谷歌财报夜：Capex指引有望上调？2026年或冲击2000亿美元

Original Author: Li Jia

Original Source: Wall Street News

Google parent company Alphabet will announce its second-quarter results after the U.S. stock market closes on July 22 (early morning of the 23rd Beijing time). However, the real focus of the market is not on the single-quarter profit performance, but on whether management will further raise its AI capital expenditure (Capex) guidance.

Robert Castellano, President of The Information Network and a veteran with over 40 years of experience in the tech industry, notes that multiple indicators from the supply chain suggest Alphabet's previous forecast of $180 billion to $190 billion in Capex for 2026 may be conservative. As AI data center construction continues to accelerate and cloud computing demand maintains strong growth, Alphabet's AI infrastructure spending in the coming years is still likely to trend upward.

Castellano predicts that Alphabet may raise its 2026 capital expenditure guidance to between $190 billion and $200 billion in its earnings report, while maintaining its statement that 2027 spending will approach $300 billion.

Meanwhile, Deutsche Bank has also significantly increased its forecast for Alphabet's future capital expenditures. According to a previous article from Wall Street News, Deutsche Bank now expects Alphabet's 2027 Capex to reach approximately $325 billion, a notable increase from its previous forecast of $250 billion. Capital expenditure in 2028 could further rise to between $365 billion and $370 billion.

If this trend materializes, it would mean that the AI infrastructure investment cycle continues to expand. The market's previous concerns about AI capital expenditure peaking and growth momentum slowing may face repricing.

AI Arms Race Heats Up: Big Five Tech Giants' 2026 Capex May Exceed $770 Billion

The wave of AI infrastructure investment is entering a phase of large-scale expansion. The significance of Alphabet's capital expenditure trajectory extends far beyond the single-quarter earnings report.

As hyperscale cloud providers continue to ramp up investments in data centers, computing power, and energy infrastructure, capital spending is shifting from gradual, incremental growth to a long-term race measured in hundreds of billions of dollars.

According to market data, the combined capital expenditure of Alphabet, Amazon, Microsoft, Meta, and Oracle has jumped from $271 billion over the twelve months ending in April 2025 to $482 billion over the twelve months ending in April 2026. Based on current guidance and market expectations, the total capital expenditure for the Big Five in the full year 2026 is projected to reach between $745 billion and $775 billion, representing a growth of approximately 55% to 61% from the previous cycle.

This figure not only reflects tech giants' bets on the commercialization prospects of AI but also signifies they are becoming the core drivers of demand growth across the entire semiconductor supply chain.

Big Five Tech Giants Dominate the AI Infrastructure Investment Cycle

It is important to note that the over $770 billion in capital expenditure will not all flow directly to chip suppliers. This spending spans multiple areas, including servers, networking equipment, data center construction, land, power facilities, and energy supply systems.

However, from a supply chain perspective, each new AI data center will drive concurrent expansion across several segments. From high-performance computing chips and HBM memory to advanced packaging, wafer fabrication, test equipment, and high-speed interconnect networks, AI infrastructure investment is creating a comprehensive supply chain multiplier effect.

The core focus for the market is that the current demand in the AI supply chain is not driven by a single company but is collectively determined by a few hyperscale cloud providers. Their procurement pace for GPUs, custom ASICs, HBM, optical networks, and data center power systems is becoming a key indicator for measuring the health of the entire semiconductor cycle.

Therefore, whether Alphabet further raises its capital expenditure is not only a judgment on the prospects of its Gemini model and Google Cloud business but also a verification of the demand intensity for the next phase of AI infrastructure.

Meta Leases Buffer, Google Orders Backstop – Two Paths for AI Capex

Recent discussions about Meta considering selling some AI infrastructure capacity to external clients have sparked market debate about potential overinvestment in AI. However, from an industrial logic perspective, this move appears more aimed at improving asset utilization rather than cutting investment.

According to revised forecasts from Wells Fargo, Meta's push to externalize some AI infrastructure capacity is primarily due to a time lag in realizing internal inference demand. The goal is to achieve asset returns early through external leasing. This suggests Meta is commercializing its already invested computing resources, rather than being forced to absorb excess capacity due to insufficient demand.

In contrast, Alphabet has stronger internal absorption capacity. Google Cloud currently has a contract backlog of $462 billion, with enterprise customer demand for AI computing power and cloud services providing substantial order support. This means Alphabet's new capital investments can be more directly linked to future revenue growth, giving its capital expenditure expansion higher commercial certainty.

Alphabet's Earnings Report Becomes Key Observation Window for the AI Cycle

For the market, the key takeaway from Alphabet's second-quarter results announced on July 22 is not just the profit and revenue figures, but whether management will raise its AI capital expenditure expectations.

If Alphabet raises its 2026 capital expenditure guidance, it would reinforce the market's view on the sustainability of the AI infrastructure investment cycle, providing new fundamental support for chips, memory, advanced packaging, and the data center supply chain.

Conversely, if capital expenditure falls short of expectations, the market may reassess the AI investment return cycle, creating short-term pressure on the valuations of related tech stocks.

As Microsoft, Meta, and Amazon subsequently report their earnings, Wall Street will further observe whether this AI infrastructure race is still accelerating and whether the hundreds of billions of dollars in capital spending can sustainably translate into revenue growth.