The Economist Bilingual How to invest in artificial intelligence

How to invest in artificial intelligence

How to invest in AI

Private startups or public markets

Private start-ups are also incumbent tech giants

It has been a torrid 18 months for investors who bet on tech. SoftBank, a Japanese investment firm that epitomised the 2010s boom in venture capital for companies with rapid-growth ambitions, is still smarting from the shift to a world of higher interest rates and lower corporate valuations. But there is one area in which the firm, run by Son Masayoshi, its charismatic founder, wants to peek above the parapet: investments in artificial intelligence (ai).

The past 18 months have been extraordinarily difficult for investors betting on technology. In the venture capital boom in the second decade of the twenty-first century, Japanese investment company SoftBank was the one who stepped on the waves; However, the new trend of high interest rates and low company valuations has added many scars. But under the leadership of Chris Masayoshi's temperamental founder, Masayoshi Son, there is always an area of investment that makes the company forget the pain and can't help but want to favor it: artificial intelligence (AI).

The advances of generative-ai platforms, such as Chatgpt, have left just about every investor discussing what to make of the incipient industry, and which firms it might upturn. Mr Son sees parallels with the early period of the internet. Generative ai could provide a new pipeline of initial public offerings—and the foundation for the next generation of mega-cap tech firms.

The development of generative AI platforms such as ChatGPT has left almost all investors talking about what to expect from this rushing wave and which companies will be photographed on the sand. In Son's view, today's AI has similarities with the early Internet industry. Generative AI will create many new public companies, laying the foundation for the birth of the next generation of tech giants.

Investors face two questions. The first is which frontier technologies will make market leaders a fortune. That is difficult enough. The second, establishing whether the value will accrue to upstarts backed by venture capital or existing technology giants, is at least as tricky. Nobody knows if it is better to have the best chatbot or plenty of customers—having a head start in a whizzy new tech is not the same as being able to make money from it. Indeed, lots of the value of revolutionary innovation is often captured by existing giants.

Investors need to answer two questions. First, what cutting-edge technologies can make market leaders profitable? Second, figure out who will spend the value created by the new technology, whether it is a VC-backed startup or an existing tech giant? The first question is already difficult to answer, and the second question is even more difficult. Whether a large number of customers are better or the strongest chatbots are better, no one knows: getting ahead of the trendy technology space is not the same as profiting from it. In fact, the fruits of revolutionary innovation are often plucked by the giants of the guard.

Alphabet, Amazon and Meta are three of the seven largest listed companies in America, worth a combined $3.4trn. They were founded between 1994 and 2004, emerging at a time when internet technology was new and people were spending an increasing amount of time online. Alibaba, a Chinese e-commerce giant, is another similar example (SoftBank's early $20m stake in the company helped cement Mr Son's reputation as an investor). Spotting tech trends, and developing the best platforms, generated a gargantuan amount of value for early and even not-so-early investors. Legacy firms struggled to jump on the bandwagon.

Google's parent companies Alphabet, Amazon and Meta are three of the Big Seven U.S. stocks, with a combined market capitalization of $3.4 trillion. These companies were founded between 1994 and 2004, when Internet technology was emerging and people were spending more and more time surfing the Internet. The rise of Chinese e-commerce giant Alibaba has been much different (when Alibaba started, SoftBank invested $20 million, which made Son famous as an investor). Discover technology trends and develop the best platforms to make a lot of money for early and even later investors. Traditional companies have fallen behind in the chase of this trend.

Will the story be the same this time around? The insights of Clayton Christensen, a management guru who pioneered a theory of innovation just as the internet giants were bursting onto the scene, can provide a useful guide. Christensen noted that smaller companies often gain traction in low-end markets and entirely new ones, which the largest incumbents eschew. The incumbents focus on deploying new technology for their existing customers and lines of business. They are not incompetent or ignorant of technological progress. Instead, they follow the seemingly correct path from a profit-maximising perspective—until it is too late and they are fatally undermined.

Will a similar story be repeated? Management expert Clayton Christensen's insights are valuable. When Internet giants emerged, Christensen proposed a theory about innovation. He pointed out that small companies tend to focus on the low-end market and new tracks, while the established giants lack attention to these areas. These Shoucheng giants are committed to applying new technologies to existing business lines and serving existing customers. They are not incompetent or ignorant of technological progress. Instead, they follow the principle of profit maximization and follow the seemingly right path until it is too late and the fatal blow is reached.

Investors like Mr Son, excited about the future of startups that focus on ai, are implicitly presuming that a period of disruptive innovation is under way. But most of the recent excitement about generative-ai platforms has focused on their potential as a new technology to be deployed, not as companies which could open up brand new markets. In the case of other recent technological innovations, incumbents have won the day. Elad Gil, a venture capitalist, has noted that the value of previous advances in machine learning, the broader category of which generative ai is a part, have accrued almost entirely to incumbents. The early internet startups have benefited, as have Microsoft and chip firms like Nvidia and Micron. The earlier stages of machine learning produced no listed firms that might be considered the Amazon or Google of their niche.

Investors like Son are excited about the future of AI startups, and they vaguely feel that an era of disruptive innovation is coming. But lately, people are more excited about the potential of generative AI platforms as a new technology than about companies that can open up entirely new markets. In terms of other recent technological innovations, Shoucheng Giant has already won big. Elad Gil, a venture capitalist, points out that almost all of the output of previous machine learning fields (generative AI is a type of machine learning) has fallen into the pockets of the giants. The first movers in the Internet space have been profitable, as has Microsoft, as well as chip companies such as Nvidia and Micron. In the early days, machine learning didn't feed itself on Amazon or Google.

Christensen’s insights make clear that revolutionary innovation does not always end up being revolutionary in business terms. Yet existing tech firms are now spending enormous sums on ai, suggesting they should be well-placed if the tech does turn out to revolutionise business. It is possible an investment in a broad index fund tracking existing listed tech firms will end up outperforming the equivalent investment in private, strictly ai-focused startups.

Christensen's insight makes it clear that revolutionary innovation doesn't always lead to a business revolution. However, the Shoucheng tech giants have shown their determination to invest heavily in the AI industry: if this technology can really change the life of the existing business model, then they must have an absolute advantage. Rather than investing in private startups focused on the AI track, it may be better to scatter money in a broad index fund that tracks existing listed tech companies.

Theories about why innovation is sometimes disruptive and sometimes not are more often discussed by students of business and management than stockpickers. But the difference between the two possibilities is crucial in assessing whether the next generation of listed tech companies, with market capitalisations in the hundreds of billions of dollars, is to be found among private ai firms. As things stand, it looks more likely that the market value of the technology will end up as a new string to the bow of already giant tech firms.

Why innovation is sometimes disruptive and sometimes not is discussed more by business and management students than by stock pickers. However, the difference between the two possibilities is crucial if one is to assess whether the next generation of publicly traded tech companies with a market cap of hundreds of billions of dollars will be born among private AI companies. As things stand, AI technology will become the new jewel in the crown of the Shoucheng technology giant.