When the AI bubble bursts...

About a year ago, the idea that speculative investment has created an “AI bubble” began to take hold and soon became conventional wisdom. Since bubbles always burst, the fear now is that time is running out for this one.
The interplay between AI deployment and financial speculation can be analysed independently of the debate between doomers and accelerationists over whether generative AI will liquidate humanity or usher in a golden age of abundance. In fact, the boom and the bubble could both be over before that debate is resolved.
In a recent blog post, Noah Smith examined how massive investments in AI infrastructure and training are reshaping the relationship between the real economy and the financial system. As hyperscalers increasingly rely on borrowed money to finance those investments, he observed, they will have to generate ever larger revenues and cash flows to justify them.
That makes this a good time to look beyond the current AI boom and adopt a longer-term perspective on financial bubbles. In my 2018 book Doing Capitalism in the Innovation Economy, I propose a framework for understanding the dynamics that drive bubbles and their potential consequences.
The first “law” of bubbles is that any tradable asset can become the object of speculation. Speculative demand can drive the valuation of any asset to levels decoupled from the cash flows — past, present, or prospective — that represent its fundamental value. This phenomenon can be traced to the dynamics of financial markets populated by investors who do not know and cannot know the future. Recognising that no one else can know, either, market participants watch what others do and follow suit. Each investor rationally tries to anticipate their peers’ behaviour, producing the collective exercise in irrationality we call a bubble.
John Maynard Keynes famously captured this dynamic in his metaphor of the beauty contest: “Professional investment may be likened to those newspaper competitions in which the competitors have to pick out the six prettiest faces from a hundred photographs, the prize being awarded to the competitor whose choice most nearly corresponds to the average preferences of the competitors as a whole; so that each competitor has to pick, not those faces which he himself finds prettiest, but those which he thinks likeliest to catch the fancy of the other competitors, all of whom are looking at the problem from the same point of view.”
Neither regulatory changes nor technological advances have altered this basic dynamic. But while bubbles are ubiquitous, not all of them are the same. I have found it useful to distinguish bubbles along two dimensions, illustrated by the figure below.
The first dimension is the focus of speculation. Can the assets whose deployment is being financed by speculative investment expand the economy’s productive capacity? This was the case with the 19th-century railway manias, the bull market of the “Roaring Twenties” that financed the buildout of the US electricity grid, and, most recently, the dot-com bubble that funded the Internet’s global deployment at the end of the 20th century.
By contrast, the Dutch tulip bubble of the 1630s revolved around tulip bulbs, which were decidedly unproductive. After some 15 years of experimentation and hype, much the same can be said of crypto. Real estate, both commercial and residential, has also repeatedly been the subject of speculative booms. The great credit boom of 2005-08, amplified by modern mathematical finance through seemingly endless varieties of derivative credit structures, is the most recent example of a thoroughly unproductive bubble.
Productive bubbles are just as certain to burst as unproductive ones. Sooner or later, economic fundamentals assert themselves. As the cash flows implicit in asset valuations fail to materialise, more and more investors recognise that the valuations cannot be sustained until a tipping point is reached. The collapse may be triggered by a high-profile failure, like that of Jay Cooke & Co in New York in 1873. Or it may follow a less dramatic but ultimately decisive conviction that “enough is enough,” as happened in the spring of 2000. Either way, the bubble bursts.
The second dimension of bubbles is the locus of speculation, which becomes especially important when bubbles pop. Was the bubble financed principally through the relatively unleveraged equity and high-yield bond markets? Or did the speculation penetrate the core banking system that finances the working capital of businesses and the real estate that accounts for much of the net worth of workers and consumers?
In a 2015 paper, Òscar Jordà, Moritz Schularick, and Alan M Taylor examined 140 years of historical financial data, concluding that “what makes bubbles dangerous is the role of credit.” Their findings are consistent with the distinction highlighted by former Federal Reserve Governor Frederic Mishkin and other policymakers in the aftermath of the 2008 financial crisis. Whereas “pure, unleveraged ‘irrational exuberance’ bubbles” may “pose a limited threat to financial stability or the macroeconomic outlook,” rising asset prices and increasing leverage reinforce one another during “credit boom bubbles.”
When credit boom bubbles burst, Mishkin explained, “the resulting deleveraging depresses business and household spending, which weakens economic activity and increases macroeconomic risk in credit markets.” This was very much the story of the 2008 crisis and the Great Recession. Indeed, when the dot-com bubble burst in 2000, WorldCom and Global Crossing — the two leading builders of the fibre-optic networks that carried Internet traffic — went bankrupt, and WorldCom’s senior executives were even jailed for fraud. But these investments in infrastructure had been funded by junk bonds, not bank credit. The economic consequences were thus limited and could be managed through conventional monetary policy.