Markets are getting AI right

Despite what you may have heard about an inflating market bubble, the US stock market isn’t rising. The once-hot S&P 500 has been cutting a herky-jerky path sideways for months. What happened? Back in May, the Magnificent Seven big tech stocks (Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, Tesla) surrendered the market leadership they’ve held for years. For a few weeks, a group of semiconductor stocks including Micron and Broadcom took up the baton, but recently they have faded, too. This week, tech stocks’ back-and-forth volatility has been especially intense, and a big AI-driven hedge fund, Situational Awareness, blew up.

It is tempting to say that markets are going mad, as they occasionally do. Amid the excitement of the AI revolution, tech stocks have become creatures of hype and price momentum. Now they are wobbling, and a panicked sell-off seems possible.

There is always plenty of irrationality in stock prices, and valuations are frighteningly high at the moment. But the recent changes in market leadership do not reflect the madness of crowds. Instead, the market is struggling — as rationally as could be hoped — to answer a hard question: what is the competitive structure of the AI industry, or indeed of an economy where AI is everywhere?

For investors, the competitive structure of industries, and the competitive position of companies within them, is by far the most important consideration.

Consider the current industrial moment. We might call it the “increasing returns era”, after a paper the economist W Brian Arthur wrote 30 years ago. Arthur argued that unlike traditional production industries, “knowledge industries” — we’d call them digital industries now — enjoy increasing returns to scale. They have high product development costs but near-zero unit costs, high switching costs and powerful network effects (that is, adding customers makes their products better). Arthur’s paper proved prescient, predicting the ever-larger geysers of cash that would…