Amazon.com Inc.

10/30/2026 | News release | Distributed by Public on 10/30/2026 10:51

Q3 Earnings: Andy Jassy on why AWS growth keeps accelerating

On Amazon's third quarter earnings call, Amazon CEO Andy Jassy explained how the AWS flywheel is driving demand across core and AI workloads:
In AWS, our plan is working. Despite lapping a comparable year-over-year period where we added a lot of capacity, AWS grew 39.3% year over year, accelerating for the sixth straight quarter, our fastest growth in nearly five years. Backlog is $578 billion, growing triple digits year over year, and well diversified.
We're installing an AI accelerator about every 14 seconds, and almost as fast as we install capacity, customers are gobbling it up. Our Core compute and storage revenue grew at their fastest rates in several years. Our operating margins have long been strong on our Core offering, but rapidly improving on the AI side, too (well ahead of where they were on Core at a similar time of evolution)-even with heightened component costs (like memory) and significant depreciation from the capex we're investing. We continue to accelerate our capex payback, and have even more conviction than we already had that the investment we're making in AWS will yield a much larger revenue and free-cash-flow generating business than we would have imagined a couple years ago, with strong return on invested capital.

Q3 Earnings: Andy Jassy on why demand for Amazon's custom chips keeps growing

Amazon's chips business continues to grow triple-digit percentages year over year, and revenue commitments for Graviton and Trainium have each increased more than 20x year over year.

We have a compelling flywheel spinning in AWS. Borrowing from Jim Collins' flywheel definition in Good to Great, where if you do A, you almost can't help but do B; and if you do B, you almost can't help but do C, and so on… In AWS, having the leading functionality, security, and operational performance can't help but drive customers to run their apps and store their data on AWS, which can't help but drive AWS AI demand (because customers prefer their production inference to be near the rest of their data and apps, which can't help but drive Core AWS demand (because AI uses Core for work like reinforcement learning/post-training/tool-usage), which can't help but drive reinvestment back into our broader AWS functionality.
This is a different model than primarily hosting GPUs or renting short-term datacenter capacity. This is a long-term platform strategy that broadly helps customers invent and evolve their customer experiences, operate stably, and build a reliable partnership they can grow for many years. And, it also yields very attractive long-term economics for us, regardless of supply scarcity.
There are many examples that illustrate our progress in AWS, but I'll share a few.
On the Core side, it's important to remember that the vast majority of Global IT spend (about 85%) is still on-premises, and we're in a 10 to 20 year cycle where that equation will flip to the cloud. Conventional wisdom has been that lynchpin workloads like Mainframes or Storage Array Networks would never move to the cloud. But, these workloads are moving as AWS has built unique cloud substitutes (and AI-driven migration capabilities) to make this transition much easier. And, enterprises get the benefits of less capex, lower operating costs, faster innovation, better developer productivity, and data accessibility to more easily leverage AI.

Highlights from Amazon's third quarter

Amazon announced financial results for its third quarter on October 29. Here's a look at what the company has been up to.

Our Core business has attractive margins because we've learned to run it very efficiently over the last 20 years. As our Core business grows, we keep re-investing in our Core and AI functionality. For example, as customers generate increasingly more data, and seek to get value from it in analytics and AI, the complexity of moving data between data stores and analytics engines is onerous and expensive. With our acquisition of DuckLabs, DuckDB will become the universal SQL dialect of AWS storage and analytics, simplifying data processing with a modern analytics engine that is fast, simple to use, and ubiquitous, and where customers will be able to write SQL queries once, and then execute using any AWS analytics service. For the first time in analytics, customers will have zero migration or portability costs between query engines. This is a big deal and you can imagine how it'll also help agents do efficient querying as well.
On the AI side, we continue to expand the capabilities of our inference service, Amazon Bedrock, and it's leading to remarkable growth, with Fortune 500 companies spending nearly 7x more on Bedrock year over year and total Bedrock token volume growing nearly 17x year over year. Bedrock is the fastest growing multi-billion dollar service in AWS's history. We recently added OpenAI models to Bedrock and usage is growing quickly. We also just added Bedrock-managed versions of Kimi, GLM, and SpaceX models.
You can't have a conversation about AI today without talking about security, and it's another reason customers keep choosing Bedrock. We've designed Bedrock so customers' data remains secure and private. Inputs and outputs are never shared with model providers or used to train base models. When customers tune a foundation model, we create a private copy specifically for their use, and data is fully encrypted, both in transit and at rest.
As frontier models get more powerful, they're surfacing software vulnerabilities previously not found, and at unprecedented rates. We built AWS Continuum to discover, prioritize, validate, and remediate code vulnerabilities at machine speed. It's already being used by customers like Capital One, IBM, Infor, Luminate, and Robinhood. In Q3, we announced that we'll integrate it into the tools where code's being written - Anthropic's Claude Code, OpenAI's Codex, and AWS's Kiro. The interest from customers exceeds anything we've ever seen for a new security service.
Agents continue to be deployed at accelerating rates, many of which are being built on Bedrock AgentCore's building blocks. Tens of thousands of customers currently use AgentCore, deploying 2x more agents with it in Q3 than the prior three quarters combined.
In addition to building their own purpose-built agents, most companies will also use turnkey agentic services, and we offer several that customers love. Kiro for coding, Amazon Connect for contact center agents, and Amazon Transform for migrations-they're all iterating quickly and picking up customer momentum-as is Amazon Quick, our intelligent AI Work Companion, which is growing very rapidly as large enterprises like Mondelez, EchoStar, 3M, Southwest Airlines and DXC are choosing Quick because it's purpose-built for work, with no compromises on customer data.
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