Original Title: AI Bubble Burst: Alphabet Could Be The First To Cut AI Capex
Original Author: Damir Tokic, Seeking Alpha
Original Translation: Sulige
Editor's Note: Damir Tokic, a columnist for the American investment platform Seeking Alpha, a professor of finance, and a CTA (Commodity Trading Advisor), published a forward-looking analysis of Alphabet's financial report this Monday, sparking widespread discussion in the U.S. stock investment circle. The article suggests that Alphabet, Google's parent company, could be the first among large tech companies to reduce AI capital expenditures. Notably, Alphabet will hold its second-quarter earnings call for 2026 at 4:30 AM Beijing time on July 23.
Influenced by this view and market sentiment, discussions about AI capital expenditures and the "AI bubble" have once again heated up, with multiple AI semiconductor stocks such as SK Hynix reversing gains during today's trading. Below is the original content:
Alphabet First to Release Financial Report
Alphabet (GOOG) (GOOGL) will be the first to release its financial report, with the market closely watching the guidance on AI capital expenditures. In April of this year, Alphabet raised its AI guidance for 2026 and signaled that AI capital expenditures for 2027 would rise significantly.
However, there are growing concerns in the market about the sustainability of AI capital expenditures on multiple levels; hyperscale companies may have to slow down or even reduce their AI capital expenditures for the remainder of 2026 and into 2027. Since Alphabet will be the first to release its second-quarter financial report, it may become the first hyperscale company to revise down its AI capital expenditure expectations, with others — Meta (META), Microsoft (MSFT), Amazon (AMZN), and Oracle (ORCL) — likely to follow suit.
In fact, the recent weak performance of stocks benefiting from AI capital expenditures — such as the semiconductor sector (SMH) — reflects market anxiety regarding AI capital expenditures.
As discussed later, Alphabet is particularly vulnerable due to issues with its adjusted free cash flow and the need to finance AI capital expenditures through debt and new stock issuances.
Even just hinting at slowing AI capital expenditure guidance could accelerate the burst of the AI bubble — hence, this is also a macro signal.
Big Picture
First, let's look at the big picture. The U.S. economy, especially the stock market, currently heavily relies on AI capital expenditures. It is estimated that AI capital expenditures in 2026 will be around $700 billion to $800 billion, with 2027 far exceeding $1 trillion, primarily focused on data center infrastructure construction.
However, due to multiple constraints, this anticipated AI capital expenditure is difficult to realize.
·Token Economics and Return on Investment (ROI): The most significant constraint lies in the uncertain ROI of AI capital expenditures, likely to be far below capital costs — meaning AI capital expenditures could be wasteful investments. Specifically, U.S. data centers are designed for expensive cutting-edge models, while businesses adopting AI require inexpensive open-source models. Therefore, there is a mismatch. Given the model substitution effect (from expensive to inexpensive), token prices continue to decline, which will compress the profit margins of hyperscale companies per token, rendering entire projects financially unsustainable. The newly launched open-source model Kimi K3 from China indicates that powerful large language models can be built at extremely low costs — therefore, all these AI capital expenditures are unnecessary.
·Energy and Water Resource Constraints: Data centers require massive energy supply and water resources for cooling, which are tangible physical constraints limiting the further expansion of data center infrastructure.
·Regulatory and Resistance Sentiments: New York State has taken the lead in issuing a one-year moratorium on data center construction, with several other states also considering similar measures. In the U.S., it seems that "red states" like Texas allow for data center construction, while "blue states" like New York hold opposing views. Consequently, the issue of AI infrastructure construction has shown signs of becoming politicized. Even in Texas, consumer resistance to data centers is rising, which could become a challenge for the Republican Party in the upcoming elections.
Thus, AI infrastructure construction faces real financial, physical, and political constraints, making it hard to see how the current AI capital expenditure guidance can be sustained.
As mentioned before, even just showing signs of slowing in AI capital expenditures could accelerate the burst of the AI bubble.
Alphabet's Situation
The market narrative regarding Alphabet has been:
· "The risk of insufficient investment is greater than that of over-investment" — suggesting that Alphabet is aware of the possibility of over-investment but is still willing to continue AI capital expenditures due to competitive and strategic needs;
· "Demand for computing power exceeds supply" — implying that Alphabet has not yet seen an oversupply and clearly states that revenues would be higher if more capacity were built.
Thus, there are no signs indicating that Alphabet will slow down or cut AI capital expenditure guidance.
However, issues are emerging at the financing end of AI capital expenditures — these are real financing constraints.
Specifically, Alphabet appears to have severe issues with its free cash flow; thus, it has been forced to maintain AI capital expenditures through debt issuance (issuing over $30 billion in bonds in the first quarter) and equity financing (announcing over $80 billion in new stock issuance) — even halting stock repurchases in the first quarter.
