Big Tech’s $725bn AI spending spree sends free cash flow to a decade low
Silicon Valley giants have transformed from asset-light cash machines to huge infrastructure investors
Big Tech’s record $725bn AI investment strategy is beginning to strain the resources of America’s largest companies, leaving them with less cash left over this year than at any point in the past decade.
The combined free cash flow of the four “hyperscalers” — Amazon, Alphabet, Microsoft and Meta — is expected to fall to roughly $4bn in the third quarter, according to Wall Street’s forecasts, down from an average of $45bn in each quarter since the Covid-19 pandemic six years ago.
Their full-year free cash flow is set to hit the lowest level since 2014, when their revenues were about a seventh of their current size, according to analysts’ estimates compiled by Visible Alpha.
It is a striking turn for companies that have rapidly transformed from relatively asset-light cash generators into some of the world’s biggest investors in physical infrastructure.
“This is the deepest industry-wide capex cycle they have had,” said Justin Post, an internet analyst at Bank of America. “They see it as a once in a lifetime opportunity.”
The free cash flow metric is closely watched as a measure of the cash companies have left to service debt or return to shareholders after covering their operating costs and capital spending.
Amazon is expected to spend more cash than it generates this year. Meta will burn cash in the second half, as will Microsoft in at least one quarter. Alphabet’s full-year free cash flow will stay positive but drop to its lowest level in more than a decade, analysts expect.
After largely funding their investments from their income for the first few years of the AI boom, these tech giants face trade-offs more familiar to capital-intensive businesses: cutting jobs, reducing shareholder returns or borrowing to fund the build-out.
Post said the companies had started the capital expenditure drive with strong balance sheets, so they were running less risk by adding some debt during a short period of negative free cash flow.
Analysts project their cash generation will improve next year as the AI spending leads to more revenue.
“They are choosing to invest in infrastructure over near-term capital returns to shareholders,” he added. “They’re all trying to catch up on demand right now.”
AI investments have already come at the expense of cash returns to shareholders. Alphabet bought back no stock in the first quarter for the first time since its share repurchase programme began in 2015.
During the quarter, the company issued $31bn in new debt and on Tuesday issued another $17bn worth of euro and Canadian dollar bonds.
“Our ability to invest in this moment and stay at the frontier . . . puts us in a strong position,” chief executive Sundar Pichai said last week.
Meta has also issued $55bn of debt over the past six months while pausing share buybacks. It marks the longest pause in repurchases since the company began buying back its own stock in 2017.
Unlike its rivals, Meta does not have a cloud business to rent out space in the data centres it builds. Executives have turned to staff cuts to free up resources for the investment programme.
When pressed by an analyst last week, Mark Zuckerberg, chief executive, acknowledged Meta did not have “a very precise plan for exactly how each product is going to scale month-over-month”.
Amazon, meanwhile, is expected to burn about $10bn in cash during the year, according to Visible Alpha estimates. It has said it will invest $200bn in 2026, the most out of its peers.
Andy Jassy, Amazon’s chief executive, told investors that the AI build-out was reminiscent of the group’s early bet on its AWS cloud business, which weighed on its balance sheet for years before becoming the source of more than half its profits.
“The free cash flow and [return on invested capital] for these investments are cumulatively quite attractive a couple of years after being in service,” he said.
Jassy added that in periods of “very high growth, like now” capital expenditure meaningfully outpaces the growth in revenue from those investments, meaning “early-year free cash flow is challenged”.
As Big Tech steps up its spending, some analysts have become concerned about the moves companies are taking to flatter their financial metrics.
Tech groups, including Meta, have shifted tens of billions of dollars of data centre projects off their balance sheets using special-purpose holding companies.
These vehicles can bring in Wall Street investors to help fund the infrastructure and raise debt that does not fully appear on the tech company’s balance sheet. But they can also obscure who is ultimately on the hook if data centre demand disappoints.
Larry Ellison’s Oracle has also used off-balance-sheet structures as it pursues a huge bet on building data centres under a $300bn contract with OpenAI. It began to burn cash last year and is not expected to return to positive cash flow until its 2030 financial year.
Christian Leuz, an accounting professor at the University of Chicago’s Booth School of Business, said that because “free cash flow” is not defined in standard accounting rules companies have some discretion in how they calculate it, such as how they treat share-based compensation or leased data centres.
“The real free cash flows of many hyperscalers are probably worse than what they call their free cash flows,” he said.
The AI spending surge is flowing into a strained hardware supply chain, increasing prices for components such as memory chips and making data centres more expensive to build and equip.
Microsoft said price inflation would add $25bn to its capex needs this year, while Meta also cited rising costs as it added $10bn to its investment forecast.
On top of tens of billions in new data centre leases, the value of servers, networking equipment and software on Microsoft’s balance sheet has more than tripled since mid-2022, from $61bn to $191bn.
Morgan Stanley’s analysts called all the spending “very compressive to [Microsoft’s] near-term free cash flow”.
Leuz said Big Tech’s AI build-out resembled the capital cycles seen in cyclical industries with heavy fixed-asset investment, such as telecoms or chemicals, where over-investment eventually leads to overcapacity, depressed margins and weak returns.
But tech bosses feel compelled to keep up with their rivals for fear of being left behind by a technology they believe will be transformational.
“They have to invest when their competition invests,” he said. “It is essentially a prisoner’s dilemma [and] this in turn reinforces the capital cycle.”
