Quarter 1
Q1 2026 Earnings Call — April 29, 2026
first question comes from the line of Eric Sheridan with Goldman Sachs. Please proceed with your question. Thanks so much for taking the question. You know, Andy, across an array of announcements you've made recently with AWS and reflecting upon what you wrote in the shareholder letter, can you talk a little bit about the needed levels of investment over the next couple of years to scale compute and capacity to meet your current state of revenue backlog? and how we should be thinking about your unique approach to custom silicon and AI infrastructure that maybe positions you competitively to build that scale. Thanks so much. Yeah, well, to your point, Eric, we've made a lot of announcements over the last several months, and we're really pleased with the growth that we're seeing in AWS right now. You know, 28% year over year, fastest growth rate in 15 quarters for us, haven't grown at this pace since we were about half the size. And growing 28% on a $150 billion annual run rate basis is not simple to do. And I think there's a few things around it.
You know, first is just, we continue to see people choosing AWS for AI, in part because of our really broad full stack functionality, in part because people want their inferences, they scale it to be close to their data and their applications. So much more of it lives in AWS and elsewhere. And in part because we have the strongest security and operational performance. And that's just what you can see it in our numbers. It's leading to very substantial AI growth. And then at the same time, we're seeing very significant growth in our core business. And some of that are the migrations that have picked up from enterprises, from on-premises to the cloud. But a lot of that is also as AI growth is exploding, it turns out that it leads to a lot of core growth as well. All the post-training, all the reinforcement learning, all the agentic actions and tool usage that these agents are using.
And it fits with what you're asking about on the chip side, which is because we have an unusual collection of chips, we have the leading CPU chip and Graviton, and we have the leading price performance silicon AI chip and Tranium, it means that we're really unusually well position for the inflection that we're seeing and the type of growth that we're experiencing. And so, you know, I don't have an update on a new update on capital. Our plan is largely the same, but we do view this as truly a once in a lifetime opportunity where every application that we know of is going to be reinvented. And there are so many new applications that none of us have ever imagined or dreamed we could build that are starting to be built and will be built And all of that is going to be built on top of AI with a lot of consumption of CPUs and core as well. So I expect that we will invest a significant amount of capital over the coming years to pursue that opportunity and that our customers, our shareholders, and Amazon in general are going to be much better off down the road because we did so. And
the next question comes from the line of Brian Novak with Morgan Stanley. Please proceed with your question. Great. Thanks for taking my questions. I have two. One is on the accounting side. We'll probably get it in the queue, but can you just give us an update on what the AWS backlog looks like and sort of any visibility on the breadth of that backlog beyond the big labs? That's the first one. And then the second one, as you sort of think about milestones for Rufus and agentic commerce for you in 2026, What are you most focused on making sure you accomplish on the agentic side this year just to make sure you stay at the nice edge of the agentic commerce offerings? Thanks. Yeah, on the backlog, the backlog for Q1 is $364 billion. That does not include the recent deal that we announced with Anthropic for over $100 billion. There's reasonable breadth in that as well. It's not just one customer or two customers. On the agentic commerce milestone question, we are very bullish on what agentic commerce will look like. I think it's going to be very good for customers in the long term. I think it'll be good for us too.
And you can see some of that focus from us in what we're building with Rufus. If you haven't checked out Rufus in a while, it's really substantially improved over the last year. And we have a lot of customers using it, as I mentioned Earlier, you see the monthly active users up over 115% in Rufus and the engagement up over 400% year over year. And I think while I think we'll do a lot of work with third-party horizontal agents to try and make that customer experience better. And by the way, I do think today it reminds me in some ways the stage we're in. of what we saw in the early days of search engines, and they're trying to refer business to e-commerce. It's never been a giant part of the referrals to our e-commerce business, but over the years, the experience got better. And what you see with agentic commerce is it's a small fraction of what we see with the search engine referrals, but the experience just hasn't gotten great with these third-party horizontal agents yet. They're not often able to get the pricing right or the product information right. They don't have any personalization data or any shopping history.
