The AI Boom’s Hidden Risk to the Economy

A Microsoft data center is under construction in Mount Pleasant, Wis., where the first phase is slated for completion in 2026.

In the past two weeks one big tech company after another reported blowout earnings amid a wholesale embrace of artificial intelligence.

Look a little closer, and a more unsettling side to the AI boom emerges. All the spending on chips, data centers and other AI infrastructure is draining American corporations of cash.

This underscores the hidden risks from the AI boom. No one doubts its potential to raise growth and productivity in the long run. But financing that boom is straining the companies and capital markets.

The AI boom props up growth

Since the first quarter of 2023, investment in information processing equipment has expanded 23%, after inflation, while total gross domestic product has expanded just 6%. In the first half of the year, information processing investment contributed more than half the sluggish 1.2% overall growth rate. In effect, AI spending propped up the economy while consumer spending stagnated.

Much of that investment consists of the graphics-processing units, memory chips, servers, and networking gear to train and run the large language models at the heart of the boom. And all that computing power needs buildings, land and power generation.

This is transforming big tech’s business models.

For years, investors loved those models because they were “asset-light.” They earned their profits on intangible assets such as intellectual property, software, and digital platforms with “network effects.” Users flocked to Facebook, Google, the iPhone, and Windows because other users did. Adding revenue required little in the way of more buildings and equipment, making them cash-generating machines.

This can be seen in a metric called free cash flow, roughly defined as cash flow from operations minus capital expenditures. It excludes things such as noncash impairment charges that can distort net income. This is arguably the purest measure of a business’s underlying cash-generating potential. Amazon, for example, tells investors: “Our financial focus is on long-term, sustainable growth in free cash flow.”

From 2016 through 2023, free cash flow and net earnings of Alphabet, Amazon, Meta and Microsoft grew roughly in tandem. But since 2023, the two have diverged. The four companies’ combined net income is up 73%, to $91 billion, in the second quarter from two years earlier, while free cash flow is down 30% to $40 billion, according to FactSet data. Apple, a relative piker on capital spending, has also seen free cash flow lag behind.

For all of AI’s obvious economic potential, the financial return remains a question mark. OpenAI and Anthropic, the two leading stand-alone developers of large language models, though growing fast, are losing money.

Much of big tech companies’ latest profits reflect their established franchises: ad spending for Meta and Alphabet, the iPhone for Apple. As to when their AI hardware will pay off, they counsel patience.

Meta, parent of Facebook, reported a 36% rise in earnings for the second quarter, but a 22% drop in free cash flow. It said capital expenditure in 2025 would be roughly double last year’s, with “similarly significant” growth in 2026.

Meta has said much of its AI-related capital spending supports core businesses, such as ads and content, and is already paying off. The balance goes toward generative AI such as its Llama model. “We are early in the life cycle” of the latter investments, Chief Financial Officer Susan Li told analysts, and “we don’t expect that we are going to be realizing significant revenue from any of those things in the near term.”

Amazon began tapering its build-out of fulfillment centers in 2022, allowing free cash flow to turn positive. But in the last year, it has ramped up investment in Amazon Web Services, which hosts data and runs AI models for outside clients, and free cash flow is down by two-thirds from the previous year.

Meta is among the major tech companies making big AI-related capital expenditures.

Dot-com echoes

For now, investors are pricing big tech as if their asset-heavy business will be as profitable as their asset-light models.

So far, “we don’t have any evidence of that,” said Jason Thomas, head of research at Carlyle Group. “The variable people miss out on is the time horizon. All this capital spending may prove productive beyond their wildest dreams, but beyond the relevant time horizon for their shareholders,” he added.

In the late 1990s and early 2000s, the nascent internet boom had investors throwing cash at startup web companies and broadband telecommunications carriers. They were right the internet would drive a productivity boom, but wrong about the financial payoff. Many of those companies couldn’t earn enough to cover their expenses and went bust. In broadband, excess capacity caused pricing to plunge. The resulting slump in capital spending helped cause a mild recession in 2001.

A dot-com-style bust looks far-fetched now. AI’s big spenders are mature and profitable companies, and the demand for computing power exceeds the supply. But if their revenue and profit assumptions prove too optimistic, their current pace of capital spending will be hard to sustain.

Amazon Web Services is spending $11 billion on a data center campus near South Bend, Ind.

The interest-rate effect

After the global financial crisis of 2007-09, big tech was both a beneficiary of low interest rates, and a cause.

Between that crisis and Covid, these companies were generating five to eight times as much cash from operations as they invested, and that spare cash was recycled back into the financial system, Thomas, of Carlyle Group, estimates. It helped hold down long-term interest rates amid high federal deficits, as did inflation below the Federal Reserve’s 2% target and the Fed buying bonds. Low interest rates, in turn, made investors value these companies’ future profits even more highly.

Today, government deficits are even larger, inflation is above 2% and the Fed has been shrinking its bondholdings. Meanwhile, corporations face steep investment needs to exploit AI and reshore production to avoid tariffs. Thomas estimates that since 2020, their cumulative free cash flow has been 78% lower, relative to GDP, than in the equivalent period following 2009.

All this suggests that interest rates need to be substantially higher in the years ahead than in the years before the pandemic. That is another risk to the economy and these companies that investors may not fully appreciate.