The US AI industry is at a critical juncture, balancing prosperity with risk.
Currently, the US AI boom is heavily concentrated in hardware and cloud services. The incremental increase in capital expenditures by major cloud computing giants between 2023 and 2025 has surpassed the total for the preceding seven years. It is projected that by 2025, the capital expenditures of the four hyperscale cloud providers will reach $305.5 billion, with AI-related spending contributing 90% of the increase in S&amp;P 500 capital expenditures.
Meanwhile, foundational model providers, exemplified by OpenAI, are continuously mired in losses, and commercialization in application layers is severely delayed. The structural imbalance of &#34;strong hardware, weak software&#34; is becoming increasingly prominent.
Although the current bubble is still in its brewing stage and fundamentally different from the dot-com bubble of 2000, risks are rapidly accumulating as the S&amp;P 500 Shiller P/E ratio approaches its historical high of nearly 44x, and redemption pressure surges in the private credit sector.
In a report released on April 7th, Zhongyou Securities stated that the implementation of downstream applications in 2026 will be a key observation window, with the ability to achieve scaled commercial monetization being the core metric. If the bubble bursts and triggers a recession, the Federal Reserve will likely accelerate interest rate cuts and restart quantitative easing, leading to a systemic reevaluation of commodities, global risk assets, and the US dollar's trajectory.
<h2>AI Boom Highly Concentrated in Hardware, Application Layer Monetization Lags</h2>
The US AI industry leads globally. By 2025, 79% (approximately $159 billion) of global AI Series A funding will flow to US companies. As of March 2026, OpenAI has secured $122 billion in financing, with a valuation of $852 billion, ranking it first among global startups.
AI tech companies have become the absolute core drivers of the US stock market rally. The market capitalization of the &#34;Magnificent Seven&#34; tech giants accounts for over a third of the S&amp;P 500's total market cap, contributing 53% to the index's annual return in 2024, with Nvidia alone contributing 5.6 percentage points.
However, behind the prosperity lies a significant structural imbalance. The value chain is highly concentrated in hardware and cloud services, with the foundational model layer experiencing long-term losses, and the scaled commercial implementation of the application layer falling short of expectations.
Taking US enterprise spending data from Ramp as an example, as of February 2026, the penetration rate of US companies paying for AI models and tools has reached 47.6%. However, the gap between AI's actual revenue-generating capacity and the scale of computing power investment continues to widen.
<h2>Debt Risks Emerge, Bubble in Brewing Stage</h2>
The capital expenditure expansion of leading cloud providers has surpassed the boundaries of what their internal cash flow can support. The capital expenditures of Alphabet, Amazon, Meta, Microsoft, and Oracle have accelerated again since 2024, with shareholder buybacks and dividends taking a backseat to AI strategic expansion.
More alarmingly, the AI-related debt financing market experienced explosive growth in 2025, with over $110 billion in debt issued in just September and October. Oracle's total debt has surpassed $96 billion, and the price of its credit default swaps (CDS) has surged accordingly.
The private credit sector is also under pressure. Software-related assets account for approximately 20.8% of the US private credit market. The release of enterprise-grade AI tools by companies like Anthropic has raised market concerns about the sustainability of traditional software business models, thus impacting confidence in the private credit market.
In the first quarter of 2026, redemption requests from the six major leading private credit institutions totaled approximately $10.1 billion, doubling from the previous quarter. Some institutions may have already initiated deferred payment mechanisms.
Despite these issues, the current bubble has not yet reached an unsustainable tipping point. The net profit margins and revenue growth rates of current tech giants remain strong, which is fundamentally different from the model during the 2000 dot-com bubble where many companies relied solely on conceptual financing.
The risks in the private credit market are also relatively contained, lacking the extensive derivative transmission chains seen during the subprime mortgage crisis. It is more likely to be a &#34;storm in a teacup.&#34;
<h2>If the Bubble Bursts, the Economy Will Suffer Multiple Shocks</h2>
Once the AI bubble bursts, the impact will transmit to the real economy through at least three channels.
The wealth effect channel is the primary transmission chain. According to the latest Federal Reserve data, in the third quarter of 2025, US households and non-profit organizations directly and indirectly held $66.5 trillion in stocks, accounting for 32.8% of total assets.
Whether through individual investors or ordinary residents holding index products via 401(k) retirement plans, there is a highly concentrated exposure to the AI sector. Relevant studies indicate that the negative impact of wealth reduction on consumption is about 50% higher than the positive impact of wealth growth, which will amplify the downward pressure on the consumer market after the bubble bursts.