And so we do want to see that get better with third-party horizontal agents. We're having conversations with all those folks to try and make that better and find something that works for customers and all the companies. And then it'll be interesting over time which agents customers choose to use. I happen to think that if you're going to a particular retailer that you like to do business with and you like to shop from, if they have a great agentic shopping assistant, you're going to often start there because it's where you're doing your shopping. They have better product information. They have better information about what other customers like you are buying. You can make all sorts of changes to how your account and your shipping information is working there. You know, that's what we're aiming to make Rufus be, is we're aiming to have it be the best shopping assistant anywhere, and I think we're on that path.
Thank you.
The next question comes from the line of Justin Post with Bank of America. Please proceed with your question. Thank you. I'd like to ask two, one on models and then one on perineum chips. So on models, it looks like you might have access to the full suite of OpenAI models on Bedrock. Just wondering how big of an unlock that is and how focused maybe you are on your own NOVA model. And then second, shareholder letter mentioned you might be able to sell racks of Tranium. Just wondering, you know, with your capacity constraints, how do you think about timing of that and how big of an opportunity? Thank you. Yeah, on the models question, I think the fact that we're going to have all of the OpenAI models available in Bedrock is a big deal. It's a big deal for customers. We obviously have a very large amount of AI being done in bedrock today on the models we have. This is Anthropic and Lama and Mistral and a host of others. The one thing you learn over and over again with every technology, who's true in databases, It's true in analytics. It's true in models. It's true in chips, too, by the way, is that customers want choice. There is not one tool to rule the world, and they want choice.
And each of the models are better at some things than the other models. And so people for a long time have wanted to consume open AI models in bedrock. We just enabled yesterday the stateless model, the 5.4 model. and will enable the most recent 5.5 model in the next couple of weeks. And most of the model work and most of the AI has been done in these stateless models, tokens in and tokens out. And while I think there will continue to be lots of work done that way, I think the future of using these models is a stateful model, a stateful API. And that's because when you're building agents, you're building AI applications, you don't want to start anew every time you interact with the model. You want to store state. You want to store identity. You want to store what the conversation or the actions have been. You want to reach out and do a little bit of compute here. You want to have the models reach out to the different tools to accomplish different tasks. That only happens if you're able to store state.
The Bedrock Managed Agents that we collaborated with and invented with OpenAI that we just announced a preview of yesterday is also, I think that's the future of how these agents are going to be built. It's something that nobody else has, and I think it's very exciting to our customers. And of course, we'll have other models like Codex and things like that as well. So I think it's a big deal for customers, and I think it's going to be good for our business as well. On the question about Tranium and the notion of our selling racks over time, I do think that's very much a possibility. You know, always we have to balance. We have such demand right now for Tranium and we have such demand from various companies who will consume as much as we make that we have to decide how much we're going to allocate to the existing demand and customers, how much we're going to save to sell as racks and And for our existing customers that we sell Tranium to, how many will be Tranium plus running on our cloud infrastructure versus just the chips themselves? But I expect over time there's a good chance we're going to sell RACs over the next couple of years. And
the next question comes from the line of Rob Sanderson with Luke Capital Markets. Please proceed with your question. yeah thank you good afternoon and thanks for taking the question um i wanted to ask a little bit about amazon leo um can you maybe help dimensionalize some of the you know the revenue opportunity in the consumer and uh in the enterprise space over the next few years what are the governors on the ramp um could you talk about types of new services that you will be able to develop with the global star infrastructure and the spectrum that maybe you couldn't address before or would take you and you can get to more quickly now and And then how expansive is the longer term vision? I know you're just beginning to launch commercial services, but over the long term, do you expect to include your non-communication services like orbital data centers or things like that as this becomes feasible in the decade ahead? Yeah, I'll try to address as many of those questions as I can. I am very bullish about Amazon Leo and the opportunity there. There are billions of people around the world who do not have access to broadband connectivity.
