During the latest tech earnings season, investor attention has zeroed in on hyperscaler capital expenditures for AI infrastructure, with Amazon’s AWS division leading the charge. Analysts estimate Amazon will allocate upwards of 20% of its total capex budget—roughly $50 billion in 2026—to build and expand AI data centers powered by its in-house Trainium and Graviton chips. This investment supports anticipated AWS growth of 25% year-over-year in Q4, reinforcing Amazon’s positioning as a top AI infrastructure provider. Management has signaled that disciplined spending on these facilities will be balanced by ongoing efficiency gains, aiming to sustain AWS operating margins north of 30% by the end of the year.

Amazon invested $40 million to acquire distribution rights for the ‘Melania’ documentary and committed an additional $35 million to its theatrical marketing campaign. The film grossed an estimated $7 million during its U.S. opening weekend—surpassing pre-release projections of $2 million to $5 million—but faces an uphill battle to recoup its $75 million investment. Early international results have been underwhelming, with the U.K. tally at $44,960 (155 cinemas) and Italy at $7,696 (94 cinemas). While the documentary achieved one of the strongest domestic openings for its genre in a decade, weak critic ratings (sub-10% on Rotten Tomatoes) and sharp second-weekend declines are expected to pressure overall profitability.

Amazon’s recent announcement of roughly 16,000 corporate job cuts—on top of earlier headcount reductions—has been partly attributed by management to efficiency gains from AI deployment across its businesses. In Washington state alone, nearly 2,200 roles in core product development and engineering were eliminated. Although Amazon encourages widespread use of its internal AI tools, economists note that the true impact of AI on labor productivity and headcount remains difficult to isolate. Critics argue that some cuts reflect broader cost-containment efforts rather than direct AI-driven redundancy, underscoring the complexity of attributing workforce changes purely to technological automation.