The staggering amount of money being spent on artificial intelligence will continue to be one of the most important themes for stock market investors this year, but serious questions hang over this spending.
Building out AI infrastructure such as data centers and power supplies is expected to cost more than US$5 trillion ($7.3 trillion) over the next few years, enough for AI spending to have a serious impact on economic growth, according to JPMorgan.
This investment frenzy has also contributed to huge increases in stock market valuations, prompting comparisons to Australia’s mining boom from the turn of the century and, of course, to the dot-com bubble of the late 1990s and early 2000s.
But all this spending raises fundamental questions for investors. Will the tech giants be able to recoup these huge expenditures with future profits?
This is important for almost everyone with superannuation. This is because the stock prices of AI-related companies are a major driver of the recent very healthy returns from global stock markets (particularly the US), which have supported super returns.
The bullish view on AI stocks is that this technology is truly a game-changer, and a small number of tech companies are well-positioned to dominate this market and extract huge profits. Nvidia is a superstar case. The company’s superior microchips are in high demand thanks to AI, significantly increasing profits and making the company one of the largest companies on the planet.
But a recent analysis of past technology booms and artificial intelligence by TCorp economists Brian Redican and Emily Perry makes a convincing case that while AI may be transformative, the road ahead for investors may be “a little rocky.”
Their insights provide an important balance to all the hype around AI that will no doubt continue this year.
First, they point out a fundamental lesson of economics. That is, the richer something is, the cheaper it is. So if AI models are really as great as some claim, all tech companies have an incentive to produce these models cheaper and more efficiently.
An example from history is the cost of providing lighting, where light bulbs have significantly reduced the cost of lighting. This is groundbreaking technology. Economists say lighting prices have been falling for a long time, and customers, not companies, are the winners.
The stock market was reminded of this risk in the AI sector this time last year, when Chinese startup Deep Seek shocked Wall Street with what appeared to be a much cheaper AI model that rivaled the world’s leading chatbots. More such conflicts are sure to occur in the coming years.
The second big lesson from past technology booms is the risk of overinvestment.
When spectacular new technology emerges, whether it’s trains, the internet, or AI, businesspeople are motivated to compete like crazy to gain market share. However, in doing so, you often end up investing more capital than you need.
There is a lively debate about whether that is exactly what is happening.
For example, JPMorgan analysts estimate that to reap the 10 percent return from expected AI investments between now and 2030, companies would need to earn an additional $650 billion a year “in perpetuity.” This is an astonishing number. They estimate that this equates to an additional $34.72 per month from everyone who owns an iPhone, and an additional $180 per month from every Netflix subscriber.
Whenever physical assets such as data centers are built quickly, there is also a risk that competition between companies, such as mining companies bidding on labor and materials, will drive up costs.
Sonya Sawtell Rixon, chief investment officer at HESTA, says a clear example of such a constraint on the AI boom is data center power demands. She points out that in the U.S., the AI boom has led to significant increases in electricity prices in some areas, sparking backlash from local communities.
“There have been significant increases in retail home prices and we are starting to see some activity with the electricity regulator,” she says.
A third lesson from past technology booms is that the winners are not necessarily those who take the lead in building new infrastructure.
Trent Masters, a portfolio manager at Alfinity, said the big winners of the 2000s technology boom weren’t the carriers that laid tons of cable to build the internet, but the ones that created something new on top of it. Examples include Google’s search, Amazon’s online commerce system, and Apple’s iPhone. He predicts something similar may happen with AI, but he doesn’t yet know what the use cases will be.
“I think the pure model will eventually become a commodity, but the applications that can be built on top of it are what will ultimately create value,” he says. The final point is that investment booms, no matter how strong they are, always ebb and flow.
There are many plausible reasons why the breakneck pace of AI investment could slow, whether it’s a lack of power or water for data centers, or simply because technology companies decide they have enough data centers. If this happens, you have to imagine that some of the excitement about AI in the market will explode.
Of course, it’s one thing to point out that the AI boom has many risks, but if you’re an investor, how do you deal with that?
For large investment firms like super funds, missing out on AI’s huge success is not really an option. If you don’t invest in an AI player, you risk falling behind the market and providing below-average returns to your members.
HESTA’s Sawtelle Rickson said AI-related investments now account for about 20% of global stock markets (mostly in the US), and that the US tech giants known as the Magnificent Seven have made annual returns of about 60% over the past three years. Although the fund’s AI exposure is slightly lower than the public market average, the growth in AI has become so large that it has become “more of a systemic risk” that requires attention and caution in portfolios, he said.
Whether you are a large investor like Sawtell Rixons HESTA or a humble individual investor, it is impossible to know how AI’s huge success in the stock market will end.
However, given the eye-popping amounts of money being invested, history and economics suggest that it is not all plain sailing.
Or, as a J.P. Morgan analyst puts it, “Even if all goes well, given the amount of capital involved and the nature of all the winners and parts of the AI ecosystem, there will[continue to be]spectacular winners, and there will probably be equally spectacular losers.”
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Clancy Yates is deputy business editor. He covers banking and financial services and was previously the national business correspondent in the Canberra bureau.connect via Twitter or Email.