A cliff dive in capital expenditures is the second channel. AI-related capital expenditures have become a core driver of US economic growth. Some studies estimate its contribution to GDP in the first half of 2025 at 1.1 percentage points. Following the historical pattern after the dot-com bubble burst around 2000, broadband operator capital expenditures plummeted by 35% in one year.
If the decline in capital expenditures after the current AI bubble burst is similar, based on the projected over $450 billion in capital expenditures by hyperscale cloud service providers in 2026, the corresponding reduction would exceed $157.5 billion, directly weakening the growth momentum of US real GDP.
Resonance in the upstream industry chain is the third channel. The AI investment craze is highly tied to the semiconductor and electricity industries, as evidenced by Nvidia's 114% year-over-year revenue growth in 2024.
Once investment cools down, the demand elasticity and price volatility for high-performance computing chips highly correlated with AI will be more drastic, and memory chip prices also face the risk of correction. AI also improves labor productivity, leading to weaker employment growth, further providing a macroeconomic basis for monetary easing.
<h2>Federal Reserve's Response Framework: RMP is Just a Prelude; Recession Will Restart QE</h2>
Historically, the Federal Reserve has shifted to large-scale asset purchases after policy rates approached zero in response to three major shocks: the dot-com bubble burst in 2001, the subprime mortgage crisis in 2008, and the COVID-19 pandemic in 2020.
Currently, Kevin Walsh, nominated as the next Federal Reserve Chairman, served as a Fed Governor from 2006 to 2011. His policy inclination towards &#34;rate cuts + balance sheet reduction&#34; has garnered significant market attention.
However, the FOMC's collective decision-making mechanism limits the chairman's personal influence. Current signs such as the ON RRP balance continuously approaching zero and the rise in the SOFR-ON RRP spread indicate that money market liquidity has shifted from excess to marginally tight, limiting further room for balance sheet reduction.
The unanimous decision by all FOMC voters in the December 2025 meeting to launch the Reserve Management Purchase (RMP) program also diverges from the stance of balance sheet reduction.
The macro team at Zhongyou Securities distinguishes three scenarios based on this:
<blockquote>
If the AI bubble only leads to a significant pullback in tech stocks without spilling over into the credit market, the Federal Reserve may manage expectations through forward guidance, tolerating stock price adjustments to suppress core inflation;
If risks spill over into the credit market and credit spreads widen, the Federal Reserve will accelerate interest rate cuts and expand the scale of reserve management purchases;
If the economy falls into recession and unemployment rises sharply, it will aggressively cut interest rates to near zero and restart large-scale QE, using long-term Treasury bonds and agency MBS as primary tools.
</blockquote>
<h2>Global Transmission of a New Round of QE: Commodities May Be the Biggest Beneficiary</h2>
If a new round of QE is implemented, its impact will extend from the US domestic market to global asset markets.
Within the US, a systemic decline in long-term interest rates will improve financing conditions, support demand and employment. Interest-rate sensitive sectors such as real estate will be the first to benefit. Globally, an expansion of US dollar liquidity will improve the overall liquidity environment of capital markets and boost risk asset pricing.
Looking at the asset performance during the past four rounds of QE, the beneficiary logic for commodities is the clearest: QE typically leads to a weaker dollar, directly pushing up the nominal prices of dollar-denominated commodities; a low-interest-rate environment increases the attractiveness of commodities for asset allocation; economic recovery drives improvements in physical demand, and these multiple factors create synergy.
Currently, commodities are in a multi-decade low valuation range relative to US stocks. Historical data indicates that such extreme valuation divergences are often followed by reversals in market dynamics.

OpenAI

The US AI boom is highly concentrated in hardware, with foundational model providers like OpenAI facing significant losses and commercialization in application layers lagging. Aggressive capital expenditures by leading cloud providers are revealing debt risks. Zhongyou Securities believes that if the AI bubble bursts and impacts the real economy, triggering a recession, the Federal Reserve will aggressively cut interest rates close to zero and restart large-scale Quantitative Easing

- The U.S. AI industry is experiencing a critical phase of prosperity mixed with risks, particularly concentrated in hardware and cloud services.  
- Capital expenditures from major cloud providers surged, with AI-related expenses contributing 90% of the S&P 500's capital expenditure increase, while foundational model companies like OpenAI face ongoing losses.  
- If the AI bubble bursts, significant impacts on the economy are anticipated, including reduced capital expenditures and adverse effects on consumer spending, potentially prompting the Federal Reserve to enact aggressive monetary easing measures.

AI Bubble: The Catalyst for a New Round of US Quantitative Easing?