Off‑balance‑sheet commitments of the eight leading U.S. technology firms jumped from $573 bn a year ago to $2.6 tn today, lifting their effective debt burden by roughly 150 % and more than doubling bond‑spread premiums, a Handelsblatt report says.
Scale of the hidden liabilities
The Allianz Trade study, quoted by Handelsblatt, tracks obligations that sit outside the traditional balance sheet – primarily contracts for data‑centre construction, long‑term energy supply and AI‑infrastructure rollout. At the start of the twelve‑month period the aggregate off‑balance‑sheet exposure was $573 bn; the latest snapshot puts the total at $2.6 tn, an increase of $2.0 tn.
Both figures are presented in U.S. dollars, as the source records them. No conversion to other currencies is performed, preserving the original scale of the commitment.
Effective debt burden rises sharply
When the hidden obligations are added to the firms’ reported long‑term debt, the average leverage metric climbs by about 150 % over the year. The study states that the effective debt load “erhöht sich … im Durchschnitt um fast 150 %” when the off‑balance‑sheet items are taken into account.
For context, the same study notes that long‑term debt alone grew by 86 % in the same period, underscoring that the bulk of the leverage increase stems from the newly disclosed commitments rather than traditional borrowing.
Bond‑spread premiums more than double
Credit markets have already priced the additional risk. The report says that risk premiums – the spreads on bonds issued by large technology companies – have “sich innerhalb eines Jahres mehr als verdoppelt.” The key‑figure in the data set records the spread change as a factor of 2, meaning investors now demand roughly twice the yield premium for comparable credit risk.
Higher spreads translate into higher financing costs for any new debt issuance and can affect the valuation of existing bonds, a concern for both corporate treasurers and fixed‑income investors.
What the numbers reveal and what remains unknown
The study provides a clear snapshot but leaves several questions open. It does not break down the $2.6 tn figure by individual company, nor does it disclose the timing of specific contracts. The identity of the eight firms is implied – the leading U.S. technology players – but the source does not list them, limiting the ability to assess firm‑specific exposure.
Furthermore, the analysis does not quantify how the rising spreads have impacted the cost of capital for each firm, nor does it project whether the trend will continue as AI‑related projects mature. The study’s author, Allianz Trade expert Alexander Hirt, is quoted in the Handelsblatt article, but no forward‑looking guidance is offered.
Investors and regulators therefore have a clear signal that hidden liabilities are expanding rapidly, but they must await more granular data to gauge the precise credit implications for individual companies.
| Metric | Start (one year ago) | End (current) | Change |
|---|---|---|---|
| Off‑balance‑sheet commitments | $573 bn | $2.6 tn | +350 % |
| Effective debt burden (incl. hidden obligations) | Baseline | Baseline + 150 % | +150 % |
| Bond‑spread premium | Baseline | Baseline × 2 | ×2 (more than double) |
| Long‑term debt (reported) | Baseline | Baseline × 1.86 | +86 % |
| Source: Handelsblatt – KI: Studie – 2,6 Billionen Dollar Tech‑Schulden durch KI‑Boom (quotes Allianz Trade study, expert Alexander Hirt) | |||
Regulators and credit‑rating agencies are likely to incorporate these off‑balance‑sheet items into their assessment frameworks. The rapid escalation suggests that traditional leverage ratios may understate true exposure, especially as AI‑driven infrastructure projects continue to scale.
For investors, the doubled spread signals a reassessment of risk premia. Portfolio managers may need to adjust duration and credit‑quality allocations in technology‑focused bond funds, while corporate treasurers might explore hedging strategies or alternative financing to mitigate the higher cost of capital.
What comes next
The study does not indicate when the next data release will occur, nor does it provide a timeline for when the hidden obligations might plateau. Analysts will be watching upcoming earnings releases and any disclosures in SEC filings for clues about the composition of the $2.6 tn figure.
Until more granular data emerge, the headline numbers – $2.6 tn in hidden commitments, a 150 % rise in effective debt, and spreads more than doubling – remain the most concrete gauge of the credit‑risk impact of the AI‑driven expansion in the U.S. tech sector.