THE ECONOMIST: What if the AI bubble bursts and trillion-dollar tech valuations come crashing down?

Since the release of ChatGPT in 2022, the value of America’s stockmarket has risen by $US21 trillion ($33t). Just ten firms — including Amazon, Broadcom, Meta and Nvidia — account for 55 per cent of the rise. All are riding high on enthusiasm for artificial intelligence, and they are not the only ones.

In the first half of the year an IT investment boom accounted for all America’s GDP growth; in the year to date a third of the West’s venture-capital dollars have gone to AI firms.

The market is so hot because many believe AI will transform the economy. Investors at Sequoia Capital recently argued it will be “as big if not bigger than the Industrial Revolution”.

In a podcast last year, Gavin Baker of Atreides Management, an asset manager, argued that AI luminaries are not just after the “tens of trillions or hundreds of trillions of value” the tech could add to their firms — they are “in a race to create a Digital God”. That belief would justify any amount of spending.

Will AI really become godlike? Perhaps, but a recent report by UBS, a bank, finds that revenue generation to date “has been disappointing”. By our reckoning, the total revenue from the tech accruing to the West’s leading AI firms is currently $US50 billion ($79b) a year.

Although such revenues are growing fast, they are still less than 2 per cent of the $US2.9 trillion investment in new data centres globally that Morgan Stanley, another bank, forecasts between 2025 and 2028 — a figure which excludes energy costs.

Meanwhile, the extent to which revenues will translate into profits is murky.

A recent study by researchers at the Massachusetts Institute of Technology concludes that 95 per cent of organisations are getting “zero return” from investments in generative AI.

No wonder more and more people are asking whether investment in AI has become irrationally exuberant.

“Global Crossing is reborn,” argues Praetorian Capital, a hedge fund, referring to the company that hugely overbuilt cross-continental fibres in the dotcom era.

“Valuations in the space are indeed flashing red and leave little room for cash-flow disappointments,” according to another report by UBS. Torsten Slok of Apollo, a private-investment firm, has noted that AI stocks are more richly valued than dotcom stocks in 1999.

Even Sam Altman, boss of OpenAI and one of AI’s most fervent evangelists, has sounded the alarm.

“Are we in a phase where investors as a whole are overexcited about AI? My opinion is yes.”

Mr Altman and his ilk also make a broader point: that bubbles are normal when new technologies emerge. “Tech enthusiasm always runs ahead of tech realities,” according to Michael Parekh, a former analyst at Goldman Sachs, another bank.

“History tells us that periods of major technological innovation are often accompanied by speculative bubbles as investors overreact to genuine advances in productivity,” reads a study published in 2008 by the Federal Reserve Bank of San Francisco.

An academic study in 2018, which examined 51 innovations from between 1825 and 2000, found that 37 were accompanied by bubbles.

Most did not prevent the technologies that inflated them from sweeping the world. In Britain there were two big railway bubbles, in the 1840s and the 1860s; the country nevertheless has lots of railways.

American investors went loopy over electric-light companies in the late 1800s and lost a lot of money, but today Americans still want to see at night. AI might well follow suit. Bubbles come and go, but Digital God would be eternal.

A crash would still have big consequences. One lesson from history is that, when tech bubbles burst, leading firms often give way to upstarts.

“The biggest and most successful lighting companies all experienced a change of control when cashflow became an issue,” wrote Alasdair Nairn in Engines That Move Markets, a history of the late 19th century.

Many firms that dominated the early days of railways, the telegraph and the telephone were also quickly supplanted.

Who now remembers Vulcatron, from America’s electronics bubble of the 1960s, or Corning, a household name during the dotcom boom? It will be a miracle if, in a decade or so, all of the “magnificent seven” listed tech firms, and the biggest AI startups, still exist.

For society at large, the consequences of tech crashes vary enormously. The bursting of America’s electronics bubble of the 1960s barely grazed the economy; the bursting of its railway bubble in the 1870s resulted in the longest slump in American history.

Our analysis of past technological bubbles finds that four factors matter most: the spark, what kick-starts the boom, the nature of the capital invested and who bears the losses.

Take the spark first. In their book Boom and Bust, William Quinn and John Turner, two economic historians, distinguish between political and technological sparks.

