AI is an exciting growth area, but the investing opportunities are not always obvious. Here’s how to integrate this theme.
One of the most exciting themes in science, technology and economics today is the transformative potential of artificial intelligence (AI) and automation, but finding the best way to invest in this theme is not always obvious.
The emergence of intelligent machines, sometimes known as “the fourth industrial revolution,” has the power to disrupt many aspects of the business world. While investment in AI and machine learning has come in and out of vogue since first discussed in the 1950s, the current mix of economic forces could unleash a wave of spending.
New tax rules provide incentives for investment. In addition, higher wage costs are driving businesses to increase capital spending to improve efficiency in the competitive global economy. Another long-term motivation is demographic in nature. The developed world has a unique challenge, with many countries facing labor shortfalls. By 2050, the U.S. alone will likely face an 18-million worker shortfall.
A One Trillion Industry by 2050
If the AI industry grows at a compound annual rate of 15.4% (my current estimate), it could reach nearly $1 trillion in revenues by 2050, based on automation replacing the projected shortfall of 18 million U.S. workers. With Europe, Japan and China facing similar demographic deficits, that growth estimate is likely conservative.
No company or set of companies has advanced a single dominant AI technology. Many firms have focused on more narrowly defined task-oriented elements of machine learning, rather than on developing general artificial intelligence. Instead of a single AI application for all purposes, investors should expect multiple AIs, or algorithms, blended for specific cognitive and physical tasks.
How to Invest?
Commercializing AI technologies is still in the early stages. While many investors might begin their search among the companies that provide the actual automation services, they may find greater opportunities in firms that supply raw inputs required by AI algorithms or in the companies that use the core technologies to improve their primary business.
My advice for investors: Gain exposure to the technology across the AI ecosystem—upstream, core and downstream. Below is additional information on each segment:
Upstream: Companies supplying the raw material for core AI technologies include providers of processing power used in supercomputers and cloud data centers, as well as those with access to vast pools of data. Upstream opportunities also likely exist with companies that have expertise in data structuring (not just collecting data, but organizing it), as well as those with expertise in training the machines. AI also requires advanced sensors and control systems.
Not all companies in these sectors will benefit equally. Technology that could make one semiconductor company a leader in smart phones might not have the processing power for AI’s high-capacity needs.