- Microsoft, Alphabet, and Amazon, all report earnings this week.
- Capex is the big focus, with investors eager to see some result from red-hot AI spending.
- Markets will be looking for continued proof of AI monetization to justify capex.
AI spending is once again the big issue heading into mega-cap tech earnings.
Three hyperscalers worth a collective $10 trillion in market cap will report Q3 earnings in the coming days — Microsoft and Alphabet on Wednesday, and Amazon on Thursday — and investors will have another opportunity to express how they feel the still-blistering pace of AI spending.
"While we're expecting strong results across the board, the focus is less about the actual earnings results than about whether the Capex spending for AI growth will translate into sustainable revenue growth for these companies, which remains a big question mark," said Chris Brigati, chief investment officer at SWBC, on Tuesday.
Here's how much each firm has so far said they plan to spend:
Microsoft
- $175 billion in 2026, and $50 billion in Q1 2027
Alphabet
- $195 billion-$205 billion in 2026, no exact guidance for 2027
Amazon
- $220 billion in 2026, no exact guidance for 2027
An approach of continuously increasing AI spending has been met with mixed reception from investors, who have started to demand a clearer path to monetization and have punished firms they think are spending too aggressively.
Rising interest rates have also increased the cost of borrowing to fund the AI buildout, making monetization even more important.
Neoclouds like CoreWeave have run into this issue recently, with volatility spilling over into both its stock and bonds. However, hyperscalers are in a stronger financial position to spend, since they already have established revenue lines that they can draw on to fund their investments, as well as clearer paths to tap the equity and debt capital markets for more funding.
Here's where Wall Street consensus is on the key AI monetization stats to watch:
Microsoft
- Expected growth of around 45% in its Azure cloud business
Alphabet
- Expected revenue growth of around 100% in its Google Cloud business, which grew 82% year-over-year in Q2
Amazon
- Expected growth of around 38% for its AWS cloud business
Still, it's a tricky line to walk for AI's biggest spenders. Investors want it both ways as the AI capex cycle drags on; they're looking for optimism around the returns on such high spending, while also worried that companies are throwing all their free cash flow at big AI projects.
Put another way, the market is worried about the effect of too much and too little AI spending.
If tech firms continue to dump huge sums of money into AI, investors punish them. Yet, if they cut their spending, they risk falling behind competitors on AI development, hurting themselves in the long run.
Any sign of a pullback has also sparked fears about other parts of the trade, like infrastructure and data centers, which rely on big outlays of capital from AI companies.
Meta's earnings report last week gave hyperscalers an updated window into just how sour investors still are on companies capex outlooks.
Despite the hype around surging usage of Meta's agentic AI assistant, Muse, investors sold the stock after the company raised the lower end of its capex range for full year 2026 to $135 billion to $145 billion.
With this in mind, hyperscalers might try to use Microsoft's "goldilocks" Q2 earnings playbook. Back in July, the company showed it was monetizing AI through its growing Azure cloud business profits. Simultaneously, it kept future spending in line with previous expectations — not overdoing and not underdoing it, but keeping capex levels "just right."
Not everyone thinks rising capex announcements will be a negative, however, even considering the negative reaction to Meta's updated expectations last week.
"We expect these three prints to calm the tape rather than feed it," said Dan Ives, the founder of Yorkville Ives known as one of the biggest tech bulls on Wall Street, in a client note on October 23.
"Roughly $850 billion of hyperscaler AI spend this year sits against more than $2 trillion of cloud backlog growing faster than revenue, so capacity, not demand, is the constraint," Ives continued. "We expect capex guides to move higher again, with the spend backed by contracted demand rather than capacity built on spec."
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