • Rhinoceros • Govion Technology • CASICloud • JD.com • Neptune • Raystrong Production process Intelligent optimization products • AInnovation Autonomous storage • Huawei Sorting • SIASUN optimization • • RISEYE • Geek+ • Xiaomi • Mech-Mind Predictive production, • Quicktron • Vivo • NeuroBot operation and maintenance • Xiao-i • COBOT • Alsontech • WYSEngine

Source: Public information, Deloitte Research

Manufacturing higher labor productivity3. By 2030, AI Combining AI and related technologies will increase global GDP by USD15.7 can optimize the efficiency along the trillion, of which USD7 trillion will come manufacturing processes, collect a from China; by 2035, AI will improve variety of production data through labor productivity by 27%, driving industrial IoT and by applying deep manufacturing GDP up to USD27 learning algorithms, generate trillion4. recommendations and even achieve autonomous optimization. Yet Three key application scenarios of AI in compared with finance, commerce and manufacturing: healthcare industries, AI’s application ••Product: Intelligently research, potential in manufacturing has been develop and design products, and considerably underestimated. SAP’s inject intelligence into products. analysis of China’s biggest 300 AI These may include generative design, investment deals over the three years a solution that uses algorithms to shows that 23.4% investments were explore a multitude of possibilities poured into commerce and retailing based on given goals and constraints. sectors, 18.3% in autonomous driving while less than 1% went into ••Production and manufacturing: manufacturing-related AI applications. With data management, As a manufacturing power, China’s incorporation of automated and investment in AI is disproportionate interconnected equipment, robots with the vast potential of its can achieve precise coordination manufacturing sector, which is the of product lines, higher prediction sector with the most promising AI accuracy and real time problem application scenarios. Adoption of detection through machine learning AI may lower processing costs of and analysis. Currently, the main manufacturers by a maximum of 20%, applications include product quality and 70% of the saving will come from inspection, smart automated sorting,

3. Soul of the machine: AI in the factory of the future, 36kr.com, 9 May 2018, https://36kr.com/p/5133138.html 4. AI-manufacturing fusion will be the prevailing trend, Communication Information News, 29 August 2018, http://www.fjii.com/jx/2018/0829/179887.shtml 11 Scenarios and Potentials of AI’s Commercial Application in China Industry-specific commercial application

predictive production, operation and •• Consumer: AI enables demand maintenance, production resources forecasting, customized marketing, allocation and production process shopping experience improvement optimization. and intelligent customer support primarily to achieve continuous and ••Supply chain: Demand/sales effective consumer engagement. prediction and autonomous storage During last year’s “Double 11”, Alibaba’s optimization are the main scenarios. intelligent recommendation system Some businesses use machine generated 56.7 billion exclusive learning algorithms to identify shelves for users. A study has found demand models by integrating data that compared with conventional from storage, Enterprise Resources webpages, personalized webpages Program (ERP) and customer insights. uplift conversion ratio by 20%.

Retail ••Goods: Applications include assisted As AI has accelerated the integration payment, stocktaking, promotion and of new retail omni-channel, traditional pricing through intelligent shelves. retail businesses team up with start- •• Store: siting, in-store shopping ups to build application scenarios experience and unmanned stores around customer, goods, store and that primarily serve to maximize the supply chain.

Figure 13. Application scenarios of AI and AI-powered application in global manufacturing market

100%

80%

60% 1 .1 40% 1 1

20% 1

1 1 0% 2016 2025E

■ Industrial robot ■ Manufacturing IoT ■ Manufacturing cloud (public)

■ Manufacturing big data ■ Manufacturing AI ■ Intelligent factory application/solution and business analysis

Source: Markets and Markets Insights, Deloitte Research

1 Scenarios and Potentials of AI’s Commercial Application in China Industry-specific commercial application

Figure 14. Smart retail industry

Attract consumer Stock Redefine Smart engagement management stores supply chain

User profile Intelligent shelf Store siting Demand prediction • Percent • ImageDT • BEHE Adtech • Cardinal • Sensors Data Solution Operations • Dt Dream • GeoHey

Online shopping Intelligent stores Intelligent logistics eperience • Cloudealk • Youhualin • Malong • Keruyun • Linx Technologies • ML • inData • Jirui Tech • Lanxin Unmanned retail Smart customer • DeepBlue service Technology • F5 • Abitai • Tuzi City

