五大巨头财报周前瞻：市场在看什么？

Preface: This Isn't an Ordinary Earnings Week, But a Collective Validation of the Tech Megatrend

This week, the US stock market is facing a genuinely "core asset exam week." Microsoft, Google, Amazon, and Meta will all report earnings after the market close on April 29, with Apple following on April 30. Since these five companies cover almost all of the most critical current tech megatrends—including cloud computing, advertising, consumer electronics, e-commerce, enterprise software, and AI infrastructure—their earnings reports will impact not just their own stock prices, but what the entire NASDAQ and tech sector is willing to trade next.

If the market's main narrative over the past few months can be condensed into one sentence, it would be: Big tech companies are continuously increasing their AI investments, and the market keeps raising valuations for tech leaders. However, the problem is that after valuations have risen to this level, the market is no longer satisfied with the fact that "companies are investing in AI." It's now asking more practical questions: Are these investments continuing to drive cloud business growth? Are they improving advertising efficiency? Are they supporting end-user demand? And most importantly, are they beginning to materialize more clearly into revenue, profit, and future guidance?

Microsoft guided for current quarter revenue of around $81.2 billion last quarter, with Azure growth guidance of 37%–38%; Alphabet has outlined its 2026 capital expenditure plan of $175 billion–$185 billion; Amazon expects 2026 capital expenditure of around $200 billion; Meta has raised its 2026 capital expenditure target to $115 billion–$135 billion. These numbers themselves indicate that the real theme of this earnings season remains: Can the market continue to accept high levels of investment?

I. What Does the Market Truly Want to Confirm This Earnings Season?

1. Are Big Tech Companies Still Willing to Spend on AI?

Because the valuations of many companies in the AI infrastructure chain are essentially built on one premise: Super buyers like Microsoft, Google, Amazon, and Meta will continue to place orders, continue to expand data centers, and continue to purchase computing power, networking, and power infrastructure. If management signals any caution regarding capital expenditure on earnings calls, it won't just affect them, but the entire AI supply chain.

2. Can the Cloud and Advertising Cash Cows Remain Stable?

Microsoft Azure, Google Cloud, and AWS are the most direct windows to observe enterprise IT spending and AI demand. Meanwhile, the advertising businesses of Google and Meta represent the core cash flow resilience of internet platforms. If the cloud is stable and advertising is stable, the market will continue to believe that: even with high capital expenditure, tech giants still have the ability to support future investments with their mature businesses.

3. Is AI Just a Story, or Is It Starting to Generate Profits?

All five companies are talking about AI, but they validate it in different ways: Microsoft focuses on enterprise payments, Google on cloud and search, Amazon on AWS and its custom chips, Meta on advertising efficiency, and Apple on the end-user terminal and its ecosystem position. It is precisely because of these different angles that this earnings season is particularly interesting.

II. What Specific Questions Must Each of the Five Giants Answer?

1. Microsoft: The First Question Isn't About Growth, But How Far AI Commercialization Has Really Come

Among the five giants, Microsoft is most like the "showcase model" of this AI cycle. The market has been willing to give Microsoft a premium over the past year not just because it's a cloud leader, but because it's seen as the company most likely to turn AI into a real business first. With Copilot embedded into Office, development tools, and enterprise workflows, combined with Azure as the underlying cloud platform, Microsoft's advantage is that it can not only provide model capabilities but also directly reach the enterprise customers most willing to pay.

Therefore, the most important thing in Microsoft's earnings this time is not just revenue growth, but whether AI's "penetration" of the revenue structure continues to increase. The market consensus for Microsoft's FY2026 Q3 is roughly $81.4 billion in revenue and $4.07 in adjusted EPS. Microsoft's own revenue guidance range provided last quarter was $80.65 billion–$81.75 billion, which is close to market expectations.

The real point to watch is whether Azure's growth rate can remain in a high range and whether AI products like Copilot are showing clearer commercialization progress. Last quarter, Microsoft reported Azure and other cloud services revenue growth of 39% and provided guidance of 37%–38% for the current quarter. This means the core expectation for this earnings report isn't really "is there growth?" but "is AI still accelerating that growth?"

If Microsoft can continue to prove that enterprise customer budgets for AI tools haven't shrunk and that AI's contribution to Azure is still rising, the market will see it as the core leader where "AI commercialization is materializing first." Related enterprise software, cloud, and data center sectors will also continue to benefit. Conversely, if Azure doesn't strengthen further while capital expenditure pressure remains high, the market will refocus on the return on investment.

