Big Tech debt is becoming a larger part of the financing behind artificial intelligence infrastructure as Alphabet, Amazon, Meta Platforms, Microsoft and Oracle expand data-center capacity. Major hyperscalers have issued roughly $220 billion in debt over the past year, while bond buyers are demanding more compensation to absorb the growing supply.
Key Takeaways
- Alphabet, Amazon, Meta Platforms, Microsoft and Oracle issued roughly $220 billion in debt over the past year.
- Hyperscaler gross debt issuance could reach about $420 billion in 2027, according to Goldman Sachs estimates cited by Reuters.
- AI-related issuers have recently traded at wider credit spreads than the broader U.S. high-grade corporate bond market.
- Meta expects 2026 capital expenditures of $130 billion to $145 billion, while Microsoft reported $41 billion of capital expenditures in its latest fiscal quarter.
- Amazon secured a $17.5 billion delayed-draw loan facility in June as it expanded spending on computing infrastructure.
The financial impact of the artificial intelligence buildout is becoming increasingly visible in U.S. credit markets.
Alphabet, Amazon, Meta Platforms, Microsoft and Oracle have issued roughly $220 billion of debt over the past year, according to a September Reuters analysis. The borrowing has accompanied rapid spending on data centers, processors, networking systems, electrical equipment and other computing capacity.
The scale could increase further. Goldman Sachs data cited by Reuters indicate gross debt issuance from major hyperscalers could reach approximately $420 billion in 2027, about 60% above estimated 2026 levels.
For bond buyers, the central issue is not simply whether the largest technology companies can meet their obligations. Investors are also assessing how much additional debt the market may need to absorb as several large issuers fund infrastructure expansion at the same time.
Big Tech Debt Meets a More Selective Bond Market
The changing market response can already be seen in corporate credit spreads.
AI-related issuers have recently traded at spreads of around 115 basis points, according to Goldman Sachs data cited by Reuters. That compares with roughly 78 basis points for the broader U.S. high-grade corporate market.
Portfolio managers have pointed to the expected volume of future issuance, uncertainty surrounding borrowing schedules and concentration within the technology sector as reasons for greater selectivity.
Alphabet, for example, offered a comparatively large pricing concession on an August bond sale, according to BNY research cited by Reuters. That differed from some recent offerings outside the technology sector, where limited supply contributed to stronger demand.
The pricing difference does not necessarily indicate immediate concern about the creditworthiness of large technology companies. Credit spreads can also widen when markets expect repeated issuance from companies that already represent a significant share of institutional bond portfolios.
That distinction is important as Big Tech debt becomes a broader corporate finance issue rather than simply another component of technology-sector expansion.
AI Infrastructure Spending Drives Larger Financing Needs
Artificial intelligence infrastructure requires significantly more physical capacity than many of the software businesses that previously shaped the economics of large U.S. technology companies.
Data centers require land, buildings, cooling systems, electrical infrastructure, networking connections and large quantities of specialized processors. Many of those costs must be incurred before the additional computing capacity generates corresponding revenue.
Microsoft reported $41 billion in capital expenditures during its fiscal fourth quarter ended June 30. Roughly two-thirds of the spending went toward shorter-lived assets, primarily CPUs and GPUs.
The company also recorded $5.6 billion in finance leases, mainly associated with large data-center sites.
Microsoft generated $55.4 billion in operating cash flow during the quarter and $19.6 billion in free cash flow after capital expenditures increased. Microsoft Cloud revenue reached $59.3 billion.
The figures reflect the financial tradeoff examined in recent Microsoft AI spending analysis. Cloud and AI-related revenue growth is occurring alongside increasingly large infrastructure requirements.
Meta Platforms is following a similar path.
The company said in July that it expected 2026 capital expenditures of $130 billion to $145 billion, narrowing its previous range of $125 billion to $145 billion. Meta reported second-quarter capital expenditures of $31.08 billion.
The company also reported $83.66 billion in long-term debt as of June 30.
The broader expansion of data-center capacity is affecting companies beyond the largest cloud providers. Chip manufacturers, construction contractors, equipment suppliers and utilities are becoming increasingly connected to the financing requirements of AI infrastructure.
