If the AI Bubble Bursts, a Double Whammy? Fears a US Downturn Could Speed Up Worker Replacement

What if the investment wave around artificial intelligence (AI) suddenly bursts like a bubble? And if that bust triggers a recession, what if employers then start replacing people with AI even faster? An analysis in NPR’s Planet Money newsletter has raised this “double whammy” fear for the American economy.

The analysis says two strands of economic research give reason to take the fear seriously. One concerns the history of financial bubbles. The other concerns a surprising relationship between recessions and automation, when businesses use technology to do tasks previously done by humans.

To explain bubbles, it draws on economist Charles Kindleberger’s influential 1978 book “Manias, Panics, and Crashes: A History of Financial Crises”. Building on the theoretical work of economist Hyman Minsky, Kindleberger saw a recurring pattern across centuries of economic history.

In that pattern, a bubble often starts with some big potential change to the economy — a revolutionary new technology, for example, promising to transform industries and create enormous wealth. Investors have good reason to be excited, but they get overly excited. During the upswing they bet huge sums expecting the sky to be the limit, and they pile up debt to make even bigger bets. That debt can become a ticking time bomb.

When reality sets in, asset prices fall but the debts remain. Borrowers struggle to repay, lenders suffer losses, and a market crash can spiral into a financial crisis and a painful recession. The analysis stresses that a technology can truly be revolutionary yet still fuel a bubble that ends in a financial crash.

The railroads are offered as an example. The collapse of the railroad bubble triggered the “Panic of 1873”, and the ensuing economic turmoil helped foment a populist uprising and the first major immigration crackdown in American history, the analysis notes.

On the present situation, it says AI is now basically propping up the US stock market. An analysis from J.P. Morgan earlier this month found that just 42 AI-related companies accounted for around two-thirds of the S&P 500’s stock price gains since early 2024. Meanwhile, AI companies are borrowing hundreds of billions of dollars to finance data centers and the energy infrastructure to power them.

But the analysis makes clear that none of this proves we are witnessing a bubble or that the debt is a ticking time bomb for the financial system. The bursting of the dot-com bubble ushered in a relatively mild recession; debt played a smaller role in that boom, limiting the financial fallout, and its collapse did not trigger a systemic crisis like the one that followed the housing bust around 2008.

Even without a financial crisis, there could be a painful reckoning. Will all these companies ultimately make enough money to justify their borrowing and spending, and will each survive? Technology analyst Benedict Evans has warned that fierce competition between companies offering similarly capable AI models could drive down the prices they can charge and leave little room for profit — even as they spend enormous amounts developing and running the models.

Then comes the second whammy. Several studies suggest recessions can be the very moment businesses turn to new technologies to replace workers. A study by economists Nir Jaimovich and Henry Siu found that jobs vulnerable to previous waves of automation saw most of their decline around recessions: between 1990 and 2017, 88% of the decline in the share of Americans employed in such jobs occurred during recessions or in the months immediately before or after them.

Here lies the analysis’s most unsettling irony: fierce price competition could keep AI companies from delivering the profits investors expect, while making their technology cheaper for other businesses to use to replace workers. If an AI bust triggers a recession, that downturn could accelerate worker replacement — investors could lose their money, and workers could still lose their jobs.

Much, of course, remains unknown — whether AI will deliver enough profits to justify the borrowing and spending, whether a bust would trigger a painful recession, or whether the automation patterns of past recessions will repeat with AI. A downturn could also leave businesses with less money to invest in AI, and AI could still prove more useful for making workers more productive than for replacing them outright.

The analysis also mentions policies that can limit the damage, from unemployment insurance to proposals, backed by figures such as Bill Gates, to tax AI and robots — making it more economical to keep employing humans while generating revenue to strengthen the safety net. For now, the “double whammy” is only a fear, not a reality — but it is not a fear that can be taken lightly either.