今天的日经亚洲论坛Nikkei Asian Review 刊登Nina Xiang的丽文，说：
In their rush to go public, China's AI unicorns reveal a fatal
Investor should be wary, as risk factors listed in IPO prospectuses
by Nina Xiang
December 1, 2020 05:00 JST.
Nina Xiang is the founder of China Money Network, a media platform
tracking China's venture and tech sectors.
In 10 years no one will remember the names of China's artificial
intelligence unicorns. While many aspects of the coming AI
revolution remain unpredictable, one thing is clear: no AI company
will emerge as a Big Tech brand.
While the internet era of the 2000s, and the mobile internet era of
the 2010s, created the Chinese tech giants of today, such as Baidu,
up Holding, and Tencent Holdings, collectively referred to as BAT,
as well as Toutiao, Meituan-Dianping, Didi-Chuxing, together known
as TMD, the AI era is unlikely to produce anything like that by
comparison -- even if overly zealous investors have nursed over a
dozen AI unicorns in China worth tens of billions in total.
That is partly because AI businesses are not consumer-facing.
Because they are mostly providers of back end hardware and software
to other businesses, or, more critically, to governments, AI
business will not become giant platform companies servicing
billions of users.
More importantly, as these highly valued startups rush to list
publicly, their fatal flaw is laid bare: they simply do not -- and
probably will not ever -- have a sustainable long-term business
model. All those who have disclosed financials in an IPO
prospectus, including Megvii, Shanghai Yitu Internet Technology,
Cambricon Technologies and Beijing Unisound Information Technology,
are deeply in the red to the scale of billions of yuan.
While AI businesses must invest heavily in research and are still
in the early days of commercialization, suffering large losses is
understandable. What is more concerning is their reliance on
government contracts or a few big customers.
Take Megvii, where around 73% of its total revenue during the first
half of 2019 came from city IoT solutions -- in other words, smart
city initiatives paid for by government. For Yitu, the majority of
its revenues also came from governments, with its top five
customers accounting for 62% of total revenue in the first half of
2020. This type of concentration is probably true right across
China's AI unicorn herd.
Whether AI companies can continue to gain ground in this
to-government market is questionable. Compared to traditional
surveillance camera makers and public security providers like
Hikvision and Dahua Technology, AI unicorns like Megvii and
SenseTime are not the ones with the deepest moats. The competitive
edge enjoyed by most AI companies is also being eroded as the likes
of Hikvision and Dahua improve their own AI algorithms to go with
their rather comprehensive product suites.
Another core dilemma for China's AI unicorns is whether it makes
sense for their big clients to outsource such a critical business
function. Should a big bank contract out and hand over its most
sensitive data to an outside AI company for a mission-critical
initiative? Would it really be better for a big retailer to share
its proprietary data with an industry outsider in exchange for
algorithms that it could probably develop on its own?
In very few cases, the answer may be yes. But as the technological
barrier to once inaccessible AI algorithms crumbles, the scale will
tilt against AI companies, especially when the data is proprietary
and in the hands of owners of traditional businesses.
This raises yet another challenge for AI unicorns. As the so-called
intelligence 'enablers' to various industries from financial
services and health care, to retail and education, they need to
develop expertise across vastly different sectors. If that is not
hard enough, having to customize products to different industries
makes it harder to achieve economies of scale. With all the AI
unicorns seeking to expand in the same industry verticals, that
will only further intensify competition.
This does not mean the coming AI revolution will not thoroughly
transform our businesses and our lives, or that there will not be
some sizable AI companies that will go on to become large and
profitable businesses. Automated logistics and robotic delivery
services are most likely to see such success stories.
But it also remains to be seen how big a role these AI unicorns --
born out of university labs amid a renewed wave of public fantasy
following AlphaGo's landmark success in 2016 -- will play. Or, for
how long -- if one believes such enabler roles to be transitional.
What is more likely is that some of the vertical enabler AI
companies will end up being acquired by their traditional business
In the end, China's AI unicorns and their investors, clients, and
end-users may all benefit from the third AI wave as AI makes our
lives smarter. But at the same time, retail investors need to be
extra careful buying these unicorns' shares, as all the risk
factors listed in those IPO prospectus are very real.