And there are many thousands of businesses and government assets that people don't have visibility to because they don't have the right connectivity. And it means that those entities can't do a lot of the things that we all take for granted today, including education online, business online, shopping or entertainment online, having constant visibility and digital twins. There's all these things that they can't do today. And so we think that Amazon Leo is going to help solve that problem. I think when we launch our service commercially, and we've got, you know, we just had another launch this week, so we have over 250 satellites in space. When we launch that service commercially, it will be one of two offerings that are on the current technology edge. And I think that we will have a meaningful advantage in performance. I think we'll be about two times better on the downlink than existing alternatives and about six times better on the uplink performance than existing alternatives. I think we'll have a cost advantage for customers.
And then for the governments and the enterprises, and we talked to a lot of them and we have already signed agreements with many of them, even though we haven't launched the service commercially, you know, the latest of which was Delta Airlines. um, committing at least half of their fleet starting in 2028. When you talk to them, another really big part of what matters to them is they're going to want to take this data off of the satellite constellation and they're going to want to store it in the cloud and they're going to want to do analytics on it and they're going to want to do AI on it. And just the combination of Leo with the leading cloud in the world in AWS is very compelling to enterprises and to government. So, you know, I think the, um, are only, you know, today, if you ask what stops us from growing the business, we have to get the constellation into space. We have over 20 launches planned this year. We have over 30 launches planned in 2027. But I think the business has a chance to be a very large, you know, many billion dollar revenue business.
And I think it has some characteristics that are reminiscent of AWS in that it's capital intensive up front where you're committing a lot of capital and cash in the early years for assets that you get to leverage over a long period of time. And so I like the free cash flow and return on invested capital characteristics of that business in the medium to long term. And the last thing I'll say about it is your question about Global Star. Increasingly, what we're finding with consumers and enterprise and governments is that they don't like to have any periods where they don't have connectivity. It just upsets whatever customer experience they're going through. Even in metropolitan areas, we all hit certain parts of the highway or certain roads where you can't get connectivity or you're hiking, you're skiing. And so increasingly, we see very large demand for consumers to have direct-to-device. And that was really the impetus for our acquisition of GlobalStar. They have unusual and scarce global spectrum that's required to provide direct-to-device. We also really like the satellite know-how that we'll get as part of that merger with Global Star.
And then it also afforded us the opportunity to build a deep relationship with Apple, who's going to use our direct device for their iPhones and for their watches. So very optimistic about the business. And
the next question comes from the line of Shweta Kajuria with Wolf Research. Please proceed with your question. Okay, thanks a lot for taking my questions. I wonder, Andy, if you could please talk about, you know, how you're thinking about the increase in price for memory and storage and just the supply chain inflation we're seeing and the impact it could have in capex this year and potentially next year as well. And then on agentic commerce, if you could talk about how you view the opportunity with advertising. I have no doubt that Rufus could be the best shopping assistant available over time. But for advertising opportunity, how do you view that if agents would be the ones taking action to shop? Thanks a lot. So on memory and storage and the supply chain, I think everybody knows that the cost of these components, particularly memory, has skyrocketed. And we're just in a stage where there's just not enough capacity for the amount of demand. We have worked very closely with our strategic partners. We saw this trend happening early, you know, in the kind of the middle of the latter part of last year.
And we've worked with our strategic suppliers here to get, you know, a significant amount of supply. And so we're working very closely with them. I think the team's been very scrappy. I think we've done a good job in making sure that we're not capacity constrained there. But we watch that very closely. You know, one of the interesting things that we see right now with the change in price and in supply on things like memory is that it is a further impetus pushing companies who have on-premises infrastructure into the cloud. And it's because, in meaningful part, these suppliers are prioritizing their very largest customers, which cloud providers are. And so we have seen a number of conversations we've been having with enterprises for many months where it's just been slower in getting the transformation plan to move to the cloud accelerate rapidly just because we have a lot more supply than what others have. So it'll be interesting to see how that evolves over time. We're doing our best to have the supply we need and keep the cost in the right spot, but we'll see how that continues to evolve.
