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AI capex · SEC filings · credit spreads

AI Debt — The Build-Out Running on Borrowed Money

The biggest AI builders are spending hundreds of billions of dollars a year on datacentres. Most of it comes out of cash flow — but not all of it, and one builder owes more than two years of construction before a single new chip is switched on. This is who is exposed, from their own SEC filings, and what the credit market charges the weakest borrowers over the strongest.

CONTAINED0.8xCASH-FUNDED

the five builders' debt together, in years of their combined capital spending — the reading this page is scored on, and the one shown on the dashboard.

The Build-Out in Three Numbers

What the largest AI builders spend, what they owe, and what the credit market charges weak borrowers over strong ones. Readings as of Aug 2, 2026.

Capital spending per year
$552.8bn
All 5 builders combined, trailing four reported quarters
Long-term debt
$439.2bn
All 5 builders combined, latest reported balance sheets
CCC minus AAA spread
9.63 pp
Percentage points, as of Jul 30, 2026 — all-sector rating buckets
Debt ÷ capex, all builders together
0.8x
CASH-FUNDED — the whole build-out on one ratio. Individual builders range from 0.3x to 2.2x; the table below ranks them.

Why this can crash the market

The AI boom is no longer just a stock story — it is a borrowing story. Hundreds of billions of dollars a year in datacentre construction now flow through the revenue of chip makers, builders and power companies, and the most leveraged builder already owes years of future construction. That works only while the credit market keeps lending. If it stops, the weakest builder breaks first, the spending stops second, and every revenue line built on that spending — including the largest companies in your index fund — breaks third. The credit spread on this page is where that break would show up before it makes the news.

Who Is Borrowing to Build

Capital expenditure and long-term debt exactly as each company reported it to the SEC. The periods genuinely differ between companies — and can differ between a company's own capex and debt — so every figure carries its own date.

The 5 Builders, Ranked by Leverage

Source: SEC EDGAR company facts (XBRL), from each filer's own quarterly reports

MOST LEVERAGED: ORCL 2.2x
BuilderCapex per yearLong-term debtDebt ÷ capex
Oracle
ORCL
$55.7bn
ttm to May 31, 2026
$122.3bn
as of May 31, 2026
2.2x
DEBT-FUELLED
Meta
META
$75.7bn
ttm to Mar 31, 2026
$58.7bn
as of Mar 31, 2026
0.8x
CASH-FUNDED
Amazon
AMZN
$173.0bn
ttm to Jun 30, 2026
$128.9bn
as of Jun 30, 2026
0.7x
CASH-FUNDED
Alphabet
GOOGL
$132.4bn
ttm to Jun 30, 2026
$98.2bn
as of Jun 30, 2026
0.7x
CASH-FUNDED
Microsoft
MSFT
$115.9bn
ttm to Jun 30, 2026
$31.1bn
as of Jun 30, 2026
0.3x
CASH-FUNDED
All 5 combined$552.8bn$439.2bn

Sorted by debt-to-capex, most leveraged first — the ratio is the point of this page: it is the number of years of construction, at the current rate, that each company already owes.

What the Credit Market Charges the Weakest Borrowers

If the AI build-out's financing cracks, it cracks here first — in the premium the market demands to lend to weak borrowers instead of strong ones.

CCC Minus AAA Credit Spread

Source: FRED BAMLC0A1CAAA and BAMLH0A3HYC — ICE BofA AAA and CCC option-adjusted spreads, daily • Latest: Jul 30, 2026 • The last three years

WEAK CREDITORS PUNISHED

Read this chart with its limitation in view: it is not a technology-sector measure, and it is not a credit default swap. Single-name CDS quotes are licensed data and cannot be republished here. AAA and CCC are all-sector rating buckets, used as a proxy because that is where the cash-rich hyperscalers and the leveraged datacentre builders respectively borrow. When this gap widens, the market is charging the weakest borrowers more for the money the build-out depends on.

How to Read This Page

Every capex and debt figure comes from the company's own SEC filings, with the period it covers printed underneath — the periods differ, and this page shows that rather than smoothing it away. The spread chart is a proxy, stated plainly above. Nothing here is a forecast: this page does not claim a bubble probability, a timing, or a hit rate, because those numbers cannot be computed from real data — anyone who quotes you one is inventing it. What this page gives you is the exposure itself, ranked, so you can see who owes what before the credit market reprises it. Pair it with the oil shock monitor and the rest of the risks section — an expensive market absorbs an external shock far worse than a cheap one.

Frequently Asked Questions About AI Debt

Is the AI boom a bubble?

This page does not compute a bubble probability, and any site that quotes you one is inventing a number. What can be measured is how the boom is financed: how much the biggest builders spend each year, how much debt they already carry, and what the credit market charges weak borrowers over strong ones. Those three readings — all shown here from SEC filings and Federal Reserve data — are what would deteriorate first if the financing stopped working.

Who is funding AI datacentre construction?

The largest builders fund it very differently. Most generate enough cash to pay for their entire build-out from operations — their debt equals a fraction of one year of spending. One borrows heavily: its long-term debt equals more than two years of construction at the current rate, which means its build-out only continues while the credit market keeps lending. The table on this page ranks the builders by exactly that ratio, from their own SEC filings.

What happens if AI capex stops?

The spending flows to chip makers, server vendors, construction firms and power suppliers, so a stop would hit every revenue line built on top of it. The companies funding construction with debt would still carry that debt after the spending ends, which is why the debt-to-capex ratio is the number to watch: it measures how many years of building each company already owes. The credit spread on this page shows what the market currently charges the weakest borrowers — a widening gap is how financing stress shows up first.

Is the credit spread on this page an AI-specific measure?

No, and it is important to be plain about that. The chart shows the gap between AAA and CCC corporate borrowing costs across all sectors — not a technology index, and not a credit default swap. Single-name CDS quotes are licensed data and cannot be republished. The all-sector rating buckets work as a proxy because AAA is roughly where the cash-rich hyperscalers borrow and CCC is roughly where the most leveraged datacentre builders borrow.

Where do the capex and debt figures on this page come from?

Every figure comes from the company's own SEC filings — capital expenditure summed over the trailing four reported quarters, and long-term debt from the latest reported balance sheet. The reporting periods genuinely differ between companies, and can differ between a company's own capex and debt figures, so each number on the page is printed with the period it covers. Nothing is estimated or interpolated to force a common date.

Why does Oracle stand out from the other AI builders?

Because its long-term debt equals more than two years of datacentre construction at its current spending rate, while the other large builders carry debt worth less than one year of theirs. Oracle is financing the build-out with borrowed money in a way Microsoft, Amazon, Alphabet and Meta are not — its ratio is the one on this page that depends on the credit market staying open.

Get told when the financing cracks

The credit spread and the builders' leverage, alongside the crash-risk score and the other risk indicators — one email a week, only when the composite score moved. A financing break shows up in this data before it shows up in the headlines.

One email a week, and only in weeks the composite score actually moved. No account, one click to unsubscribe, and the address is never shared.

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Company figures sourced from SEC filings as noted above. For educational purposes only. Not investment advice.