AI data centre boom is pushing Big Tech deeper into debt
AI data centre expansion is driving a surge in borrowing as Big Tech raise billions to fund infrastructure, chips and power capacity.
AI is expensive. Really expensive.
The race to dominate artificial intelligence is driving one of the biggest spending booms the technology industry has ever seen. Behind every new AI model and chatbot are massive investments in data centres, specialised chips and power infrastructure.
To keep up, technology companies are borrowing more than ever while also taking on huge long-term financial commitments that often do not appear as traditional debt on their balance sheets. Together, these obligations run into trillions of dollars and show just how costly the race for AI leadership has become.
AI infrastructure is becoming a trillion-dollar investment race
Training and running advanced AI models requires enormous computing capacity. To meet growing demand, technology companies are rapidly expanding data centres, securing electricity supplies and ordering thousands of advanced GPUs before facilities even become operational.
These projects require billions of dollars upfront, forcing companies to rely increasingly on debt and long-term financing rather than operating cash flows.
Industry forecasts suggest AI-related debt issuance could approach $570 billion in 2026, reflecting the unprecedented capital needed to build the infrastructure behind modern AI. One of the world's largest data centre operators also reported approximately $18.6 billion in total debt as of June 30, 2026, underscoring the scale of ongoing expansion.
The hidden $1.65 trillion behind Big Tech's AI push
Reported debt tells only part of the story. According to a Nikkei Asia analysis, Alphabet, Amazon, Microsoft, Meta and Oracle have accumulated approximately $1.65 trillion in off-balance-sheet AI-related obligations.
That figure is around 22% higher than the roughly $1.35 trillion in debt reflected on their balance sheets, meaning the obligations investors can't see now exceed the ones they can. These commitments largely stem from long-term contracts for AI data centres, computing infrastructure and power capacity that have been agreed but are not yet operational.
Since many of these facilities have not entered service, the obligations are disclosed in financial statements but are generally not recognised as conventional debt. For investors, this means understanding AI spending requires looking beyond headline debt figures to assess the full scale of future financial commitments.
New financing models are accelerating expansion
To fund this infrastructure build-out, companies are using more than traditional bank loans. Private 144A bond offerings, asset-backed securities and partnerships with private capital firms are becoming increasingly common.
Long-term leases for hyperscale data centres are also helping companies secure financing while spreading costs over several years. These financing structures allow operators to move quickly, but they also increase long-term obligations as AI infrastructure projects continue to expand worldwide.
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Bigger investments also bring bigger risks
The rapid pace of borrowing carries financial risks. Higher interest rates increase financing costs, while delays in securing power, land or specialised chips can postpone projects and reduce expected returns. If AI adoption grows more slowly than anticipated, companies with large debt loads and long-term infrastructure commitments could face pressure on profitability and cash flows.
Investors are therefore watching not only how much companies spend, but also whether new AI capacity is being leased and utilised fast enough to justify these investments.
AI's future depends on more than smarter models
The race to dominate AI is not defined solely by software innovation. It is becoming a contest to build and finance the infrastructure that powers the technology.
As demand for AI computing continues to climb, data centres, energy supply and advanced chips have become strategic assets. The growing mix of traditional debt and off-balance-sheet commitments shows that the AI revolution is not only rewriting technology, but also reshaping corporate finance on an unprecedented scale.