$180 billion gamble! Can Google's computing Great Wall build an AI empire?

Eastern Time, February 4th, Alphabet (Google’s parent company) released its fiscal year 2025 Q4 (ending December 31) and full-year earnings report, with core financial metrics such as revenue and earnings per share (EPS) significantly surpassing market analyst expectations.

However, behind these impressive results, the company’s disclosed capital expenditure guidance for 2026 caused a collective shock on Wall Street. Google expects capital expenditures to reach $175 billion to $185 billion in 2026, nearly double the total for 2025.

Following the earnings release, Alphabet’s stock experienced a textbook “rollercoaster” ride. After-hours, the stock price plummeted sharply, initially dropping 7.5%, erasing about $350 billion in market value within minutes; then, as investors delved into the company’s cloud computing profit margins and AI-related order scales, the stock rebounded, rising over 4%.

In just a few minutes, Alphabet’s market capitalization fluctuated by approximately $800 billion. This extreme market reaction not only confirmed investors’ recognition of Google’s current profitability but also starkly revealed Wall Street’s underlying anxiety about the prolonged, costly global AI industry race.

01. Stellar Performance: Cloud Computing Enters Profit “Harvest” Phase

To understand why Google’s stock could rebound so quickly after a sharp dip, the key lies in its strong commercial monetization capabilities demonstrated this quarter, primarily driven by the deep integration of cloud computing and AI technology.

From a financial perspective, Alphabet achieved a qualitative leap in 2025. Total annual revenue reached $402.8 billion, up 18% year-over-year. In terms of profit, Q4 EPS hit $2.82, a 31% increase YoY.

Notably, Google Cloud’s performance was particularly outstanding, now officially a core engine driving profit growth. This quarter, cloud revenue reached $17.7 billion, with a further acceleration in YoY growth to 48%. More importantly, profit quality improved significantly, with operating profit margins soaring from 17.5% last year to 30.1%.

In the cloud industry, a 30% profit margin is a critical threshold, indicating Google Cloud has fully moved beyond the “burning money to capture market” stage. Leveraging the scale effects and technological advantages of AI large models, it has entered a high-profit return period. Additionally, Google Cloud’s backlog doubled YoY to $240 billion, providing strong certainty for sustained future revenue growth.

On the product side, AI penetration is translating into astonishing data. Currently, Gemini App’s monthly active users (MAU) have exceeded 750 million, and Gemini Enterprise, targeting businesses, sold over 8 million paid seats within just four months of launch.

Image source: Google official website

This marks the successful transformation of this tech giant from a traditional ad-driven company into a high-technology barrier provider of computing power and AI services.

Furthermore, its strategic positioning within the industry ecosystem was fully validated in this earnings report. As the preferred cloud service provider for Apple’s next-generation foundational models, Google has become a key technological supporter of iOS ecosystem AI transformation.

Alphabet and Google CEO Sundar Pichai personally confirmed this deep integration during the conference call: “I am pleased to announce that we are collaborating with Apple as its preferred cloud provider and are using Gemini technology to develop the next-generation Apple foundational models.”

This statement implies that the core AI functions in the new iPhone, including model inference and computing power, will be supplied by Google Cloud, allowing Google to benefit directly from Apple’s ecosystem upgrades. This revenue model, based on AI model licensing and computing power leasing, offers higher user stickiness and stronger industry defensibility compared to traditional advertising.

These solid cash flow expectations have helped investors, after initial panic over capital expenditure, regain confidence in Google’s ecosystem position in the AI era.

02. $180 Billion Investment Boosts Computing Infrastructure

Another noteworthy point in the earnings report is Alphabet’s disclosed capital expenditure estimate for 2026, reaching $175 billion to $185 billion. This massive investment plan triggered a sharp decline in stock price after hours.

Investors were evidently panicked, uncertain whether this trillion-dollar-level investment aims to build a higher industry moat or risks becoming a bottomless money pit.

In response to Wall Street’s collective doubts, Sundar Pichai candidly stated during the conference call: “In fact, the biggest concern keeping us awake at night is the bottleneck in computing power.”

He believes that during the peak of the AI wave, “the risk of under-investment is far greater than over-investment.” This money is not filling a “bottomless pit” but is addressing the overflowing customer demand. He revealed that despite Google’s aggressive capacity expansion, the supply remains severely “constrained.”