Those dynamics are also reflected in broader AI infrastructure spending trends across the technology sector.
Amazon and Other Hyperscalers Expand Funding Options
Amazon has also increased its access to financing as infrastructure spending rises.
In June, the company secured a $17.5 billion delayed-draw term loan facility involving lenders including Citibank, Bank of America Securities, JPMorgan Chase, HSBC and Wells Fargo.
The facility can be used for general corporate purposes and allows Amazon to draw funding as required rather than receiving the full amount immediately.
Amazon has also expanded its presence in international bond markets. In September, the company raised £4.25 billion through its first sterling-denominated bond sale.
Reuters reported that hyperscalers had issued more than $200 billion of debt in 2026 by that point, already more than double the amount raised during 2025.
Amazon has projected approximately $200 billion in capital expenditures for 2026, with much of the spending connected to artificial intelligence and cloud infrastructure.
Chief Executive Andy Jassy said earlier this year that Amazon Web Services AI services had reached an annualized revenue rate of more than $15 billion.
The company’s financing activity illustrates how major technology groups are increasingly combining operating cash flow with loans, bond issuance and other financing structures to support large infrastructure programs.
Cash Flow Becomes Central to the Big Tech Debt Story
The expansion of AI infrastructure is also changing how corporate credit markets evaluate cash generation.
A Reuters analysis of LSEG consensus estimates found that Microsoft, Alphabet, Amazon, Meta Platforms and Oracle were on a trajectory to spend more collectively on capital expenditures than they generate in free cash flow by 2027.
The estimates indicated roughly $340 billion of additional annual operating cash flow between 2025 and 2027 compared with approximately $534 billion of additional capital spending.
Those projections remain subject to changes in company plans, equipment pricing, construction schedules and demand for computing services.
Technology companies also differ in how they categorize and disclose AI-related spending, making direct comparisons difficult.
Meta reported $31.86 billion in operating cash flow during the second quarter but $784 million in free cash flow after capital expenditures and other cash requirements. Microsoft, meanwhile, continued to generate substantial operating cash while expanding its data-center footprint.
The companies therefore enter the current borrowing cycle with different cash positions, spending schedules and infrastructure requirements.
Bond buyers are evaluating those differences while also accounting for the combined supply of technology-sector debt entering the market.
The rise in Big Tech debt does not by itself indicate financial distress among the largest technology companies. It does show that artificial intelligence is making their operations more capital intensive and increasing their reliance on corporate credit markets alongside internally generated cash.
For U.S. bond markets, borrowing frequency, issuance volume, free cash flow and the financial returns generated by new computing capacity are becoming increasingly important factors in assessing technology-sector credit.
Frequently Asked Questions
Why is Big Tech debt increasing?
Big Tech debt is increasing as major technology companies spend heavily on data centers, processors, networking equipment and other computing infrastructure. Borrowing allows companies to fund part of those costs without relying entirely on existing cash reserves and operating cash flow.
How much debt have major hyperscalers issued?
Alphabet, Amazon, Meta Platforms, Microsoft and Oracle issued roughly $220 billion in debt over the year covered by a September 2026 Reuters analysis. Goldman Sachs estimates cited by Reuters indicate gross hyperscaler debt issuance could reach approximately $420 billion in 2027.
Why are AI-related bond spreads wider?
Bond managers have cited large expected issuance volumes, uncertainty surrounding future borrowing and portfolio concentration. Wider spreads can reflect supply and demand conditions even when investors are not signaling immediate concerns about an issuer’s ability to repay debt.
How much are Meta and Microsoft spending on infrastructure?
Meta expects capital expenditures of $130 billion to $145 billion in 2026. Microsoft reported $41 billion of capital expenditures in its fiscal fourth quarter, with roughly two-thirds directed toward shorter-lived assets such as CPUs and GPUs.
Is AI already generating revenue for technology companies?
Some companies have disclosed substantial AI-related or AI-supported revenue. Amazon said its AWS AI services had exceeded a $15 billion annualized revenue rate, while Microsoft has reported continued growth across its cloud and AI businesses, although company reporting methods are not directly comparable.
