Supply Shortages and Inflation Drive Up Big Tech AI Capital Expenditure
As Big Tech prepares to report earnings, investors must scrutinize whether soaring capital expenditure forecasts reflect genuine artificial intelligence expansion or merely the rising cost of scarce data center resources.
Big Tech companies are preparing to announce their latest financial results, with capital expenditure forecasts taking center stage over traditional revenue metrics. Google, Amazon, Microsoft, and Meta have already committed to deploying over $700 billion this year, predominantly targeting artificial intelligence infrastructure.
However, the purchasing power of that massive investment is deteriorating. Morgan Stanley estimates that constructing one gigawatt of AI computing capacity now costs approximately 20 percent more for several leading systems due to supply constraints.
For instance, a standard Nvidia-based configuration has jumped from roughly $29 billion to $35 billion per gigawatt. A more advanced iteration of that same setup has climbed from $41 billion to $49 billion per gigawatt.
This dynamic has created a self-reinforcing cycle of demand and inflation. As technology giants aggressively order data center equipment, shortages in memory chips, power infrastructure, construction materials, and skilled labor worsen, driving prices even higher.
Brad Gastwirth, head of research at Circular Technology, warns that market participants must parse these spending figures carefully. "Investors need to be careful when interpreting higher capex," he noted, emphasizing that there is "absolutely an inflation component" to the current spending surge.
This distinction is critical for market valuation. Previous research indicates that escalating memory chip prices alone could account for roughly 45 percent of the capital expenditure growth seen among major cloud providers this year.
Looking ahead, Cantor Fitzgerald analysts anticipate that current earnings reports will show minimal adjustments to 2026 spending plans. However, projections for 2027 are expected to surge, with estimates reaching $283 billion for Google, $271 billion for Amazon, and $200 billion for Meta.
A sudden pullback in spending remains unlikely, as no major player wants to signal caution while competitors accelerate their artificial intelligence ambitions. The key for market professionals will be listening for specific operational details alongside the headline spending numbers.
Gastwirth advises monitoring management commentary closely for those specific operational details. "When the companies discuss capex, I'd pay close attention to whether they're also talking about power capacity, GPU deployments, memory purchases, networking, and new data center campuses," he said, adding that if spending rises alongside those metrics, it points to genuine expansion rather than simply higher costs.
