Big Tech Goes Into Debt: Alphabet and Meta Borrow Billions for AI

The largest US tech companies have stopped paying for AI with their own money alone. Alphabet, Meta and other giants are now borrowing heavily on the markets to build the infrastructure that runs chatbots. Bloomberg describes this as a radical change in model: for decades, these companies' growth rested on high revenue and rising share prices, and now debt has been added to the mix. Last year's deals show the scale. In October 2025, Meta issued $30 billion in bonds, and the construction of the Hyperion campus in Louisiana took roughly $27 billion in external financing, raised through a separate structure together with Blue Owl.

The excerpt of the Bloomberg piece we are reviewing contains no new figures. So below we rely on public deals from past years and on the logic the publication lays out.

Two Jobs, One Budget

The platforms carry a double burden. First, they train and serve their own models: Gemini at Google, Llama and its successors at Meta. Second, they sell compute to startups that cannot buy tens of thousands of accelerators themselves. Each job requires data centers, electricity, networking equipment and chips, and purchases run ahead of demand. The money goes out today; the revenue arrives quarters or years later.

With a gap like that, even companies with tens of billions in free cash flow hit a ceiling. Spending all their cash on capital expenditures would mean giving up the buybacks and dividends that investors count on. Debt lets them avoid the choice.

Why Borrowing

Bonds offer these issuers clear advantages:

• high credit ratings keep rates moderate and demand huge;
• interest on debt reduces the tax base;
• shareholders are not diluted, as they would be in a share offering;
• the loan term can be matched to the service life of a data center.

Off-balance-sheet structures are a separate matter. Hyperion is set up so that part of the obligations sits in a separate company rather than directly in Meta's reporting. For investors, this is also a signal: even when the cash is there, companies prefer not to load their own balance sheets. Oracle, which is not among the top three cloud leaders, borrowed about $18 billion in September 2025, and the deal showed that the debt market is open to more than just the richest players.

Where the Risk Lies

There is one contentious point: payback. Data centers are built for expected AI demand, and so far demand is outpacing revenue for far from all customers. Many capacity tenants themselves live on venture money. If startups start cutting their compute purchases, the platforms will have to service their debt with underused facilities. Accelerators also age faster than buildings: a chip generation turns over in a couple of years, while bonds last longer.

The second risk comes from a chain of mutual dependencies. A chip maker, a cloud provider, a model lab and a lending bank are often tied to one another by contracts. A failure in one link quickly reaches the others.

What to Watch Next

For investors, the main indicator is the ratio of capital expenditures to operating cash flow in the reports of Alphabet, Meta, Microsoft and Amazon. If debt grows faster than revenue from cloud and AI businesses, the pressure intensifies. It is worth reading the footnotes on off-balance-sheet obligations and lease agreements: that is usually where the real size of the burden hides.

For startups, the practical takeaway is simpler. Compute prices depend on providers' cost of capital. More expensive borrowing will sooner or later show up in rates, so it is better to lock in long-term capacity contracts while the credit market is still cheap. Do not build a business model on the assumption that token prices will keep falling: that decline rests on one more assumption, that the platforms will keep borrowing.