KI: Studie – 2,6 Billionen Dollar Tech-Schulden durch KI-Boom
Der KI-Boom der US-Techriesen kostet Milliarden – und ein Großteil der Rechnung taucht in den Bilanzen bisher nicht auf. Eine Studie zeigt, wie hoch die Verschuldung tatsächlich ist.
A recent study reveals that the rapid growth of artificial intelligence (AI) is increasingly being financed through hidden debts. Within a single year, the long-term debt of the eight leading US technology companies has risen by 86 percent, according to a report published by credit insurer Allianz Trade on Friday. Simultaneously, their off-balance-sheet obligations, primarily for data centers, energy supply, and AI infrastructure, increased by 573 billion to roughly 2.6 trillion dollars within the same period.
When these previously only partially visible obligations are taken into account, the total debt load of the companies rises on average by nearly 150 percent. Consequently, the credit quality of the companies is estimated to drop by one to two rating levels due to this calculation. "The tech sector has so far skirted around the iceberg, but navigation will become more difficult," said Alexander Hirt, an expert at Allianz Research.
"The actual development, however, takes place beneath the water's surface: obligations that are still not appearing in the balance sheets will gradually become actual liabilities in the coming years." Risk factors have already started to materialize in the credit markets, with risk premiums, known as spreads, for bonds of major technology companies having more than doubled within a year.
Allianz Trade assumes that risk factors are only partially accounted for at this stage. "Despite rising burdens, the immediate default risk for tech companies remains low," explained Hirt. "The greater risk lies in a continuous spread widening and thus a gradual revaluation of creditworthiness by capital markets." The authors also believe the findings are relevant for the German economy.
Many companies rely on the infrastructure of the major US providers and plan their own billion-dollar AI investments. Investors should therefore consider long-term infrastructure and supply contracts more heavily in their risk analysis, advised Hirt.
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