In other words, the key takeaway from Microsoft's earnings this time isn't to prove AI is important, but to prove that enterprises are still paying for AI.

2. Google: Cloud Next Just Told the Story, Now Earnings Must Deliver the Results

Compared to Microsoft, Google's situation is more like a "product launch followed by a test." With Cloud Next 2026 just concluded, Google unleashed a flurry of signals at the conference regarding AI agents, Gemini Enterprise, Vertex AI, TPUs, and infrastructure investment. This has certainly raised market expectations for Google Cloud again. However, conferences are about vision, while earnings are about delivery. The most significant pressure for Alphabet this earnings season comes precisely from its need to quickly turn "stories" into "numbers."

Google's uniqueness lies in the fact that it's neither a pure cloud company nor a pure advertising company. It straddles two major pillars: one is Google Cloud and AI infrastructure, and the other is the mature cash-flow machine of search and advertising. The current market consensus is roughly Q1 revenue of $106.9 billion–$107.0 billion and EPS of around $2.73. But more crucial than just looking at revenue and EPS is whether three things can happen simultaneously: Google Cloud continues to grow, capital expenditure remains high, and search advertising stays robust. In February, Alphabet already outlined a 2026 capital expenditure plan of $175 billion–$185 billion; last quarter, Google Cloud revenue grew 48% to $17.7 billion, with an annualized run rate exceeding $70 billion and rapidly growing backlog orders. In other words, the market has already partially priced in the narrative of "strong Cloud, heavy AI investment."

So Google's real test isn't whether Cloud can grow, but whether it can maintain its search and advertising profit base while continuing to invest heavily. If all three lines are stable, Alphabet is likely to be redefined by the market as an AI platform leader with the best "offense-defense balance." However, if any one of Cloud, Capex, or advertising shows weakness, the market's demands will immediately become stricter.

Google's earnings this time represent not whether a single business beats expectations, but whether the earnings report can live up to the expectations set by Cloud Next.

3. Amazon: The Real Challenge Isn't AWS, But "Investing and Profiting Simultaneously"

The difficulty of Amazon's earnings report this time differs from Microsoft and Google. The market will certainly look at AWS, but solely looking at AWS is insufficient because Amazon is not a single cloud platform company; it also bears the lines of retail, e-commerce, logistics, advertising, and cash flow. In other words, when the market looks at Microsoft and Google, it's more about AI and enterprise demand. When it looks at Amazon, it's about whether a single company can continue to bet on the future without sacrificing its current profitability.

Based on disclosed information, Amazon's investment in AI is very aggressive. The company stated in its Q4 earnings report in February that 2026 capital expenditure is expected to be around $200 billion, primarily for AI infrastructure. CEO Andy Jassy subsequently added in his shareholder letter that the annualized revenue run rate for AWS's AI services has exceeded $15 billion, while AWS's overall annualized revenue run rate is approximately $142 billion. Simultaneously, the annualized revenue run rate for custom chip-related businesses like Trainium, Graviton, and Nitro has surpassed $20 billion. This shows that Amazon is no longer just saying "we're also doing AI," but is hoping "AI becomes the core engine for AWS's next growth phase."

The problem, however, is that Amazon cannot only talk about the future. AWS is its growth and profit engine, but retail and fulfillment systems determine whether overall profit margins can be maintained. Last quarter, AWS revenue grew 24% year-over-year to $35.6 billion, with full-year AWS revenue reaching $128.7 billion. The company guided Q1 operating profit between $16.5 billion and $21.5 billion, with the midpoint not being particularly aggressive. This means the market will look at Amazon this time not just for AWS growth, but for a more realistic question: Will high-intensity AI investment squeeze profit margins again? If the answer is no, Amazon will be seen as a paradigm where "high investment and high-quality profits can coexist." If the answer becomes ambiguous, market patience will wane.

What's truly difficult for Amazon isn't proving AWS is still growing, but proving it can continue to invest in the future while continuing to earn money in the present.

4. Meta: The Market Continues to Buy In, Not Because It Spends Big, But Because It Spends Efficiently

Among the five giants, Meta's logic is the most easily misjudged. On the surface, like the others, Meta is also ramping up capital expenditure drastically. But the market still awards it a high valuation, not because it also has a series of AI product launches, but because it has repeatedly proven that AI can directly improve its core business—advertising. For Meta, AI isn't a distant new story, but more like an ongoing "efficiency revolution."

