Netease Technology News July 2 news, according to foreign media reports, the current artificial intelligence is one of the hottest areas of venture capital, including artificial intelligence algorithms, related machine learning systems, neural networks and back-end process processing. As the CEO of Nvidia recently said, "Software is occupying the world, and artificial intelligence is occupying software."
AI investment has always been hot
Investors in the field of artificial intelligence have increased from US$3.2 billion in 2014 to US$9.5 billion in the first five months of 2017. Among them, the number of investments has almost doubled since 2015. The total investment this year has reached more than 1,200 times. The famous market consulting company Frost & Sullivan made artificial intelligence the most popular investment field in 2017.
Artificial intelligence mergers and acquisitions are "small-scale" mergers and acquisitions
Investors enter a field for more returns. However, the opposite is true in the field of artificial intelligence. A successful artificial intelligence company often sells for less than $50 million. This may be very beneficial to founders or small-scale angel investors, but it is a big deal for big venture capitalists.
Of the 70 M&A deals that have occurred in the field of artificial intelligence since 2012, 75% are selling for less than $50 million. These transactions are usually "acquisition acquisitions," and the transaction itself is simply to gain the company's talent rather than business performance. Among them, there are few deals that total more than 200 million U.S. dollars.
An artificial intelligence company with 10 to 20 people sells for 25 to 50 million US dollars
A typical transaction process of an artificial intelligence company is as follows: The company has 1 to 2 people as the core, and it has made practical progress in key use cases such as voice recognition, visual tracking, fraud detection, or consumer behavior analysis. A small number of well-known customers are recruited. The funds are less than 10 million U.S. dollars, and most of them are even less than 5 million U.S. dollars. Then attracted to a major buyer. This type of artificial intelligence company is often valued according to the value of each engineer rather than the performance of the company. The average company's price per employee is approximately $2.5 million.
High-value M&A target is not too much
Another problem faced by venture capital in the field of artificial intelligence is that even if the market value exceeds 100 million U.S. dollars, artificial intelligence companies generally do not need to raise too much money. For example, Argo, with a market value of 1 billion U.S. dollars, had only 20 employees when Ford acquired. Research from PitchBook shows that among the top 10 most valuable artificial intelligence companies, the average raised funds are only 15 to 25 million US dollars. In fact, there are only 1 to 2 venture capital spaces in each transaction.
Of course, the field of artificial intelligence is not without big companies. For example, Palantir has a market value of US$10 billion and has raised more than US$500 million. However, the artificial intelligence field does not have a large number of venture capital investments to create a typical case of a billion-dollar unicorn.
In fact, venture capital will have the opposite effect.
Once there are several venture capital companies entering, then such an artificial intelligence company will not be able to acquire about 50 million US dollars in mergers and acquisitions, but only by expanding the company's scale, expanding its products and services to achieve a higher valuation, so that the risk Investment companies can get the required return. Here are the reasons why we think counterproductive:
The value of most artificial intelligence companies depends on two or three core experts who have mastered key technologies. The growth of the company's scale does not have much benefit in improving its own level. These people are usually highly technical college professors or industry experts. With the expansion of the company's scale, it will inevitably become more bureaucratic, which will also make the core technicians lose interest in development. In other words, the larger the size of an artificial intelligence company, the easier it is to lose core technical tasks. On the other hand, how do interested big buyers react to this problem after the merger? They learned to isolate these technical experts from the bureaucratic style of the company. But when a company is still just a fast-growing startup, it's harder for the founder.
In addition, many buyers believe that the acquisition, sales, marketing, and business development capabilities of the acquired company are all negative values. They already have enough business talent and want technical teams and core algorithms and just property rights. Therefore, they are not willing to pay extra for other extra content.
After the venture capital enters, the buyer must consider this bet in the merger and acquisition, which will bring more risks to the buyer.
For venture capital companies, this type of investment often does not make any sense. The acquisition of an artificial intelligence company means getting a small profit in a short time, but it is not a long-term return. What venture capital companies want is, in turn, to invest more money in more than five years and earn ten times the profits. This is the difference between Blackjack and Go. The acquisition of artificial intelligence is the former, and venture capital companies are paying attention to the latter.
For technology founders, raising funds does not mean profitable. For example, it raised 5 million U.S. dollars and sold the company 50 million U.S. dollars. This is more cost-effective than raising $25 million and then selling the company for $100 million.
In this regard, the best way for an AI founder is to divert attention away from raised funds, focus on solving technical problems, and wait for the bell to ring. (晗冰)
Guangzhou Jiaqi International Trade Co., Ltd , https://www.make-case.com