Every cloud beat. Every capex forecast rose. That is the two-sentence summary of the biggest earnings day of 2026, and it tells you almost everything you need to know about where Big Tech’s AI infrastructure spending actually stands right now.
Microsoft, Alphabet, Meta, and Amazon collectively committed somewhere between US$630 billion and US$650 billion in capital expenditure for 2026. Q1 was the first real accounting of whether those bets are generating returns. The answer, across all four calls, was yes. The follow-up, also across all four calls, was: we’re spending more.
Microsoft: Azure re-accelerates, capex forecast rises to US$190 billion
Microsoft beat on every major line. Revenue came in at US$82.9 billion, up 18% year on year. The number investors were actually watching was Azure, guided at 37% to 38% constant currency growth; it came in at 40%, beating analyst consensus expectations of 38.8% from CNBC and 39.3% from StreetAccount.
Microsoft’s annualised AI revenue has now exceeded US$37 billion. Microsoft Cloud revenue for the quarter reached US$54.5 billion, up 29%, with commercial remaining performance obligations growing 99% to US$627 billion. Satya Nadella framed the quarter around what he called “the agentic computing era,” a phrase that signals where Microsoft sees the next phase of enterprise AI demand.
The complication: CFO Amy Hood raised the full-year fiscal 2026 capex forecast to US$190 billion, well above the roughly US$154.6 billion analysts had previously expected. Capital expenditures for the quarter were US$31.9 billion, up 49% year on year. The stock slid more than 3% in after-hours trading despite the operational beat, which tells you where investor attention currently sits.
Management guided Q4 Azure growth at 39% to 40% constant currency, signalling further acceleration into the second half of the calendar year as data centre capacity comes online.
Alphabet: Google Cloud surges 63%, capex guidance raised
Alphabet delivered its highest quarterly revenue growth rate since 2022, with total revenue growing 20% year on year. Google Cloud was the headline: revenue grew 63% from a year earlier, well above analyst expectations, driven by Google Cloud Platform growth across enterprise AI solutions and infrastructure. Net income for the quarter came in at US$62.57 billion, or US$5.11 per share–up 81% year on year.
CEO Sundar Pichai acknowledged directly on the earnings call that the company is “compute constrained in the near term”, a phrase that reads less as a warning and more as confirmation that demand is outpacing even Alphabet’s ability to build fast enough. Alphabet updated its 2026 capex guidance to US$180 billion to US$190 billion, up from the prior US$175 billion to US$185 billion range, and CFO Anat Ashkenazi said 2027 capex is expected to “significantly increase” compared to 2026.
Meta: revenue up 33%, capex guidance raised again
Meta reported Q1 revenue of US$56.31 billion against analyst estimates of US$55.45 billion–growth of 33% from a year earlier, its fastest quarterly growth since 2021. EPS came in at US$6.79, above the US$6.82 consensus. Mark Zuckerberg called it “a milestone quarter.”
The capex line is where the story gets complicated. Meta raised its full-year 2026 capex guidance to US$125 billion to US$145 billion, up from the prior range of US$115 billion to US$135 billion, citing higher component pricing and additional data centre costs. Actual Q1 capex came in at US$19.84 billion, below the US$27.57 billion analyst estimate, which initially read as a positive before the full-year raise registered.
Meta’s AI-powered ad business, Advantage+, continues to be the primary mechanism through which AI infrastructure spending produces near-term returns for the company. The 33% revenue growth suggests that the machine is still working. The open question is how long the ad business can fund a capex commitment that now rivals the GDP of a small nation.
AWS: fastest growth in 15 quarters
Amazon’s result was arguably the cleanest of the four. AWS revenue reached US$37.59 billion in Q1, up 28% year on year against analyst expectations of US$36.64 billion, its fastest growth rate in 15 quarters. Operating income hit US$14.2 billion at a 37.7% margin, well above the US$12.84 billion StreetAccount consensus.
CEO Andy Jassy noted in his statement that Amazon’s chips business topped a US$20 billion revenue run rate, growing triple digits year on year, a figure that signals AWS’s custom silicon investment in Trainium and Inferentia is beginning to produce meaningful scale. Amazon announced new AWS partnerships with OpenAI, Anthropic, Meta, NVIDIA, and Uber alongside the results.
Total Amazon revenue for the quarter reached US$181.5 billion, up 17%, with net income of US$30.3 billion.
What the numbers actually say about AI infrastructure spending
Taken together, these four results make a coherent argument. AI infrastructure spending is generating real revenue acceleration across cloud businesses; Azure at 40%, Google Cloud at 63%, AWS at 28%, at a pace that, for now, justifies the scale of the build-out.
The consistent thread across all four calls is that demand is supply-constrained. Microsoft said so explicitly on capacity. Alphabet’s Pichai said it outright. AWS has been signalling the same dynamic for two quarters. That is a very different problem from the one investors feared going into earnings, a world where the infrastructure was built, and the customers didn’t come.
The question the market is wrestling with in after-hours trading is not whether AI is generating revenue. It clearly is. The question is the trajectory of the capex commitments themselves, all of which were raised tonight, not held steady. Microsoft’s US$190 billion full-year forecast and Alphabet’s signal that 2027 will be even higher are the numbers that sent both stocks lower despite the operational beats.
The AI infrastructure spending supercycle is not over. If anything, tonight’s calls confirm it is still accelerating and that the companies running it believe the demand on the other side will catch up.
See also: Big tech’s $320B AI spend defies efficiency race
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