Source: Public information, Deloitte Research

benefits of investment into stores. and corresponding sales data of AI-powered siting combines a variety retailers, integrates user profiles of data including sales records, and supplementary external data demo-economic data and distance to automatically generate pricing to competitors to bring the data strategies and recommendations for granularity and relevance of siting retail goods through data algorithm model to a new high. models, thus providing relevant strategic suggestions around revenue •• Supply chain: intelligent pricing, management goals and ultimately delivery and storage for improved forming intelligent pricing plans. efficiency. AI-powered pricing, based on daily price changes

1 Scenarios and Potentials of AI’s Commercial Application in China Regions’ potentials of commercialization

3. Regions’ potentials of commercialization

AI technologies have been AI and offered tax benefits, subsidies, commercialized and applied in talent introduction and government various industries since 2015. The process optimization to optimize the prospect of commercialization business environment, attract strong has been generally recognized by companies and help develop local AI governments, companies and other companies and application markets. all parties. In order to promote the Driven by policies and capital, a healthy industrial upgrading and transform competition in AI industry among old economic drivers into new ones, regions has taken shape and become a governments have introduced guiding catalyser in the rapid growth of China’s opinions on industrial plans related to AI commercialization.

Figure 15. Distribution map of China’s AI companies

400 368 350

300

250

185 200

150 131

100 95

39 50 25 16 12 10 9 6 6 5 5 3 1 1 1 1 1 1 1 0

Tibet Beijing Fujian Hubei Tianjin Anhui Henan Shanxi Hunan Shanxi JiangsuSichuan ShanghaiZhejiang Liaoning Guizhou Guangxi Shandong Chongqing Heilongjiang

Source: iyiou.com, Deloitte Research

1 Scenarios and Potentials of AI’s Commercial Application in China Regions’ potentials of commercialization

Figure 16. Analysis from five dimensions

First-level indicator Second-level indicator

Policy Planning and policy

Capital Investments and proceeds raised

Technology Patent

Research universities and institutions

Number of companies

Computing power

Talent Number

Application Convenience offered by for residents’ living

Operating efficiency improved through urban management

Source: Deloitte Research

In the city layer, Beijing, Shenzhen, Policy and have the The number of policies, policy direction largest numbers of AI companies, all and financial subsidy are three having more than 90. They are in the ways of measuring regions’ policy top tier with the combination of AI and efforts. In terms of the number of AI urban development far over other related policies introduced, Shanghai cities, thanks to their advantages in ranks first, followed by Beijing, policy, capital, technology, talent and Shenzhen, Hangzhou, Guangzhou, application. Based on the location and Chongqing. With the support in features of AI companies, the report planning and capital, they leverage selects Beijing, Shanghai, Hangzhou, innovative technology resources and Shenzhen, Guangzhou and Chongqing strengths in talent and market to build from Beijing-Tianjin-Hebei Region, AI clusters. From the perspective Pearl River Delta, Yangtze River Delta of policy direction, each of these and Western China and analyzes cities focuses on developing the AI these six cities from the perspective of industries respectively based on their policy, capital, technology, talent and own characteristics. Guangdong’s application. policies focus on applications, while

1 Scenarios and Potentials of AI’s Commercial Application in China Regions’ potentials of commercialization

Figure 17. Proceeds raised by AI start-ups (by city)

(RMB100 million) 600 550

500

400 350

300

200

100 87 25 14 8 0 Beijing Shanghai Shenzhen Hangzhou Guangzhou Chongqing

Source: iyiou.com, Deloitte Research

Beijing places stress on the integration offers technology innovation funds of industry, university and research while Shanghai set up a RMB200 and technological innovation; million special fund for AI innovations. Shanghai highlights support for Chongqing provides a fund of up to talent, innovation ecosystem, industry RMB10 million for qualified projects. cluster and investment and financing; Hangzhou emphasizes AI industry Capital structure and application and Dynamic capital environment has a Chongqing focuses more on promoting positive impact on helping AI start- the integration of technologies with the ups in technology upgrading, user traditional manufacturing industry. In acquisition and market expansion, the financial subsidy aspect, it mainly facilitating upstream and downstream includes project fund, subsidized loan companies in the AI industrial chain to and special industry fund for industry gain the benefits of scale economy. As development. Hangzhou set up a start-ups act as the pioneer in the R&D RMB3 billion special fund for AI Town; and application of new technologies, Shenzhen offers project funds (capped the proceeds they raise partly at RMB45 million), subsidized loans indicate the prospect of the region in and intellectual property funds for developing new technologies. emerging industries; Beijing primarily