I think on the agentic commerce and how that impacts advertising, I actually believe that we're going to like this for advertising. I think it's going to be good for customers and it's going to be good for our business. I think, first of all, the first thing to remember is the way that our ads team has built tools and agents themselves is making it so much easier to to do advertising. You know, if you look at small, medium-sized businesses that had to take, you know, weeks and months to do creative and to pick the right audience, all of that is just, it's so much faster and so much easier because of our advertising agentic tools. And you no longer have to take as much time or spend as much money building the creative. So I think there are going to be a lot more advertisers with the rise of what's happening in AI. And then if you look at the agentic commerce experiences, if you look at any of these agentic experiences, they tend to be multi-turn conversations where you're not interacting with one search and getting an answer. You tend to find that you're asking questions, you're narrowing questions, it's asking you questions on what you want.
And in that process of having multi-turns, there are multiple opportunities to surface relevant products to customers, many of which will be organic and some of which will be sponsored. And it also gives rise to opportunities like sponsored prompts. And so one of the interesting things that has been very successful for customers in our store has been when they ask certain questions, we give them a number of suggestions that are all created through AI. And we've gotten pretty good at also having sponsored prompts and that mix of questions and prompts that make it easy for people to keep digging deeper into what they're interested in. So I actually believe that advertising will do well in a world of agentic commerce. Thank you. And
our final question comes from the line of Colin Sebastian with Baird. Please proceed with your question. Thanks very much. Good afternoon. Maybe a two-parter, if I could. Andy, first off, just wondering what you're seeing in terms of the trend between incremental AI demand from earlier adopters and larger AWS customers versus maybe how the demand curve is shaping up across the broader enterprise base. And then at a high level, if you think about the use of AI internally across Amazon's businesses, presumably the business overall looks very different in three or four years Maybe, Andy, if you could contextualize where you see the most opportunity for the technology internally, both in terms of product, as well as maybe driving more operating efficiency, I think that would be helpful. Thank you. Yeah. So on what we see in the incremental AI demand from early adopters versus broader enterprise base, I think it's no secret that you've got the AI labs are spending an incredible amount of money on compute at this point, and compute both on the AI side as well as on the core side.
And the models that they're building and the companies that have successful generative AI applications are certainly spending a lot. And there's several of those labs, but We also see quite a bit of enterprise adoption and usage of AI. As I've said before, the largest absolute place that we see enterprises having success is in projects that are around cost avoidance and productivities. These are things like automating customer service or business process automation, fraud, or things of that sort. But the number of projects that we're working with across enterprises and that we're now starting to see come to production around brand new experiences, trying to figure out how to reinvent their current experiences, but using inference and AI to be smarter, also very significant. So we're seeing the adoption of both of those segments. On the use of AI internally and for our current businesses, I think that the shortest First summary I could give you, Colin, is that I do not see a place in any of our businesses or any of the ways that we do work where we're not going to have giant impact on what we do.
I've long had this belief that while you can add incrementally to a lot of your existing customer experiences, different agentic and AI experiences, I really believe that in the fullness of time, and I don't know if that's three years from now or five years from now, or it could be sooner too, that all of these customer experiences we know are going to be completely reinvented. And they're going to have different interfaces. They're going to have different ways that people interact with them. People are going to want to have dialogue with them. And so I think it means that you have to look. It's tricky if you have an existing business that's doing well. but you have to look at every single one of your customer experiences and you have to be able to carve off resource for that team to think anew about what would the future customer experience look like if you started from scratch today and if you had all the technologies like AI available to you when you started. And that is what we're doing in every single one of our experiences. And if I, you know, I have a chance to be involved in some of those and, It's really exciting.
