Amazon just dropped its Q3 earnings, and while the top-line numbers beat Wall Street expectations with $180.2 billion in revenue, the real story is the thunderous return of Amazon Web Services. After a period of sluggishness that had investors worried Amazon was losing the AI arms race to Microsoft and Google, AWS roared back to life, posting 20% year-over-year growth—a pace not seen since 2022.
CEO Andy Jassy made it clear that this isn't a fluke. "AI drives meaningful improvements in every corner of our business," he said in a statement. The evidence is in the numbers and the tech. AWS sales hit $33.0 billion, fueled by what the company describes as "strong demand in AI and core infrastructure." This demand is being met by a massive build-out, including custom silicon like its Trainium2 AI chip, which Amazon claims is now a multi-billion-dollar business that grew 150% in a single quarter.
The company is also flexing its AI muscle with Project Rainier, a colossal compute cluster with nearly 500,000 Trainium2 chips dedicated to training Anthropic's Claude models. This, combined with new AI business tools and a contact center AI solution that's now a $1 billion run-rate business, paints a clear picture: Amazon's expensive, long-term bet on building its own AI ecosystem is starting to pay serious dividends.
The high cost of an AI future
Despite the blowout quarter, Amazon's stock dipped slightly in after-hours trading. Investors are likely eyeing the costs behind the curtain. The company's operating income was hit by a $2.5 billion legal settlement with the FTC and another $1.8 billion in severance costs tied to recent layoffs.
Those layoffs, which have cut 14,000 corporate jobs, loom large over the AI-powered success story. While Jassy frames the cuts as creating a "leaner" culture, it's hard to ignore the timing as the company pours an estimated $125 billion into capital expenditures this year, largely for AI and automation. The Amazon Q3 earnings report shows a company successfully navigating economic headwinds by leaning into AI, but it also reveals the steep price of that transition—both in capital and, potentially, in its human workforce.
