Companies are burning through exorbitant sums of money to keep pace in the AI arms race. Debt is climbing. Amidst this flurry of activity, Amazon has signed a deal to borrow some $17.5 billion from a number of financial lenders, according to Bloomberg.
The banks behind the loan reportedly include Citigroup, JPMorgan Chase, Wells Fargo, HSBC, and BofA Securities. The deal has been characterized as a delayed draw term loan, meaning Amazon can draw down the funds on its own timeline rather than taking the full sum upfront, giving it flexibility in how and when the money gets deployed.
This loan comes just two days after it was reported that Amazon would also raise $14 billion in a Canadian bond sale, bringing its total new financing to roughly $31.5 billion in the span of roughly 48 hours.
It’s not clear exactly how Amazon plans to spend all the new money. Reuters notes that the new loan will be used for “general corporate purposes.” TechCrunch has reached out to Amazon for more information.
Amazon is hardly alone. To fund new AI infrastructure like chips and data centers, companies are leveraging historic capex. Increasingly, companies are borrowing money to fund their massive AI buildouts. The question investors and analysts are increasingly asking isn’t whether this spending is necessary — it’s whether the returns will ever justify it.
The scale of the borrowing is striking even by Silicon Valley standards. About a week ago, Google parent company Alphabet said that it planned to raise $80 billion through a stock sale designed to help “fund its investments in a balanced way while retaining a healthy balance sheet.” Meta has also announced plans to raise $30 billion in a bond sale — its largest ever.
This trend of massive borrowing is not limited to Amazon. Other tech giants are following suit, and the question on everyone’s mind is whether these companies will be able to generate sufficient returns to justify their investments.
The AI arms race is driving this unprecedented level of spending. Companies are racing to build out their AI infrastructure, from chips to data centers, in an effort to stay ahead of the competition. However, the cost of this endeavor is staggering, and it remains to be seen whether these companies will be able to generate sufficient returns to justify their investments.
In a related development, it has been reported that some companies are spending as much as $7,500 per employee each month on AI-related expenses. This figure highlights the scale of the investment required to stay competitive in the AI arms race.
The borrowing by Amazon and other tech giants raises questions about the sustainability of this level of spending. Will these companies be able to generate sufficient returns to justify their investments, or will they be left with a mountain of debt?
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