Bubbles inflated by politicians — by changing regulations or taxes, say — cause more damage than those inflated by new technologies. Political sparks encourage investors to move as a herd.

Lenient property taxes, low interest rates and financial liberalisation led to a gargantuan asset bubble in Japan in the late 1980s. For decades after it burst, Japan’s economy remained sluggish. By contrast, technological sparks do less damage: no long slump followed the dotcom mania.

The size and durability of capital investment is also important. In 1840s Britain, businesspeople went truly bananas for railroads. From 1844 to 1847 investment rose from 5 per cent to 13 per cent of British GDP. Investment fell by half when the bubble burst — and British unemployment doubled.

Then there is the manner in which capital is deployed. Much of the capex by Japanese electronics firms in the 1980s ultimately served no useful function.

By contrast, bubbles can benefit society if they create enduring assets. The railway mania built the backbone of England’s rail network, even if profitability took a long time to arrive.

The tens of millions of miles of fibre-optic cable laid across America during the late 1990s was far more than the internet needed at the time. But in recent years it has facilitated data-intensive services such as streaming and video calls.

The final factor determining a crash’s severity is who bears the losses. When lots of individual investors each lose a little, the economic damage is limited.

This is what happened after America’s electronics and dotcom booms. Amid the British railway bust of the 1860s, by contrast, losses were concentrated among banks, which ended up with lots of bad loans. They then cut new lending, deepening the downturn.

Where might AI sit in this rogue’s gallery? To judge this, we picked ten historical bubbles and assessed them on factors including spark, cumulative capex, capex durability and investor group.

By our admittedly rough-and-ready reckoning, the potential AI bubble lags behind only the three gigantic railway busts of the 19th century.

The spark of the AI boom was technological, but politicians are adding fuel to the fire. A foundational paper titled “Attention is all you need” was published in 2017. OpenAI released ChatGPT in 2022.

These developments had nothing to do with politics. Lately, however, governments have begun to support their AI champions.

America’s, under Donald Trump, has promised to trim regulation and help provide the infrastructure and workers needed to achieve “global dominance”. Gulf countries’ governments are pouring trillions of dollars into AI investment.

The nature of AI capex is also worrying. For now, the splurge looks fairly modest by historical standards. According to our most generous estimate, American AI firms have invested 3-4 per cent of current American GDP over the past four years.

British railway investment during the 1840s was around 15-20 per cent of GDP. But if forecasts for data-centre construction are correct, that will change.

What is more, an unusually large share of capital investment is being devoted to assets that depreciate quickly. Nvidia’s cutting-edge chips will look clunky in a few years’ time. We estimate that the average American tech firm’s assets have a shelf-life of just nine years, compared with 15 for telecoms assets in the 1990s.

Last is the question of who would bear the losses from a crash. Almost half the forthcoming $US2.9t in data-centre capex, Morgan Stanley reckons, will come from giant tech firms’ cashflows.

These companies can borrow a lot more to fund their investments if they wish, since they have little existing debt. They make up about a fifth of the S&P 500 index’s market value, but as borrowers, they account for only 2 per cent of the investment-grade bond market. Their balance sheets look rock solid.

The other big investors are likely to be insurance companies, pension schemes, sovereign-wealth funds and rich families. In August PIMCO, a big bond investor, and Blue Owl, a private-credit firm, funded Meta’s $US29b data-centre expansion in Louisiana.

If the value of all AI investments went to zero such investors would suffer, but would be unlikely to bring down the financial system. Since American banks are not financing much of the AI boom themselves, their exposure to it is mostly indirect, through such non-bank lenders.

In another respect, though, America’s economy is in a historically unique position: individuals’ exposure to the stockmarket has never been so high. Ownership of stocks accounts for about 30 per cent of the net worth of American households, compared with 26 per cent in early 2000, at the peak of the dotcom bubble.

Such ownership is concentrated among the rich, whose spending has powered economic growth of late. According to Oxford Economics, a consultancy, consumer spending rises and falls by about 14 cents for every dollar change in financial wealth.

These changes, in turn, depend more than ever on a few giant firms whose prospects will be shaped by AI.

Over the past year, the promise of technological revolution has been a welcome distraction from the darker reality of America’s shaky institutions, rising trade barriers and vast government borrowing. Should Digital God fail to arrive, the fall will be brutal.