And there are experiences that may take a while for customers to get used to and to use over time. You might find different segments like those AI forward experiences more than others early on. But if you're not actually working on inventing those right now, I think it's going to be very hard to have the business and the experience leadership that we want over a long period of time. So every single one of our consumer businesses, every single one of our businesses in general is working on that. And then I would say internally, I also think that it's going to radically change how we work. It already is. I mean, just look at how coding, agentic coding is changing how we're all building products. I think it's going to have a comparable impact on how we do DevOps and how we do customer service, how we do research, how we do analytics, how sales is conducted. I think every single one of these functions that we all do at work are going to very significantly change. And that's another area of real focus for us. And, you know, we have this experience I mentioned in my letter.
But, you know, if you look at one of our services, we swapped out the engine of the service while we were, you know, also running the service full tilt. And normally that would have taken 40 or 50 people about a year to do. And we took five really smart people, AI forward thinking people building on agentic coding tools. And those five people rebuilt it in 65 days. Like that is a very different world of operating. And that's the world I think we're heading to over the next few years. Thanks for joining us on the call today. And for your questions, a replay will be available on our investor relations website for at least three months. We appreciate your interest in Amazon and look forward to talking with you again next quarter.
Quarter 2
Q4 2025 Earnings Call — February 5, 2026
Mark Mahaney (Evercore ISI): On the strong long-term return on invested capital, I think that's the debate in the market today. So could you give us a little bit more insight into that? How do you think investors will be able to see that? Either talk about the duration of the CapEx cycle that you're going through now or what we should see in terms of profitability levels, and maybe also talk about other de minimis or minimum free cash flow generation levels that you don't want to go below as you go through this CapEx cycle. Just help us get to your level of confidence in having a strong long-term return on that invested capital. Thank you.
Executive (Title): Yeah, sure, Mark. Thank you. I'll start from a financial side. So on the investments we're making, as Andy said earlier, you know, we are putting into service with customers all capacity that we're getting, and it's immediately useful. And we're also seeing a long arc of additional revenue that we see from other customers and backlog and commitments of people who are anxious to make with us, especially for AI services. So you can see that's working its way into our P&L, both through CapEx and also through our operating margin in AWS. AWS is 35% operating margin through Q4, up 40 basis points year over year. As we talked about before, that is going to fluctuate over time. It certainly has a headwind from the investments in AI and the depreciation on that CapEx, but we also work very hard to offset that with efficiencies and cost reductions. So we'll see how that develops over time. So, but yeah, we see long, strong return on invested capital, see strong demand for these services, and we continue to like the investments in this area.
I would add to that, you know, if you look at the capital we're spending and intend to spend this year, it's predominantly in AWS and some of it is for our core workloads, which are non-AI workloads, because they're growing at a faster rate than we anticipated. But most of it is in AI. And we just have a lot of growth and a lot of demand. When you're growing 24% year over year with an annualized revenue run rate of $142 billion, you're growing a lot. And what we're continuing to see is as fast as we install this capacity, this AI capacity, we are monetizing it. It's just a very unusual opportunity. As I've shared a lot of times, I passionately believe that every customer experience that we know of today is going to be reinvented. With AI, there are going to be a whole bunch of customer experiences that none of us ever imagined that are going to become the norms of how we all operate every day and what we use. I think the other thing is that if you really want to use AI in an expansive way, you need your data in the cloud and you need your applications in the cloud. Those are all big tailwinds pushing people towards the cloud.
So we're going to invest aggressively here and we're going to invest to be the leader in this space as we have been for the last number of years. We have, I think, a fair bit of experience over the years in AWS of forecasting demand signals and doing it in such a way that we don't have a lot of wasted capacity and that we also have enough capacity to serve the demand that's there. And I think we've also proven with AWS over the years in how we build data centers and how we run them and how we invent in there. If you think about our chips and our hardware, our networking gear, and how we've invented Empower, that this isn't some sort of quixotic top line grab. We have confidence that these investments will yield strong returns and invested capital. We've done that with our core AWS business, and I think that will very much be true here as well. And I think some of the things that you will see over time in the AI space is you're going to keep seeing all the inference services, which is going to be the majority of the long-term AI workloads is going to be inference. You're going to see the inference keep getting optimized. You're going to see higher utilization on those services.
