After the market close on July 22, Eastern Time, Alphabet, the parent company of Google, released its second-quarter earnings report for 2026.
On paper, this is an extremely dazzling report card: total quarterly revenue reached $119.796 billion, a 24% year-over-year increase, marking the 12th consecutive quarter of double-digit growth; net profit attributable to shareholders surged to $112.107 billion (including equity investment income). However, the feedback from the capital market is intriguing. After the release of the earnings report, Google's after-hours stock price once plunged by more than 4%.
Behind the comprehensive beat of earnings expectations and the contrary drop in stock price lies a reflection of the capital market's deepest anxieties and divisions in the face of the generative AI era.
Let's first take a look at the earnings highlights.
Google Cloud: The "Catalyst" for AI Commercialization
The biggest highlight of this quarter's earnings report is undoubtedly the explosive growth demonstrated by the Google Cloud segment.
Revenue growth surges: Google Cloud revenue reached $24.8 billion, a massive 82% year-over-year increase. This growth rate not only far exceeded the market expectation of $22.3 billion, but also achieved a significant secondary acceleration compared to the previous quarter (63%) and the same period last year.
Profitability multiplies: Operating profit for the cloud business surged from $2.826 billion in the same period last year to $8.814 billion, nearly tripling. This performance directly dispelled previous market doubts about "whether enterprise AI demand is excessively inflated." CEO Sundar Pichai revealed that nearly 90% of the Fortune 100 companies have connected to and are using Gemini Enterprise services. The strong demand from enterprises for AI infrastructure (GCP) and AI solutions is becoming the core driver accelerating Google Cloud's performance.
Search and Advertising: AI Not Only Failed to Kill Search, But Instead Became an Enhancer
At the dawn of the rise of new AI conversational terminals such as ChatGPT, there was a view that Google's traditional search would be disrupted. However, judging from the Q2 data, the fundamental base of Google's search advertising remains rock-solid.
Revenue from Google Services reached $94.54 billion, a 15% year-over-year increase.
Search and other advertising revenue grew 17% to $63.3 billion.
YouTube advertising revenue grew 13% to $11.1 billion.
With the comprehensive rollout of "AI Overviews" and "AI Mode" on the search front, the API token processing volume of the Gemini model has reached 22 billion per minute. Facts have proven that AI has not replaced search; instead, it has significantly increased user interaction frequency and search stickiness, thereby pushing up the space for advertising monetization.
With revenue, profit, and core businesses all exceeding expectations across the board, why is the capital market still "voting with its feet"?
Free Cash Flow Turns Negative for the First Time in History, Earnings Quality Under Pressure
To seize the AI computing power track and build a solid technological moat, Alphabet significantly increased its investment in hardware and infrastructure this quarter, with single-quarter capital expenditures reaching as high as $44.92 billion, mainly used for GPU chip procurement, server expansion, and AI data center construction. The massive investment directly led to the first quarterly negative free cash flow since the company went public, with free cash flow at -$5.9 billion this quarter, completely shattering the market's inherent perception of Google as having "stable cash flow and high profitability."
The trend of deteriorating cash flow has long been evident. If we set aside Google's financing amount in the market in a single quarter and look solely at the quarterly [Net cash flow from operating activities - Net cash flow from investing activities (including capital expenditures)], this figure was $620 million in Q4 2025, -$17.69 billion in Q1 2026, and expanded to -$43.36 billion in Q2 2026, continuously highlighting the "cash-burning effect" of AI investments.
Full-Year Expenditure Expectations Raised Again, No Signs of Slowdown in the Arms Race
Compared to the current cash flow pressure, the future expenditure guidance released by management has aroused deeper concerns on Wall Street. The earnings report disclosed that Alphabet has raised its full-year 2026 capital expenditure expectation from the previous $180 billion to $190 billion, to $195 billion to $205 billion, setting a new high for the full-year investment scale.
CFO Anat Ashkenazi stated bluntly that the global AI computing power market is currently in a tight balance of continuous supply shortage, and the industry's computing power race is still ongoing. The company's capital expenditures will continue to grow significantly in 2027, meaning that the future cash flow pressure will be difficult to alleviate, and the return cycle for AI investments will be further extended.
Hidden Costs Lurk in the AI Transformation of Search, Monetization Efficiency Falls Short
In addition to explicit capital expenditures, the hidden costs and monetization risks in the AI transformation of Google's search business have also caused the market to have concerns about its long-term profitability. On the one hand, the cost per search (CPR) has surged significantly. AI-powered intelligent search driven by the Gemini large model requires massive computing power and storage resources to support reasoning operations. The cost is far higher than that of traditional index search, continuously driving up business operating costs.
On the other hand, the game theory dilemma between user experience and advertising monetization has not yet been resolved. The model where AI directly generates precise answers has significantly reduced users' behavior of clicking on traditional ad links, forming a structural contradiction of "rising search traffic but declining monetization rate per click." Currently, Google has still not explored an efficient AI scenario ad placement model. How to balance user experience and commercialization revenue has become a core challenge on its AI transformation path.