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AI hírek, hogy ne maradj le

2026. november 1., vasárnap · frissítve 19:43
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UkrMedia News2026. nov. 1. 17:16üzlet

Veszélyben az AI-adatközpontok hitelből épített birodalma

Elemzők szerint az AI-infrastruktúrát biztosító cégek 80 százaléka önállóan működésképtelenné válhat 2030-ra a hatalmas adósságteher miatt.

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The artificial intelligence bubble is under threat: what we know

A mesterségesintelligencia-iparág növekedése jelentős részben olyan szakosodott felhőszolgáltatókra épül, mint a CoreWeave, a Nebius vagy az IREN. Ezek a cégek dollármilliárdos hiteleket vesznek fel Nvidia márkájú grafikus processzorok és adatközpontok vásárlására, amelyeket aztán bérbe adnak a nagy technológiai vállalatoknak.

A felvett kölcsönök és a gyors amortizáció miatt a cégek pénzügyi kitettsége rendkívül magas. A Gartner előrejelzése alapján a szakosodott szolgáltatók több mint 80 százaléka felvásárlás áldozata lesz vagy beolvad más társaságokba 2030-ra. A kutatócég szerint az évtized végéig akár 3,5 billió dollárnyi infrastrukturális beruházás értéke is leértékelődhet.

A legnagyobb szolgáltatónak számító CoreWeave adóssága 2026 közepére elérte a 35,6 milliárd dollárt, miközben az elmúlt időszakban a piaci szereplők részvényárfolyama jelentősen esett. A piaci kockázatot növeli, hogy a méregdrága szerverparkok gyorsabban avulnak el, mint ahogy a vásárlásukra felvett hiteleket törleszteni tudnák.

Az eredeti szöveg (UkrMedia News)
The rapid growth of the artificial intelligence industry is increasingly reliant on companies that are racking up billions in debt to build data centres and purchase expensive processors. According to the BBC, the financial stability of such operators is causing concern amongst investors, whilst the fall in their share prices is fuelling fears of a possible overheating of the AI market. The spotlight has fallen on the so-called neocloud companies — specialist cloud infrastructure providers that supply computing power to artificial intelligence developers. Among the leading players in this sector are CoreWeave, Nebius, IREN and Applied Digital. They build data centres and purchase thousands of graphics processing units Nvidia and lease computing power to technology corporations and AI developers, including Microsoft, Meta and OpenAI. Unlike technology giants with diversified sources of revenue, a significant proportion of these operators’ business depends directly on demand for AI computing. To expand, companies take out loans, using high-value processors and long-term contracts with clients as collateral. This enables them to rapidly scale up their infrastructure, but at the same time creates a significant debt burden. A prime example of this was the American CoreWeave, one of the leading providers of computing power for artificial intelligence. According to its financial statements, as at 30 June 2026, the company’s total debt stood at $35.6 billion. Despite its rapid business growth, CoreWeave remains loss-making. In the second quarter of 2026, its revenue reached $2,575 billion, but its net loss stood at $626 million. At the same time, the company had a portfolio of future contract revenue amounting to approximately $104 billion. It is precisely these large orders that enable operators to secure new funding, although the receipt of these funds depends on the fulfilment of the contracts over the coming years. Investors are increasingly scrutinising whether future revenue will be sufficient to cover the costs of equipment, loan servicing and the construction of new data centres. According to the BBC, over the past month, shares CoreWeave has lost around a quarter of its value. Nebius, IREN and Applied Digital all saw similar falls. The research firm Gartner believes that the current pace of investment in AI infrastructure may prove to be financially unsustainable for a significant proportion of operators. According to her forecast, More than 80% neocloud companies will cease independent operations by 2030. This does not necessarily mean bankruptcies: some operators may be taken over by larger competitors or merge with other companies. Gartner also estimates that more than $3.5 trillion in investment in AI infrastructure could be at risk of depreciation by the end of the decade if current rates of capital expenditure continue. The problem is that expensive server equipment becomes obsolete much more quickly than traditional infrastructure. New generations of processors can render previous ones less competitive even before the investment has been fully recouped. The financial difficulties faced by specialist operators could also have an impact on large technology companies. According to S&P Global, the six largest US operators of large-scale cloud infrastructure, including Amazon, Microsoft, Alphabet, Oracle and Meta, could spend more than $7 trillion on data centres and other AI projects between 2025 and 2030. At the same time, some of the financial liabilities arise from complex partnership agreements, guarantees and credit arrangements, which make it difficult to assess the overall risk. A further risk stems from operators’ dependence on a handful of major customers. If technology corporations scale back their investment programmes, specialist suppliers may be left with expensive equipment and loans that must be serviced regardless of server utilisation. At the same time, demand for computing power currentl

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