For much of 2026, investors viewed Big Tech's record AI capital expenditures as a potential drag on valuations. But recent earnings reports from Microsoft, Amazon, Alphabet, and Meta suggest the tide may be turning, with demand for AI services finally catching up to the infrastructure build-out.
In their latest quarters, Microsoft's Azure grew 43%, Amazon Web Services (AWS) rose 37%, and Google Cloud surged 82%. Meta also posted a 28% revenue increase. These figures are providing fresh evidence that the billions poured into data centers are beginning to translate into tangible revenue growth.
From Spending Concern to Growth Catalyst
The combined capex for these four tech giants is projected to reach $730 billion to $760 billion in 2026, according to Janus Henderson, with roughly $430 billion expected in the second half. For months, this spending weighed on free cash flow and caused hyperscalers to lag behind the semiconductor rally. However, the latest numbers have shifted the debate.
Microsoft's commercial remaining performance obligations hit $678 billion, while Google Cloud's backlog reached $514 billion. Janus Henderson estimates the three largest cloud platforms now hold more than $1.6 trillion in contracted backlog. This growing pipeline suggests that capacity being brought online today can convert into higher revenue over the next several years.
Monetization Phase Approaches
The investment thesis is no longer just about strong AI demand; it's about the ability to monetize that demand. Microsoft noted that customer demand still exceeds available Azure capacity, while Alphabet raised its 2026 capex forecast to $195 billion-$205 billion due to faster-than-expected demand. AWS growth accelerated to 37% as more AI workloads moved into production.
Richard Clode of Janus Henderson expects profit and cash-flow growth at hyperscalers to begin outpacing incremental capex growth by late 2027 into 2028. That would mark a pivotal shift: spending that previously compressed free cash flow would start generating stronger returns for shareholders.
Scale as a Differentiator
Despite the optimism, risks remain. Alphabet reported negative free cash flow of $5.9 billion in the second quarter, while Meta generated just $784 million as infrastructure spending surged. Meta expects 2026 capex of $130 billion-$145 billion. These figures underscore the heavy financial commitment required to stay competitive in AI.
As the AI trade evolves, companies with scale, deep customer relationships, and control over their infrastructure may be better positioned to reap the benefits. Capital Group's John Lamb argues that investors shouldn't view chipmakers and hyperscalers as an either-or choice. Both can benefit as spending flows through the AI ecosystem, but their return profiles will differ as new capacity starts generating revenue.
The market still needs proof that returns can justify the massive sums involved. But with cloud growth accelerating and backlogs swelling, Big Tech's AI capex is beginning to look less like the problem investors feared and more like a reason earnings could keep growing. For context, Nvidia's recent gains reflect similar optimism about AI spending, while some investors remain cautious about the sustainability of this spending. Meanwhile, Microsoft's strength has helped offset concerns about Meta's capex, and other companies' AI investments are also signaling broader demand.
This article is for informational purposes only and does not constitute financial advice.