Based on last quarter's earnings, Meta's advertising business remains the foundation supporting all its AI investments. In Q4 2025, Meta's ad impressions grew 18% year-over-year, the average ad price increased 6%, and full-year capital expenditure reached $72.2 billion. At the same time, the company has further raised its 2026 capital expenditure guidance to $115 billion–$135 billion and total expense guidance to $162 billion–$169 billion. This means what investors truly need to observe isn't how much Meta spent, but whether that spending continues to yield stronger recommendation capabilities, longer user engagement, better ad targeting, and higher ad monetization efficiency.

Before the earnings report, the mainstream market expectation was roughly Q1 revenue of $55.46 billion, ad revenue of $53.93 billion, and EPS of $6.73. These numbers are certainly important, but what truly determines market sentiment is the underlying logic chain: AI recommendation optimization → increased user engagement → improved ad efficiency → higher ad revenue → continued market tolerance for high Capex. If this chain holds true, Meta will continue to be seen as one of the best examples of "AI improving mature business efficiency." Conversely, if ad growth slows down while capital expenditure pressure increases, the market will scrutinize its investment pace more critically.

In other words, Meta's earnings report this time isn't answering "Is AI worth investing in?" but rather: "Is AI continuing to make the advertising machine more profitable?"

5. Apple: The Market Doesn't Expect It to Be the Most Aggressive, It Just Wants to Confirm It Hasn't Fallen Behind

If the first four companies are all, to some extent, centered around "AI investment and commercialization," then Apple's logic is entirely different. The market doesn't expect Apple to tell the most aggressive AI story this earnings season, nor will it judge Apple by "how much capital expenditure it made." Apple has one most critical question: In this AI cycle, does it still firmly hold the most important end-user terminal?

This is why Apple's focus this time will be on a more subtle combination: hardware demand, services business, and clarity of AI strategy. Apple guided in its last quarter's earnings report in January for this quarter's revenue growth of 13%–16% year-over-year. Based on this guidance, revenue is estimated to fall in the range of $107.8 billion–$110.7 billion. The current mainstream market consensus is roughly revenue of $108.9 billion and EPS of $1.94–$1.95. S&P Global's preview shows the market expects Q1 iPhone revenue of around $56.5 billion. Meanwhile, Apple's global smartphone shipments grew 5% year-over-year in Q1 2026, capturing a 21% global share. In the Chinese market, iPhone shipments also grew 20% year-over-year. This suggests that, at least before the earnings report, the market hasn't seen clear signs of stalling end-user demand for Apple.

Therefore, the real focus for Apple this time isn't whether it will loudly emphasize AI investment like Microsoft or Google, but whether it can continue to prove: Even without the most aggressive pace in the AI cycle, it still possesses the most important end-user ecosystem, the strongest user base, and the most stable, high-quality profit source. As long as hardware demand is stable, the services business is stable, and its AI narrative is clearer than before, the market will not easily exclude Apple from this tech megatrend.

Apple represents, not the first to materialize AI commercialization, but that the value of the end-user terminal in the AI cycle remains firmly in its hands.

III. Looking Across All Five Companies, the Market is Essentially Performing a "Cross Validation"

If you look at each company in isolation, this week is certainly five separate earnings reports. But if you put them together, you find the market is actually conducting a larger cross-validation. Microsoft checks if AI has formed a closed-loop enterprise payment system; Google checks if conference narratives can quickly translate into dual delivery from Cloud and Advertising; Amazon checks if high investment can coexist with high-quality profits; Meta checks if AI continuously improves mature business efficiency; Apple checks if its terminal and ecosystem position remains solid.

They seem like five different lines, but they all point to the same question: Are the current high valuations of tech leaders built on real delivery, or are they still largely built on expectations? If the answers from the five companies are mostly positive, the market will be more willing to continue pushing up directions related to AI, cloud, advertising platforms, and end-user ecosystems. However, if the results show significant divergence, the market will shift from "broadly raising valuations" to "only rewarding the strongest deliverers."

IV. What Might the Market Reprice After Earnings Season?

After the earnings week, what the market is most likely to reprice isn't a single company, but several major trends.

The first is undoubtedly the AI infrastructure chain: If major tech companies maintain a high capital expenditure trajectory, sectors like data centers, networking, optical interconnects, power, and cooling will continue to receive fundamental support.

The second is the cloud and enterprise AI sector: As long as Microsoft, Google, and Amazon continue to prove enterprise demand exists, the market will continue to view cloud platforms as the core infrastructure for AI commercialization.

The third is internet platforms and advertising efficiency: If Meta and Google continue to prove that AI is improving ad monet