1 Scenarios and Potentials of AI’s Commercial Application in China Regions’ potentials of commercialization

Technology established research universities In terms of technology, we analyze the and institutions, Beijing has the most features of China’s regional technology remarkable scientific achievements development from patents, research with more than 8,000 patents. universities and institutions, number of companies and computing power. Features of universities: China’s AI papers published have outnumbered Number of patents: With increasing those of the U.S. and other countries R&D funds and social capital into since 2014, largely driven by the China’s AI technology reserves, rapid growth of Chinese AI research China is a leader in the number of AI universities and institutions, which patents. According to the statistics of are also the main force of AI patent the number of patents held by major applications.

Figure 18. Number of patents held by research institutions, universities and leading companies (by city)

9,000 8,183 8,000

7,000

6,000

5,000

4,000

3,000

2,000 1,360 1,013 1,000 739 680

0 Beijing Hangzhou Guangzhou Shenzhen Shanghai Chongqing

Note: Incomplete statistics; given key statistics of the most outstanding large Chinese research universities and institutions in AI sector, the number of patents of cities may be different from the total.

1 Scenarios and Potentials of AI’s Commercial Application in China Regions’ potentials of commercialization

Figure 19. Features of AI research institutions and universities (by city)

Features Universities Labs jointly built by government or Companies’ labs research institutions and universities

Beijing •• Strongest R&D technology Take up over 50% of Over 10 labs: • 360 capabilities the country •• National Laboratory of Pattern • Xiaomi •• Recognition • Sinovation Ventures • Baidu •• •• State Key Laboratory of Intelligent Technology and Systems • Meituan •• Beihang University • Toutiao.com •• National Engineering Laboratory for Deep •• Institute of Learning Technology and Applications • Automation, Chinese • JD Academy of Sciences

Shanghai •• Mainly rely on universities; Lots of universities: •• SJTU-Versa Computer Science and • SAIC Motor the number of companies’ AI Joint Lab •• • Philips research institutes/labs is smaller than Beijing but •• Shanghai Jiao Tong with certain academic University foundation •• Tongji University

Shenzhen •• Mainly rely on companies •• Shenzhen University Mainly led by governments: • Tencent

•• Southern University •• Shenzhen Academy of Robotics • Huawei of Science and • ZTE •• Shenzhen Research Institute of Artificial Technology Intelligence and Big Data

Hangzhou •• A certain gap with Beijing, •• University • Alibaba Shanghai and Shenzhen • NetEase • Geely Auto

Guangzhou •• Mainly rely on iFLYTEK Labs jointly built by universities and companies:

•• Cooperation between iFLYTEK and universities, including SCUT-iFLYTEK joint lab for brain- machine cooperation intelligence technology and application

•• SCNU-iFLYTEK joint lab for the integration and innovation of industry big data application

Chongqing •• Weak in AI technology •• Chongqing University •• Chongqing Institute of Green and • CloudWalk Intelligent Technology, Chinese Academy •• Chongqing University • Kaize Technology of Sciences of Posts and Telecommunications

Source: Public information, Deloitte Research

1 Scenarios and Potentials of AI’s Commercial Application in China Regions’ potentials of commercialization

Number of AI companies: As of the Figure 20. Number of AI companies by city (as of June 2018) first half of 2018, there are nearly 5,000 AI companies detected around the 450 world, with China only second to the 395 400 U.S.5. The numbers of AI companies in Beijing, Shanghai, Shenzhen and 350 Hangzhou rank in the global top 20. 300 Beijing has distinct leading advantages with about 400 companies; Shanghai, 250 210 Shenzhen and Hangzhou grow fast. 200 Chongqing has few AI companies due 150 to technology and talent constraints. 119 100 63 46 50 5 0 Beijing Shanghai Shenzhen Hangzhou Guangzhou Chongqing

Source: China’s AI Development Report 2018, Tsinghua University, Deloitte Research