This judgment is central to Google’s “stockpile first, defend later” wartime strategy, explaining why Google is willing to endure stock price volatility to push forward with a doubled capital expenditure plan.

To better understand this aggressive approach, compare it with its main competitor, Microsoft. While both are ramping up capital investments, their core strategies differ markedly. Microsoft’s moat is more built on the deep integration of Azure cloud and Office ecosystem, with high capital expenditure mainly supporting OpenAI’s core computing infrastructure, focusing on application deployment and commercialization for profit.

In contrast, Google pursues a more extreme “vertical integration” route. Its core advantage lies in its self-developed TPU (Tensor Processing Units). This “self-made chips, self-fought” capability allows Google to achieve a higher return on investment and bargaining power in its $180 billion “big gamble” compared to competitors heavily reliant on external chips.

CFO Anat Ashkenazi pointed out: “Of this nearly $180 billion expenditure, about 60% is allocated to core server chips and related hardware, with 40% invested in data centers and power infrastructure.” She emphasized that Google is not blindly throwing money but has already seen initial returns through its cloud profit margin of 30.1%.

Google’s logic is that in the heavy asset phase of AI, whoever controls the absolute redundancy of power and computing resources will hold the pricing power for the next decade. Sacrificing short-term financial aesthetics for long-term monopoly is key to Alphabet’s market value recovery after dips.

03. Google’s Confidence and Challenges

In response to market concerns over the trillion-dollar capital expenditure, Sundar Pichai clearly stated during the earnings call: Google is reshaping and innovating its core business through AI transformation and commercial breakthroughs, validating the reasonableness of this huge investment. The company’s current business performance also supports this confidence.

The AI revolution in Google’s core search business has shattered the prophecy that “AI chatbots will end Google Search.” The quarterly data shows that the new “AI Mode” smart search feature did not cannibalize traditional search traffic; instead, it enhanced user experience through more intelligent interactions, leading to higher-quality user engagement.

Data indicates that search queries in AI mode are three times longer than in traditional search, meaning user behavior has shifted from simple keyword searches to complex conversational information research. This behavioral change presents two major commercial opportunities for Google: one, precise ad matching based on deep user needs, significantly increasing ad conversion rates; two, higher traffic monetization efficiency, further boosting search business profitability.

In this quarter, Google Search revenue grew by 17%, demonstrating that AI technology is not a disruptor but an enhancer of core business, making the company’s traditional strength more profitable.

Additionally, Waymo, Google’s autonomous driving unit, has reached a key commercialization milestone, shifting from long-term R&D to a new growth engine. Previously labeled a “money furnace” due to continuous R&D investments, Waymo’s latest results have impressed the market.

Currently, Waymo has launched its sixth commercial operation market in Miami, with weekly paid autonomous ride services exceeding 400,000 trips, and its scale continues to grow.

More importantly, AI technology has empowered Waymo’s operations and improved internal efficiency. Using internally developed AI Agent tools, Google now has 50% of its code written and reviewed by AI, significantly reducing R&D costs.

This internal efficiency boost allows Google to support “cost-cutting” measures—such as Waymo’s commercialization and cloud growth—by freeing up cash flow, underpinning the massive capital expenditure.

However, for Alphabet, 2026 will be a significant balancing challenge. The company must accelerate infrastructure development to meet surging AI computing and service demands, maintaining its industry leadership; simultaneously, it needs to leverage high-margin AI software services like Gemini Enterprise subscriptions and revenue sharing from Apple’s foundational models to rapidly grow revenue and profit, offsetting the financial costs of the trillion-dollar investment.

This earnings report indicates that Google is steadily transforming into a “digital heavy industry empire” focused on building a global computing infrastructure. Its $400 billion annual revenue demonstrates its strong monetization capability, while the nearly $180 billion capital expenditure guidance signals that the global AI industry has entered a heavy-asset phase.

Google’s core challenge in 2026 will be to ensure that the profit growth rate of its AI business keeps pace with the rising costs of infrastructure development. This trillion-dollar computing layout will not only shape Google’s future industry positioning but also serve as a key indicator for the global AI industry’s development trajectory.