Source-led article
Investors reward Amazon for AI cloud spending as AWS revenue surges 37%
Amazon reported better-than-expected second-quarter earnings on Thursday, and investors responded by sending the stock up nearly 10% in after-hours trading. Net sales rose 20% year over year, driven largely by a 37% surge in AWS revenue to $42 billion for the quarter.
The results offer a clear signal about the current state of AI investment: cloud hosts that can show growing revenue alongside massive infrastructure spending are winning investor confidence, while AI labs and startups without matching revenue streams continue to face scepticism.
AWS revenue and capex climb together
Amazon spent $173 billion on property and equipment in the fiscal year ended June 30, up from $107.65 billion the previous year. That category covers GPUs, natural gas turbines and land for data centres. The company also raised its 2026 capital expenditure forecast from $200 billion to $220 billion, even as it began drawing down cash reserves. Amazon ended the quarter with $7.6 billion less cash than 12 months ago, marking its first period of negative free cash flow this year.
Under normal circumstances, such ballooning expenses would alarm investors. But AWS revenue growth of 37% year over year, reaching $42 billion for the quarter, helped justify the spending. While that revenue does not balance the capex arithmetic directly, it shows demand growing alongside supply — a critical reassurance given the years-long lag between breaking ground on a data centre and selling its capacity.
Datos clave
| Metric | Q2 2026 | Year-over-year change |
|---|---|---|
| Net sales growth | 20% | +20% |
| AWS revenue | $42 billion | +37% |
| Property and equipment spend (fiscal year) | $173 billion | +60% |
| 2026 capex forecast | $220 billion | +10% from prior forecast |
AI chip bets and the Bedrock strategy
Amazon’s AI play extends beyond building large data centres. The company is making long-term investments in custom chips such as Trainium and the Arm-based Graviton processor. These projects do not appear directly in capex numbers but can meaningfully improve margins for the cloud business over time.
During the Q2 earnings call, CEO Andy Jassy said: “We see the AI business following very much the same margin trajectory we saw in the core business before.” He added that “AWS and Amazon Bedrock can have a wildly successful business without its own frontier model, and the reason is that there’s not going to be a single model to rule them all.”
That positioning — offering infrastructure and model-agnostic services rather than building a single frontier AI model — appears to resonate with investors who want revenue visibility over speculative AI bets.
Cloud hosts favoured over AI labs
The pattern is not unique to Amazon. Microsoft and Google also saw their shares rise after reporting strong cloud revenue. By contrast, Meta’s stock fell 8% after its earnings this week, as investors focused on its cash flow crunch and continued spending without a clear matching revenue source.
This divergence reveals a broader dynamic in the AI economy. Investors are treating cloud hosts as the most reliable part of the AI stack, while remaining sceptical about the underlying economics for AI labs and startups. However, as the TechCrunch analysis notes, Amazon’s hosting revenue is someone else’s AI bill. In Anthropic’s case, the same money cycles through Amazon’s investment in the lab and back to AWS as cloud spending.
What this means for Indian AI and cloud users
For Indian enterprises, startups and developers relying on AWS for AI workloads, the results suggest that Amazon will continue to invest heavily in capacity and performance improvements. The company’s chip investments could eventually lower costs for Indian customers running AI inference or training on AWS. However, the sustainability of this spending depends on whether downstream AI demand holds up. If AI labs and their clients cannot sustain their own spending, cloud revenue will eventually be affected.
The broader lesson for India’s AI ecosystem is that infrastructure providers are currently winning the investment narrative, but the entire stack remains interdependent. Indian AI startups consuming cloud services should watch both their own unit economics and the health of the global AI demand cycle.