In fact, Alphabet's free cash flow issues may be more severe than reported. The Wall Street Journal, in an article titled "How the Financial Data of Tech Giants Masks the Real Cost of AI Construction," quotes the views of "Heard on the Street" columnist Jonathan and Purdue University professor Kevin Koharki, pointing out that after adjusting for economic costs such as stock compensation, Alphabet's free cash flow for 2025 could be 67% lower than reported values, and 62% lower for the first quarter of 2026. This means the reported free cash flow of $73 billion for 2025 would drop to $24 billion, and the reported free cash flow of $10 billion for the first quarter of 2026 would drop from $10 billion to about $4 billion.
The key implication is that Alphabet cannot continue AI capital expenditures without borrowing and issuing new stocks — increasing debt will expose it to credit issues (especially given low ROI), while issuing new stocks will dilute the equity of existing shareholders.
Now, as we approach the second-quarter earnings report, Alphabet must update its AI capital expenditure guidance — which presents a tricky situation for investors.
· If Alphabet raises the AI capital expenditure guidance despite facing financial constraints (token economics, ROI), physical constraints (energy, water, resistance sentiments), and financing constraints (free cash flow, debt, equity), investors will question management's motives and prudence — likely resulting in a drop in stock price.
· If Alphabet cuts its AI capital expenditure guidance, it will be interpreted as a macro signal, likely accelerating the burst of the AI bubble and severely impacting AI capital expenditure beneficiaries like SMH.
· Even if Alphabet merely reiterates its 2026 guidance and cautiously emits a robust signal for 2027 AI capital expenditures, it may be interpreted as a slowdown in AI capital expenditure growth, thus generating macro effects similar to a reduction in capital expenditures.
Therefore, this indeed presents a dilemma for Alphabet and the broader market. Investors are unlikely to reward increases in capital expenditures, while reductions in capital expenditures will likely lead to punishments for sectors benefiting from AI capital expenditures.
From the recent performance of the semiconductor sector, investors seem to be preparing for a slowdown or reduction in AI capital expenditures.
Alphabet's Financial Condition
About 80% of Alphabet's revenue comes from service business (advertising-driven), primarily from Google Search, while about 20% comes from Google Cloud.
Alphabet Q1 Financial Report
After the Q1 earnings release, Alphabet CEO Sundar Pichai stated:
The start of 2026 is strong. Our AI investments and full-stack strategy are activating all aspects of the business. The search business performed robustly this quarter, with AI experiences driving user growth, query volume hitting historic highs, and revenue growing by 19%. Google Cloud revenue increased by 63%, with backlogged orders nearly doubling quarter-on-quarter, exceeding $460 billion. Fueled by the Gemini application, this has been our strongest quarter ever for consumer AI business. The total number of paid subscribers has reached 350 million, with YouTube and Google One being the main drivers. Gemini Enterprise Edition momentum is strong, with paid monthly active users increasing by 40% quarter-on-quarter. Lastly, I am pleased to see Waymo exceeding 500,000 fully autonomous rides per week. These outstanding results are built on our differentiated full-stack strategy. Our self-developed models, like Gemini, are currently processing over 16 billion tokens per minute through direct API calls from customers, a 60% increase quarter-on-quarter. It is exciting to see our AI investments creating value for users, customers, and businesses.
Thus, Google Search grew about 19%, and overall profit margins increased from 34% to 36%, with AI Overviews not yet eroding advertising revenue.
Google Cloud grew by 63%, and demand for computing power remains strong — this is a major source of growth for Alphabet. Additionally, API usage for Gemini increased, token usage grew by 60%, indicating that the model substitution effect has yet to manifest.
All of these are positive signals; there are no indications pointing toward a downward revision in the financial data — in fact, Alphabet is seen as an AI winner, with even Berkshire Hathaway investing in Alphabet.
However, the problems are gradually becoming apparent in the cash flow statement, even without adjusting for free cash flow. In the context of declining free cash flow, Alphabet cannot achieve the guided AI capital expenditures without taking significant credit risks or diluting the equity of existing shareholders.
Alphabet Q1 Financial Report
Impacts and Insights
The Q1 financial data reported by Alphabet is strong, with the only danger signal being the decline in free cash flow — especially the adjusted decline — which is significant enough to warrant a major warning for downgrading GOOG to a "sell" rating.
If Alphabet cannot achieve its AI capital expenditure guidance without new debt and equity issuance, this not only increases credit risk and dilutes shareholder equity, but also reduces buybacks. In the broader context mentioned above, this is negative news.
If Alphabet cuts or slows down its AI capital expenditure guidance, investors will have to adjust their growth expectations, which means a reduction in valuation multiples — also negative news. It is worth noting that GOOG's GAAP price-to-earnings ratio is 26 times, not particularly expensive. However, given concerns about overall inflated earnings, the actual price-to-earnings ratio may be much higher.
Note that this is also a macro judgment — as the AI bubble burst accelerates, the S&P 500 (SPY) (SP500) and NASDAQ 100 (QQQ) may face a deep correction, with Alphabet likely becoming the first hyperscale company to cut its AI capital expenditure guidance.
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