Computing power: From city Figure 21. Ranking of computing power (by city) distribution perspective, leading cities in China are all located in coastal areas with more advanced AI technologies. Hangzhou, Beijing, Shenzhen and Shanghai rank the top five while Chongqing and Guangzhou rank lowest.

eiin

hanhai

1 anhou

ih Chonin henhen

uanhou ow

Source: 2018 China AI Computing Power Development Report, Inspur, IDC, Deloitte Research

5. 2018 World AI Industry Development Blue Book, China Academy of Information and Communications Technology and Gartner, 2018-09, http://www.caict.ac.cn/ kxyj/qwfb/bps/201809/P020180918696199759142.pdf 1 Scenarios and Potentials of AI’s Commercial Application in China Regions’ potentials of commercialization

Talent Figure 22. Proportion of number of AI talents (by city) China’s AI talents are distributed unevenly but mainly concentrated in Beijing-Tianjin-Hebei Region, Yangtze River Delta and Pearl River Delta with a certain amount of talents in central and western china along the Yangtze River. Beijing is the most dominant city, accounting for 28%, doubling that of Shanghai (12.1%) in the second place. The proportions of Guangzhou, Shenzhen, Hangzhou and Chongqing are all lower than 10%, sitting in the second tier. This is largely because many strong AI companies concentrate in developed areas with support from governments and social capital, as well 27.9% 30% as higher compensations for AI talents than other areas. 25% 20% Application of the cities 15% From the application perspective, 12.1% 10% 8.5% the deployment of smart city brings 6.5% substantial benefits for these cities, 5% 3.9% 1.2% including improving the convenience 0% and quality of people’s life. With Beijing Shanghai Shenzhen Hangzhou Guangzhou Chongqing positive support from governments, Source: Global AI Talent White Paper, China’s AI Development Report 2018, Tencent, Deloitte Research Hangzhou leverages Alibaba’s leading Note: The map presents the numbers of AI talents in these cities with the darker the color is, the more AI experience in AI sector to build a smart talents the city has; bar charts represent the proportion of AI talents equals the number of AI talents one city city centered on services benefiting has/China’s total AI talent people. Beijing has stronger research capabilities and leading AI companies, Figure 23. Ranking of smart life (by city) but the smart services benefiting people are not good as Hangzhou due to many considerations of Hangzhou 1 governments. Cooperating with many local AI companies, such as Huawei Beijing and ZTE, Shenzhen provides services benefiting people and achieves certain Shenzhen results. Guangzhou and Shanghai make some progresses in smart life. As Guangzhou the first city launching urban services through WeChat in China, Guangzhou Shanghai has the largest number of active users while Chongqing, the western city, is Chongqing lagging behind in creating smart life. 12 13 14 15 16

Source: Super Smart City, Deloitte Research

Scenarios and Potentials of AI’s Commercial Application in China Regions’ potentials of commercialization

AI is one technology sector where clusters in Beijing-Tianjin-Hebei Region, China has the opportunity to set rules. Pearl River Delta, Yangtze River Delta China has a huge application market and Sichuan and Chongqing in Western with a rapid growth of AI industry China and built regional industrial driven by commercialization. Moreover, parks with policy support. Going research institutions and companies forward, China needs to increase are accelerating their AI related attention and investments into long- researches and innovations. From term basic researches and further regional development perspective, improve technology capabilities and China has built several AI company industrial chains.

Figure 24. Ranking of smart city administration (by city)

1 16 14 12 10 8 6 4 2 0 Shenzhen Shanghai Hangzhou Beijing Guangzhou Chongqing

Source: Super Smart City, Deloitte Research

1

Office locations Beijing Harbin Shenyang 8/F Tower W2 Room 1618, Development Zone Mansion Unit 3605-3606, Forum 66 Office Tower 1 The Towers, Beijing Oriental Plaza 368 Changjiang Road No. 1-1 Qingnian Avenue 1 East Chang An Avenue Nangang District Shenhe District Beijing 100738, PRC Harbin 150090, PRC Shenyang 110063, PRC Tel: +86 10 8520 7788 Tel: +86 451 8586 0060 Tel: +86 24 6785 4068 Fax: +86 10 8518 1218 Fax: +86 451 8586 0056 Fax: +86 24 6785 4067

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Shanghai 30/F Bund Center 222 Yan An Road East Shanghai 200002, PRC Tel: +86 21 6141 8888 Fax: +86 21 6335 0003

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