---
title: "Hidden debt of $1.65 trillion: how the AI race creates a financial mine for tech giants"
description: "US tech giants have accumulated hidden debt of $1.65 trillion due to the AI race. Meta and Oracle lead in obligations that have not yet come into force. Experts fear that this could lead to a financial bubble if demand for capacity does not meet expectations. 📉🤖💸"
date: 2026-07-23T15:32:40.000Z
lang: en
url: https://xab.info/en/posts/hidden-debt-of-tech-giants-due-to-the-ai-race
tags: [meta, oracle, artificial-intelligence, tech-debt, amazon]
publisher: "XAB.info"
---

# Hidden debt of $1.65 trillion: how the AI race creates a financial mine for tech giants

![Rendering of a massive AI data center complex representing huge tech giant investments](https://xab.info/media/2026/07/23/skrytyy-dolg-tekhnogigantov-iz-za-gonki-za-ii/skrytyy-dolg-tekhnogigantov-iz-za-gonki-za-ii-1.webp)

In the world of high technology, a race is unfolding that could lead to unforeseen financial consequences. The five largest American technology companies, actively investing in the development of artificial intelligence (AI) and the necessary infrastructure, have accumulated a colossal hidden debt. According to available data, its amount reaches $1.65 trillion.

These obligations do not appear in the main balance sheet reports but are hidden in the notes to the quarterly reports. As Nikkei Asia found out, the volume of hidden debt exceeds the officially declared $1.35 trillion. This means that investors may face a serious surprise when these figures finally come to the surface.

### Accounting trick or survival strategy?

The situation looks particularly dramatic in the case of Meta*. The ratio of its off-balance sheet debt to official debt is one of the highest in the industry: the company owes $420 billion in unrecorded obligations against $140 billion recorded in the balance sheet.

Oracle's hidden debt is growing at even more impressive rates. According to available information, it amounts to $273.3 billion. This is 2900% higher than the company's figure in 2022. At first glance, such figures may cause bewilderment, however, such accounting practice is considered acceptable.

Hidden debt arises from long-term contracts that have already been signed but have not yet come into force. This refers primarily to billions of dollars promised to data center operators. The race in the AI field has forced many hyperscalers to conclude agreements, undertaking to pay for computing power only after the launch of facilities.

### Why are companies taking such a risk?

Any organization promising to pay for services or goods is obliged to indicate this as a liability. However, the fact that data centers have not yet started operations allows such agreements to remain off the balance sheet. When the facilities launch, the contracts will come into force, and companies will have to pay for capacity regardless of whether there is real demand for it.

Technology companies are investing money in these future contracts for a reason. According to reports, Alphabet, Amazon, and Microsoft have accumulated a portfolio of orders for cloud services worth $1.45 trillion — services that still need to be provided and paid for.

Amazon Web Services head Matt Garman stated that the investments the company is getting involved in are "not speculative." Such a scheme looks like a convenient way to ensure capacity: companies sign contracts with customers guaranteeing demand, and then conclude long-term agreements with data centers to obtain the necessary resources.

### The shadow of a bubble and the risk of overproduction

However, this approach exposes technology giants to colossal risks. If demand does not arise, companies will be left paying for excess capacity without customers to sell it to. Even more worrying is that the capital expenditures of these companies exceed their profits. This means that tech giants are increasingly relying on corporate bonds and the issuance of new shares for financing.

Despite the growing demand for AI computing, the technology remains relatively new and unproven. Many experts say that it must benefit a larger number of people to avoid the formation of a bubble.

The cost of using AI for almost everything, called "tokenmaxing," has already caught some companies in a difficult position. Agent AI can "eat up" annual AI budgets in a matter of weeks. Because of this, a number of companies are reducing the use of technologies or switching to more affordable models from China.

This uncertainty, combined with the way technology companies "hide" liabilities, raises concerns. On paper, they have fewer long-term liabilities than they actually do, and it is precisely this gap that could become a critical factor in the coming years.