Key Points
-
Alphabet recently increased its 2026 capital expenditure guidance due to surging demand for compute.
-
Hyperscalers are racing to build AI infrastructure to fuel the AI boom.
-
Capital expenditures drain free cash flow.
Amazon (NASDAQ: AMZN) will announce its second‑quarter 2026 earnings after the market closes on Thursday, July 30. After the release, CEO Andy Jassy and the Amazon leadership team will host a live earnings conference call with Wall Street analysts.
As a member of the “Magnificent Seven” and a leading hyperscaler, Amazon is among the world’s largest companies driving the artificial‑intelligence revolution.
All eyes will be on the company as it seeks to balance massive AI‑infrastructure investments with the concerns of increasingly cautious shareholders.
My expectation is that Jassy will raise Amazon’s full‑year 2026 capital‑expenditure (capex) guidance following the earnings release.
Signs from several directions
Early in the second‑quarter earnings season, there are already several signals that Amazon is likely to lift its capex outlook.
Recently, Alphabet reported its Q2 2026 earnings, raising its full‑year capex guidance from a range of $180 billion to $190 billion up to $195 billion to $205 billion, bringing it in line with—or above—Amazon’s current $200 billion guidance.
Alphabet’s CFO, Anat Ashkenazi, said the increase “is primarily due to an acceleration in the delivery of capacity to meet growing demand.” Alphabet also lifted its 2026 capex forecast in the first quarter, whereas Amazon has not, but both firms are major players in the cloud market.
Alphabet’s shares slipped on the higher capex outlook, and Amazon’s stock also declined as investors braced for near‑term headwinds.
While capex is essential for building the AI infrastructure that will power the boom, hyperscalers have already strained their balance sheets, with many projecting negative free cash flow over the next few years. Yet they are beginning to see returns, as Alphabet reported an 82 % year‑over‑year increase in cloud‑business revenue in Q2.
Investors worry that the combined $700 billion‑plus that the Magnificent Seven are expected to spend on capex in 2026 may not generate sufficient returns.
In the first quarter, Jassy sought to reassure investors that the company is not gambling on AI but merely responding to staggering demand: “We continue to be confident in the long‑term capex investments we are making,” he said during the earnings call. He added:
Of the AWS capex we intend to spend in 2026, much of which will be installed in future years, we have high confidence this will be monetized well, as we already have customer commitments for a substantial portion of it and that it will yield compelling operating margins and ROIC [return on invested capital].
Additionally, Jassy said the company would not hesitate to increase near‑term capex if Amazon Web Services (AWS) continues to demonstrate rapid growth.
Jassy also noted that AWS capex is spent on items such as land, power, buildings, chips, servers, and networking gear before they can be monetized. The spend typically translates into revenue six to 24 months later.
Memory prices have also risen sharply recently, meaning companies like Amazon may need to allocate more for NAND flash memory and dynamic random‑access memory (DRAM), which feeds data to the graphics‑processing units (GPUs) in data centers.
Image source: The Motley Fool.
The market is prepared
The reaction of Amazon’s shares after Alphabet raised its capex guidance shows that the market is already anticipating a possible increase in Amazon’s 2026 capex outlook when it reports earnings.
If Amazon maintains its $200 billion capex guidance, the stock could react favorably, as the market is braced for a hike. However, a meaningful increase in guidance could put pressure on the share price.
It remains uncertain how the AI narrative will unfold, but companies such as Amazon are investing heavily with confidence that their investments will pay off.
Investors should focus less on short‑term capex figures and instead assess whether the AI demand we see today is sustainable and likely to grow, or whether the AI story is already in a later stage than some observers believe.