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AWS grew 39% and beat forecasts, yet Amazon missed on revenue and earnings while free cash flow swung negative by $42.4 billion. The question now is whether AI spending discipline can catch up to AI spending ambition.
Amazon's third-quarter report, released Thursday, delivers a familiar split screen for anyone tracking the AI infrastructure buildout: the cloud division is firing on all cylinders, while the rest of the balance sheet shows the strain of funding it.
Net sales rose 12% to $201.9 billion, just short of the $202.2 billion analysts polled by FactSet had expected. Earnings per share came in at $1.89 against a forecast of $1.97. Neither miss is dramatic on its own. Together, though, they set a cautious tone for a quarter that was supposed to showcase Amazon's AI payoff.
AWS was the payoff. Cloud revenue hit $45.98 billion, beating the $45.29 billion consensus estimate, and grew 39% year over year. AWS operating income climbed to $17.8 billion from $11.4 billion a year earlier, a margin expansion that should reassure anyone questioning whether cloud profitability can keep pace with its growth. This marks the sixth straight quarter of accelerating AWS growth, according to Bloomberg, a streak that CEO Andy Jassy was eager to highlight on the earnings call.
The bigger story, and the one that sent shares down roughly 6% in after-hours trading, was cash. Free cash flow fell to negative $42.4 billion on a trailing 12-month basis. A year ago, the same measure stood at a positive $14.8 billion. That swing of nearly $57 billion is the clearest evidence yet of how aggressively Amazon is funding its AI ambitions, and how little patience the market has left for spending without visible near-term return.
Amazon reiterated it still expects roughly $220 billion in cash capital expenditures for full-year 2026, the majority of it going toward AWS. Jassy told analysts the company plans to spend "meaningfully more" in 2027.
Put that $220 billion next to Amazon's own fourth-quarter guidance. The company forecasts net sales of between $240 billion and $247 billion for the period, typically its strongest quarter thanks to holiday shopping. In other words, Amazon expects to spend nearly as much on capital expenditures for the entire year as it expects to generate in revenue during its single biggest sales quarter. That is an extraordinary ratio for a company of Amazon's scale, and it explains why analysts pressed Jassy repeatedly on the call about margins, demand signals, and the timeline for returns.
Jassy's answer leaned on scale and ambition rather than near-term reassurance. He called the current AI cycle a "once-in-a-lifetime opportunity" and argued the investment was necessary to defend AWS's position. "We're going to invest to continue being the leader," he said. "We can fund this plan, and I think it will forever change the size of Amazon."

He went further, forecasting AWS growth north of 40% in both 2027 and 2028, and reiterating his belief that the division could become the first trillion-dollar revenue business within five to ten years. AWS currently sits at a $184 billion annualized run rate, he noted, which gives some mathematical plausibility to the long-term target even if it requires years of sustained compounding to get there.
Jassy also framed enterprise AI adoption as still nascent. "We're in the very early days," he said, adding that the current strategy "is working." That framing matters for investors trying to decide whether today's spending is front-loaded infrastructure for a market that is still forming, or overcommitment to a demand curve that could flatten.
Amazon is not alone in this spending pattern. Microsoft just posted its tenth consecutive quarter of record-breaking revenue, driven largely by its own cloud business, and has spent heavily to get there. Industry-wide capital expenditures tied to AI infrastructure are now projected to top $1 trillion in 2027 across major cloud providers, according to CNBC reporting. The difference, for now, is that Microsoft's spending has not produced the kind of negative free cash flow swing Amazon just reported. That contrast is likely to keep coming up in comparisons between the two companies for the next several quarters.
The capex commitment also underscores how AWS has become central to Amazon's broader financial identity. A separate note on Amazon's relationship with Anthropic suggests the company's AI infrastructure bets extend beyond its own cloud buildout into equity stakes that could pay off even more than Anthropic's own investors stand to gain, should that company eventually go public. Whether that optionality offsets near-term cash burn is a question investors are still working through.
The immediate signal to track is whether AWS's margin expansion continues to outpace its capex growth. Operating income growth from $11.4 billion to $17.8 billion year over year is a strong number, but it needs to keep climbing at a similar clip relative to the $220 billion spending base for the investment thesis to hold.
Free cash flow trajectory matters just as much as the AWS growth rate. A single quarter of negative $42.4 billion on a trailing basis is tolerable if it is temporary and tied to a defined infrastructure buildout. It becomes a structural problem if it persists into 2027 alongside the "meaningfully more" spending Jassy has already flagged.
Watch guidance revisions closely heading into the holiday quarter. Amazon's $240 billion to $247 billion fourth-quarter sales forecast will be the first real test of whether retail demand can help offset the capital intensity of the AI buildout, or whether the company is increasingly a cloud and AI infrastructure story wearing a retailer's balance sheet. For a stock that dropped 6% on this report alone, the market has made clear it wants evidence of discipline, not just ambition, before it extends further patience.
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Amazon reported booming cloud revenue but otherwise missed expectations | TechCrunch
↗ https://techcrunch.com/2026/10/29/amazon-reported-booming-cloud-revenue-but-otherwise-missed-expectations
About the author
Marcus began tracking AI's market implications in 2016, noticing AI-related patent filings accelerating ahead of earnings upgrades before most of the sell-side had caught on. A former fixed-income quantitative analyst, he spent two decades building models that priced risk across emerging markets before pivoting to cover the economic impact of AI full-time. His writing translates opaque technical developments into clear risk/reward terms — and he's rarely diplomatic about the gap between AI valuations and underlying fundamentals. He believes most market participants still underestimate AI's long-run deflationary effect on knowledge work.
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30 October 2026
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