Anyone who invests in the new new thing must answer two questions: First, how much value will this innovation create? And second, who will capture it? Information and communication technology (ICT) was a revolution whose value was captured by startups and led to thousands of newly rich founders, employees, and investors. In contrast, shipping containerization was a revolution whose value was spread so thin that in the end, it made only a single founder temporarily rich and only a single investor a little bit richer.

Is generative AI more like the former or the latter? Will it be the basis of many future industrial fortunes, or a net loser for the investment community as a whole, with a few zero-sum winners here and there?

There are ways to make money investing in the fruits of AI, but they will depend on assuming the latter—that it is once again a less propitious time for inventors and investors, that AI model builders and application companies will eventually compete each other into an oligopoly, and that the gains from AI will accrue not to its builders but to customers. A lot of the money pouring into AI is therefore being invested in the wrong places, and aside from a couple of lucky early investors, those who make money will be the ones with the foresight to get out early.

You couldn’t have known in the mid-1970s that the PC (and PC-like products, such as ATMs, POS terminals, smartphones, etc.) would revolutionize everything. While Steve Jobs was telling investors that every household would someday have a personal computer (a wild underestimate, as it turned out), others questioned the need for personal computers at all.

When a technological revolution changes everything, it takes a huge amount of innovation, investment, storytelling, time, and plain old work. It also sucks up all the money and talent available.

In the entire year of 1976, when Apple Computer was founded, the NYT mentioned PCs only four times.

No one took note of personal computers in the 1970s. In 2025, AI is all we seem to talk about.

If AI had started a new wave, there would have been an extended period of uncertainty and experimentation. There would have been a population of early adopters experimenting with their own models. When thousands or millions of tinkerers use the tech to solve problems in entirely new ways, its uses proliferate. But because they are using models owned by the big AI companies, their ability to fully experiment is limited to what’s allowed by the incumbents, who have no desire to permit an extended challenge to the status quo.

In 2025, machines that think better than previous machines are easy for people to understand.

While it’s too late to invest in the model companies, the profusion of those using the models to solve specific problems is ongoing: Perplexity, InflectionAI, Writer, Abridge, and a hundred others. But if any of these become very valuable, the model companies will take their earnings, either through discriminatory pricing or vertical integration. Success, in other words, will mean defeat—always a bad thesis. At some point, model companies and app companies will converge: There will simply be AI companies, and only a few of them.

Being an entrepreneur will be a fabulous proposition in these sectors. Being an investor will be harder. Companies will not need much private capital—IKEA never needed to raise risk capital, and Costco raised only one round in 1983 before going public in 1985—because implementing cost-savings technology is not capital intensive. As with containerization, there will be a long lag between technology trigger and the best investments. The opportunities will be later.

Knowledge-intensive services will get cheaper, allowing consumers to buy more of them, while services that require person-to-person interaction will get more expensive, taking up a greater percentage of household spending. This points to obvious opportunities in both. But the big news is that most of the new value created by AI will be captured by consumers, who should see a wider variety of knowledge-intensive goods at reasonable prices, and wider and more affordable access to services like medical care, education, and advice.

"The lessons learned from investing in tech over the last 50 years are not the right ones to apply now. The way to invest in AI is to think through the implications of knowledge workers becoming more efficient, to imagine what markets this efficiency unlocks, and to invest in those. For decades, the way to make money was to bet on what the new thing was. Now, you have to bet on the opportunities it opens up."