Tuesday, August 14

AI spurs greatest number of start-ups, 463% growth in VC funding

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AI shows the highest growth in number startups created, at 24.8% yoy since 2008,  while VC funding has popped 463% between 2012 and 2017, according to a recent report by Startup Genome, a research and advisory firm.

In financial services, the report highlighted areas of AI adoption such as: customer interactions, fraud detection, trading, and risk management.

But it looks like wealth management in particular is rapidly adopting these technologies. Robo-advisors are expected to have some $2.2 trillion in AuM by 2021, according to the report citing research from A.T. Kearney, a consulting firm.

The report pointed to US-based Betterment as an example: the automated investing service has some 300,000 clients and $12 billion in assets under management.

Source: Startup Genome

Tech v bank

One of the trends Startup Genome identified was that technology firms are encroaching on the financial space.

Large tech companies are tapping into their customer base and user data to provide banking services directly.

The top cases in the report were: Alipay, a payment service that got developed by Alibaba’s affiliate Ant Financial, which already boasts 520 million users; and Tencent’s WeChat-based Weixin Pay.

“In developing countries, large shares of the population are cut off from basic financial products—tech and telecoms companies are often first movers in terms of providing greater access to financial services for the 2.5 billion unbanked people,” the report said.

Source: Startup Genome

AI is accessible for startups

Major opportunities exist in the adjacent markets of big data and analytics, which is expected to grow to $203 billion in 2020 ($130.1 billion in 2016), said the report, citing IDC research.

The big boost to AI takeup is that the machine intelligence and big data stack are widely accessible to startups.

A lot of the fixed cost of developing underlying machine learning technologies has been paid by existing institutions—government, universities, engineering communities, and large tech companies, the report explained.

Meanwhile, the marginal costs of deploying these technologies have dropped, and that is a boon for startups.

“Even relatively small teams can deploy machine intelligence algorithms quickly and cheaply,” the report said.

Moreover, with open source tools for AI and big data like TensorFlow, scikit-learn, and Hadoop freely available, even the fixed cost of doing machine intelligence operations and managing large amounts of data has dropped dramatically.

Cloud services for low prices from players like Google Cloud and Amazon Web Services also play a
role in this.

“It is now easier than ever before for a startup to get up and running with AI technology,” the report said.

Financial AI startups at saturation point?

Citing PwC research, the report noted that global GDP could be up to 14% larger in 2030 as a result of AI— the equivalent of an additional $15.7 trillion, making it the biggest commercial opportunity in today’s economy.

The greatest gains from AI are likely to be in China (which will enjoy a boost of up to 26% larger GDP in 2030) and North America (potential 14% boost).

But financial services may not be where the future of AI startup growth will be.

According to the report, the biggest growth potential for emerging ecosystems will be in legacy industries that have yet to see widespread AI use: for example agriculture, manufacturing, and
healthcare.

The explosive growth in AI, big data & analytics investments in the past years competing in the “horizontal” (across all industry categories) make it incredibly hard for smaller ecosystems to compete across all categories, according to the report.

 

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