Alphabet's Major Earnings Night: Will Capex Guidance Be Raised? Senior Analyst: Could Hit $200 Billion in 2026

Alphabet, Google's parent company, will release its second-quarter results after the U.S. market close on July 22 local time (early morning on July 23 Beijing time). However, the market's true focus 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, who has over 40 years of experience researching the technology industry, pointed out in an article that multiple supply chain signals indicate Alphabet's previous Capex expectation of $180–190 billion for 2026 may already be conservative. As AI data center construction continues to accelerate and cloud computing demand remains strong, Alphabet's AI infrastructure spending in the coming years is likely to maintain an upward trend.

Castellano expects that Alphabet may raise its 2026 capital expenditure guidance to $190–200 billion in its earnings report, while maintaining its previous 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 by Wallstreetcn, Deutsche Bank expects Alphabet's 2027 Capex to reach approximately $325 billion, a significant increase from its previous forecast of $250 billion; capital expenditures in 2028 could further rise to $365–370 billion.

If this trend materializes, it means the AI infrastructure investment cycle is still expanding, and previous market concerns that AI capital expenditures are about to peak and growth momentum is slowing may face repricing.

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

The wave of AI infrastructure investment is entering a phase of larger-scale expansion. The trajectory of Alphabet's capital expenditures has market significance far beyond a single quarter's earnings report.

As hyperscale cloud providers continue to increase investments in data centers, computing power, and energy infrastructure, capital investment is shifting from gradual growth in the past to a long-term competition measured in hundreds of billions of dollars.

According to market data, the combined capital expenditures of Alphabet, Amazon, Microsoft, Meta, and Oracle have risen significantly from $271 billion in the trailing twelve months ending April 2025 to $482 billion in the trailing twelve months ending April 2026. Based on current guidance from each company and market expectations, the full-year 2026 capital expenditures of the five giants are projected to reach $745–775 billion, representing an increase of approximately 55% to 61% compared to the previous cycle.

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

Five Giants Dominate the AI Infrastructure Investment Cycle

It is important to note that the over $770 billion in capital expenditures will not all flow directly to chip suppliers. It includes various sectors such as servers, network equipment, data center construction, land, power facilities, and energy supply systems.

However, from the perspective of supply chain transmission, every new AI data center will drive simultaneous expansion in multiple links. From high-performance computing chips and HBM memory to advanced packaging, wafer fabrication, test equipment, and high-speed interconnect networks, AI infrastructure investment is forming a complete supply chain pull effect.

The core concern of the market is that current demand in the AI supply chain is not driven by a single enterprise but is jointly determined by a few hyperscale cloud providers. Their procurement pace for GPUs, custom ASICs, HBM, optical networks, and data center power systems has become an important indicator for measuring the prosperity of the entire semiconductor cycle.

Therefore, whether Alphabet further raises its capital expenditures is not just a judgment on the prospects of the Gemini model and Google Cloud business, but also a verification of the intensity of AI infrastructure demand in the next stage.

Meta Rents Out Buffer, Google Orders Provide Backstop—Two Paths for AI Capital Expenditures

Recently, Meta's consideration of selling part of its AI infrastructure capacity to external customers sparked discussions in the market about whether AI investment is becoming excessive. However, from an industrial logic perspective, this move is more akin to improving asset utilization rather than cutting investment.

According to adjusted forecasts from Wells Fargo, the main reason Meta is pushing for the externalization of part of its AI infrastructure capacity is the time lag in the release of internal inference demand, hoping to realize asset returns early through external leasing. This means Meta is commercializing its already invested computing resources, rather than being forced to digest excess capacity due to insufficient demand.

In contrast, Alphabet has stronger internal absorption capabilities. Google Cloud currently has a backlog of contracts worth $462 billion, and enterprise customer demand for AI computing power and cloud services has formed strong order support. This means Alphabet's new capital investments can more directly correspond to future revenue growth, and the commercial certainty of its capital expenditure expansion is higher.

Alphabet Earnings Become an Important Observation Window for the AI Cycle

For the market, the key to Alphabet's Q2 results announced on July 22 is not just profit and revenue performance, but whether management further raises AI capital expenditure expectations.

If Alphabet raises its 2026 capital expenditure guidance, it will strengthen the market's judgment on the sustainability of the AI infrastructure investment cycle and provide new fundamental support for the chip, memory, advanced packaging, and data center supply chains.

Conversely, if capital expenditures are lower than expected, the market may reassess the AI investment return cycle and exert short-term pressure on the valuations of related tech stocks.

As Microsoft, Meta, and Amazon subsequently announce their results, Wall Street will further observe whether this AI infrastructure race is still accelerating and whether hundreds of billions of dollars in capital investment can continue to translate into revenue growth.

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