The financing flood for tech giants has repeatedly set records, with the 30-year U.S. Treasury yield reaching a nearly 20-year high! The AI super cycle has entered a new stage where "capital is computing power."

The issuance of investment-grade bonds in the United States has set monthly historical records for three consecutive months, highlighting that as companies heavily borrow to fund the construction of artificial intelligence computing infrastructure, the high-rated bond market in the U.S. is maintaining the fastest issuance pace ever. With record bond issuances by AI hyperscaler giants such as Google's parent company Alphabet, Amazon, and Meta, an unprecedented AI investment frenzy has triggered a significant shift in the financing paradigm: transitioning from tech giants using their strong and continuous free cash flow to build AI to a stage where global capital markets collectively finance AI super factories for major tech players. However, this AI investment surge is also pushing long-term U.S. Treasury yields, including 10 and 30-year bonds, continuously higher. According to the latest statistics compiled by Bloomberg News, as of this Monday, U.S. high-rated bond supply in August has reached $145.2 billion, surpassing the previous monthly record of $136 billion set in August 2020. Earlier this year, January, June, and July all set individual monthly records for bond issuance, with three additional months marking their second-busiest high-rated corporate bond issuance levels in history. Looking at it more broadly, since the beginning of this year, AI hyperscalers like Alphabet, Amazon, and Meta have issued nearly $220 billion in bonds, more than double the $108 billion projected for the entire year of 2025. Based on existing comparable data, this level of issuance can be described as a "historical high or record-setting issuance pace for the same period." Notably, the forecast for 2025 is already well above historical normsdata from Bank of America indicates that the top five largest hyperscalers are expected to issue $121 billion in U.S. corporate bonds over the entire year of 2025, while the average annual issuance from 2020 to 2024 was only about $28 billion. In other words, the issuance level in the first eight months of 2026 has significantly exceeded the normal levels of any previous complete year, positioning this period as the highest in history and marking an unprecedented AI debt financing cycle. Furthermore, Wall Street financial giant Morgan Stanley predicts that global AI-related debt financing could approach $570 billion in 2026. These figures not only reinforce the funding certainty for AI infrastructure investment but also suggest that the cost of capital, 10-year and longer-term U.S. Treasury yields and ROIC will become key pressure points in the next stage of the AI bull market. From Alphabet to AMD, the AI spending frenzy has ignited the credit market! The AI arms race is pushing the bond market into a "record-making machine." The torrent of bond issuance has forced investors to become pickier when deciding which bonds to buy and at what price. This was particularly evident last week: the proportion of initial subscription orders that were ultimately withdrawn saw a significant increase. However, this has not deterred companies from continuing to enter the debt market for financing, with another $9.1 billion in bonds scheduled for issuance on Monday. There were a total of 12 transactions that day, including two issuances from private credit funds. As shown in the image above, the issuance of high-rated bonds has set another monthly recordAugust has become the fourth month this year to reach historical highs. This month's issuance was primarily led by a $25 billion bond issued by Google's parent company Alphabet Inc. This marks the eighth bond issuance this year to reach or exceed $25 billion, and all eight deals have come from tech companies. More issuances are expected to follow. Recently, JPMorgan upgraded its forecast for the 2026 dollar bond issuance scale from technology, media, and telecommunications (TMT) companies by about 20% to $540 billion. By roughly aggregating the latest disclosed amounts from media sources, Alphabet raised $31.51 billion in February from the dollar, pound, and Swiss franc markets, followed by another 9 billion (about $10.6 billion) + C$8.5 billion (about $6.2 billion) + 576.5 billion (about $3.6 billion) in May, and then completed a $25 billion dollar bond in August. Before accounting for the proposed Australian dollar bonds, public bond financing for 2026 has already reached about $76.9 billion; the latest dynamics from Alphabet indicate that the company is preparing to enter the corporate bond market denominated in Australian dollars for the first time, with maturities of up to 20 years. August also included a $10 billion bond issuance by U.S. healthcare giant AbbVie Inc. for acquisition financing, as well as a $6.75 billion bonds issuance by financial giant HSBC Holdings Plc. Last week, Nvidia, one of AI chip field's strongest competitors, raised $4.75 billion, creating the largest dollar bond issuance record in the history of this chip manufacturer. The debt capital markets generally accelerate activity in early September, especially after the U.S. Labor Day holiday. So far this year, the bond supply has already reached $1.46 trillion, an 8.5% increase compared to the same period in 2020, when the pandemic-induced bond issuance frenzy set an all-time record for the