AI Investment Trends From 10 Chinese VC Kingpins
What's the next opportunity for AI investment? 10 famous and successful investors share their opinions about AI investment trends.
Artificial intelligence (AI) started to become a hot-button area for Chinese investment institutes in around 2015, with 343 AI-related investment events happening and almost CNY 80 billion flowing to AI companies, according to EO Intelligence - one of China's technology and industry research institutes subordinate to EO Company.
However, some Chinese leading AI startups today secured their first financing in 2013 or 2014, when the majority of investors barely have knowledge about AI. So we explore which investment institutes and investors participated in AI investment at an early time.
We've discussed the top 10 of most active investors in China by the number of deals before. To get the whole content, please click on this link: Top 10 Most Active Investors in Chinese AI Startups, 2000 - 2019Q1. Based on it, we select 10 typical investors who have deep insights about the AI investment trends as below.
Idealistic market for AI-related technologies and applications development exists in China, considering two reasons: one is a bunch of AI scientists and engineers contribute a lot in China, especially in the field of speech recognition and image recognition; the other is China has sufficient data accumulated by smartphone, which is widely used in China, for algorithm training.
Internet giants like Alibaba, Tencent and Baidu, obtaining great business achievements partly benefited from the demographic dividend, stare on any of new business opportunities like AI, and keep pace with them by developing themselves of investment. However, most of their revenue is from 2C business domestically. So opportunities that AI startups grow to be great and large-scale enterprises, may exist in the area of 2B business and globalization.
The Chinese AI application development is very likely to surpass the U.S. in five years. In China, the amount of data in several fields is much larger than America: three times in mobile phone users, 10 times in food delivery, 50 times in mobile payment and 300 times in bicycle-sharing infrastructure.
With the support of the abundant data, several Chinese AI startups are standout in the world with extremely high valuations, which mostly build their technical barrier in computer vision, drone, speech recognition, TTS (Text To Speech) and machine translation.
Furthermore, three industries are probably firstly revolutionized by AI: Internet, finance and education. For the internet and finance industries, massive data is the treasure for algorithm training. For the education industry, around 50% of teachers’ works are repeated and fixed, which can be replaced by AI with little technical difficulty.
Among AI + education startups, great companies will probably appear in the next two or three years. There are expectedly two development stages in this field. For the first stage, all the content, offline teaching (or training) and management process will be digitalized. And for the second stage, personalized learning for individuals will be realized by big data, machine learning and biometrics. With these new technologies, the problem of inequality in educational resources will be solved, and the new teaching methods will come out.
When it comes to the AI startups that investors are optimistic to invest, the answer is different from many years ago. Startups that only verify their ability in specific AI technologies like facial recognition and AI chips design, can attract investment institutes indeed 10 years ago as people didn’t have much knowledge about AI. But it may don’t work today.
Many startups that focus on some specific products employed by computer vision are going through with a tough period on business development. What their clients need is systematic solutions rather than single products.
For each type of AI product, there always be a bunch of tech players competing with one another. How to distinguish the companies that are valuable to invest?
Our investment logics consist of three parts. The first part is to invest the companies that have connected with many industry partners and potential clients, as well as deep insights of industries. For instance, among all the startups that develop AI-assisted medical image diagnosis systems, we prefer investing the companies that keep good relationships with hospitals, clinics and other medical institutions. Besides, the team should have good knowledges on healthcare-related policies and regulations.
We believe these six AI application scenarios, as below, will bring prospective market with the valuation of over 100 billion dollars in the future.
The first is that AI is employed to upgrade business intelligence. At the very beginning, business intelligence is reflected in some software for enterprises, which provides tools to manage the working process. Nowadays, dozens of companies develop AI system to assist human workers to make better business decisions.
The second is fintech. Hundreds of Chinese startups build risk control systems based on big data and machine learning, which can help financial institutes for anti-fraud and anti-money laundering.
The third is AI + healthcare. The technical barriers are not so high, but the difficulty hides in the traditional medical industry. Interest entanglements always prevent newcomers from connecting with hospitals.
The fourth is AI + education. AI can raise the learning efficiency and effects by matching individualized learning plans for students.
The fifth is AI + manufacture. To produce customized and low-cost products within limited time can be realized today thanks to AI.
The last is autonomous driving, which is the future market that startups are paving the way to achieve it. It may take 10 to 15 years for mass production of the vehicles with level five autonomous driving ability.
Automation is the way out for enterprises to reduce labor costs, which is dramatically increasing continually at present and in the future. Technologies like AI and robotics have been proved that it can raise efficiency indeed.
Automobile manufacture is a typical industry with a high degree of automation. For example, in the factory of Xpeng Motors in Zhengzhou, 70% production flow is manipulated by machines.
Despite an isolated technology, AI will play an important role in various industries combining with IoT (Internet of Things) and big data. More smart front-end devices will emerge, and these technologies will be the fundamental components.
Because of the technical barriers, technology companies are popular for investment. However, it takes time and costs a lot to develop technology products. Investors should prepare to support companies in a long period.
Tech companies should pay more attention to their intellectual property (IP). All of the global tech kingpins have a great amount of IP, which can protect their technologies and brands from being copied and damaged.
For instance, IBM’s intellectual property contributes 60% of the total revenue. Chinese tech companies are lacking in the awareness of IP registration and protection, which will limit the expansion and development of business.