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INSIGHTS / THE BIG PICTURE

From state to BAT, China backs startups for global AI dominance

China · Jul 12, 2018 · By Wang Xiao'e

Finance, automobile, retail and healthcare seen to lead China’s advances and gains in AI, as part of a RMB 10 trillion economy by 2030

The world’s most populous nation is in the race to also become its “smartest.” 

A huge population; top-notch IT talent; diverse industries; and a thriving mix of e-commerce, mobile payments and social networks all feed into a massive pool of data for China to become an AI heavyweight. Such deep resources make it easy for China-based AI companies to invent and test new concepts and products.

China expects innovation in artificial intelligence to transform local industries worth a total of RMB 10 trillion (US$1.5 trillion) by 2030, according to the 2017 report China AI Innovation and Application. Among them, finance, automobile, retail and healthcare would lead the growth, enjoying forecast profits of around RMB 600 billion, 500 billion, 420 billion and 400 billion, respectively, through reduced costs and increased benefits from AI adoption.

Such prospects are reflected in the levels of investment achieved so far in 2018, a record-breaking year. In May, Ubtech raked in US$820 million in Series C funding led by Tencent. Ubtech, with a valuation of US$5 billion, is now the highest-valued AI startup in the world, breaking the record set by another Chinese firm SenseTime (worth US$4.5 billion) – just a month prior.  

President Xi Jinping has made ending poverty in China by 2020 one of the key government goals, and tech has proven to be a job creator. While many are decrying the jobs AI will likely take away – e.g., service positions in the food and retail industries – it has yet to be seen what jobs AI can create, directly or indirectly through boosting the economy.

PWC has forecast AI will lift global GDP by about US$15.7 trillion in 2030, or 14% from 2017. The consultancy also expects China to lead the world in productivity gains from AI, adding 26% to GDP in 2030.

Edited by Wang Xinlei

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