year. Global debt financing activity in 2026 is also significantly heating up, with cumulative sales of publicly syndicated bonds reaching an unprecedented $5 trillion. The torrent of bond issuances by tech giants collides with the continuously expanding fiscal deficit of the U.S. government, pushing the 30-year U.S. Treasury yield to its highest level since 2007. As noted above, the unprecedented AI investment frenzy has triggered a crucial shift in the financing paradigm: moving from "tech giants using their free cash flow to build AI" to a new stage where "global capital markets collectively finance AI factories." Data compiled by Bloomberg News indicates that just from August, U.S. investment-grade bond issuance reached $145.2 billion, setting a record for the month. This series of latest debt issuance data strongly validates the certainty of AI computing demand and capital expenditures and indicates that AI has transitioned from merely a "stock market theme" to a macro capital cycle capable of changing the funding price in global credit markets. What is truly concerning is that this AI financing surge is creating an endogenous counterforce"the more the AI training/inference frenzy requires capital, the more expensive capital may become." On August 17, the yield on 30-year U.S. Treasury bonds rose to 5.3103%, the highest level since 2007. The core driving forces behind this include approximately $1.9 trillion, around 6% of GDP, in U.S. fiscal deficits and risks related to energy/inflation, along with the long-term corporate bonds issued en masse by AI companies representing a supply of duration; the actual yield on 30-year bonds has approached 3%, an 18-year high. The economic mechanism is very straightforward: the U.S. Treasury Department is competing simultaneously with Alphabet, Amazon, and Meta for global long-term capitalinvestors demand higher term premiums and actual returnsleading to an increase in long-term risk-free rateshigher average cost of capital (WACC) for corporationshigher minimum return thresholds for AI data centers/GPU clusters and power and networking infrastructure. Wall Street asset management giant BlackRock has termed this phenomenon a rare recent trend of capital competition/capital scarcity. Therefore, AI CapEx (i.e., AI capital expenditures) is not only creating economic growth through semiconductor orders, but it may also raise the discount rate for the entire financial system through bond supplywhich is the macro feedback loop most worthy of attention in the current AI super cycle. However, this does not mean that the AI investment cycle is about to be halted by high-interest rates; rather, it implies a very distinct "financing capability stratification" will emerge in the next phase. Top hyperscalers like Alphabet will be able to finance across currencies such as the dollar, euro, pound, Swiss franc, Canadian dollar, Japanese yen, and even Australian dollar, proving that global bond investors are still willing to support their AI infrastructure development with long-term capital; back in February, Alphabet's mere $20 billion dollar bond attracted over $100 billion in orders, demonstrating that top-rated credit issuers still possess strong financing capacity. Furthermore, the latest corporate earnings and demands for AI cloud computing have alleviated some market concerns over AI returns; Wall Street institutional investors seem to be shifting from questioning "whether AI CapEx is too high" to identifying "who can ultimately convert this CapEx into strong profits." Thus, the real watershed for future AI capital expenditures is no longer about "who has the ambition to spend the most on AI," but rather who possesses the lowest financing costs + the strongest operating cash flows + the highest GPU leasing/sales utilization rates + the clearest AI monetization capabilities: powerful cloud computing platforms like Microsoft, Alphabet, and Amazon may further expand their advantages, while technology enterprises reliant on external financing, with high customer concentration and long-term negative free cash flows, will primarily feel the pressure of long-term rates exceeding 5%. The current landscape of the AI investment frenzy is more aptly defined as a "capital cost stress test of the AI super cycle," rather than a signal of an AI bubble burst. From a short-term perspective, the record bond issuance means that the funding source for strong orders related to the construction of AI data centers, GPU/ASIC, HBM/DRAM/NAND storage components, optical interconnects, power, and liquid cooling systems, as well as energy storage systems, is becoming more certain, continuing to reinforce the fundamentals of the AI computing supply chain. In the medium to long term, however, attention must be paid to a dangerous self-reinforcing feedback loop: i.e., "rising AI CapExan increase in AI bond issuancehigher real yields and term premiumshigher discount rates and financing costs for tech companiesmarkets require higher ROICmarginal AI projects are eliminated." Some analysts even point out that real yields may continue to rise until high financing costs begin to truly suppress borrowing and demand for risk assets. In other words, the primary adversary for the next phase of the AI super bull market may no longer be the absence of AI computing demand, but rather a demand for computing that is so strong that it starts competing with the U.S. government for global capitalultimately pushing capital market prices too high.