You'll see prices normalize over a period of time. And then I think the companies that have not just the excellence in infrastructure, but also the components that give customers better price performance and give those companies themselves better economics are going to have advantaged financials. And I think if you look, we're already off to a really good start having Tranium underneath the majority of our Bedrock service. And that's not just giving customers better prices, but it also gives us better economics. And so we see that following the same sorts of patterns we saw in the early days of our core AWS investment. I'm very confident we're going to have strong return on invested capital here.
Doug Anmuth (JPMorgan): Can you just talk about how Project Rainier is running with Anthropic after its first full quarter? And I think in the release it talks about 500,000 chips, but a few months ago you talked about getting to a million as well. So if you could clarify that. And then maybe just to follow up on Mark's question, are there any financial guardrails or governors in place that we should think about around the spend just in terms of operating income growth or positive free cash flow? Thanks.
Executive (Title): Yeah, I'll start with the Tranium piece. We are very excited about the growth that we see in Tranium and the future that we have there. You know, I think if you look at what's happened in the early innings of AI over the first few years, you see a lot of usage. But customers are really thirsty for better price performance. Tranium has 30% to 40% better price performance than comparable GPUs. So it's very compelling to customers. You mentioned Project Rainier. Anthropic is building their next, they're training the next cloud model on top of Tranium 2.0. And that's what Project Rainier is. We talked about 500,000 chips there. You will see that continuing to increase. They're also using a fair bit of Tranium 2 for other workloads and their own APIs beyond just Project Rainier. But Tranium is a multi-billion dollar annualized run rate business at this point. And it's fully subscribed. And what you're also seeing is Tranium 3, which is the next version of training which we just started shipping that's 40% more price performance than training 2.
And we have a very substantial amount of interest there, we expect that nearly all that supply will be committed by somewhere around the middle of this year. And we're just in the process of building training for, there's very substantial interest in training for which is coming in 2027 and we're already having conversations about training five. So there is a lot of interest in Tranium at this point. I think people know about our chips capability, our chips business, but I'm not sure folks realize how strong a chips company we've become over the last 10 years. If you look at what we've done with Tranium, if you look at what we've done with Graviton, which is our CPU chip, which is about 40% better price performance than comparable x86 processors, 90% of the top 1,000 AWS customers are using Graviton very expansively. If you combine training and Graviton, it's well over a $10 billion annualized run rate business, and it's still very early there. So I'm very optimistic about what we're seeing. The Project Rainier has gone very well. I think Anthropic is quite pleased with it. We've learned a lot in the process as well, but it's early days with what's possible here.
This is a big business that's getting bigger and has a lot of potential. And I just, you know, I'd briefly comment on your second question that, you know, we are, as I mentioned, this is what, you know, I think this is an extraordinarily unusual opportunity to forever change the size of AWS and Amazon as a whole. I think it also is an extraordinary opportunity for companies to change all their customer experiences and for startups to be able to build brand new experiences and businesses that would have taken much longer to try to accomplish before that they can do right now. And so we see this as an unusual opportunity and we are going to invest aggressively here to be the leaders. Cause I, you know, like we've been the last number of years and like, I think we will be moving forward. Thank you.
Ross Sandler (Barclays): Andy, you mentioned a few calls back how the AI market was currently a bit top heavy with a lot of the spend kind of clustering around a few of the AI native labs. So how is that changing as you look out into 26? And specifically, how do you think you might extend your relationship with a company like OpenAI to maybe help Amazon's AI efforts both on the retail side and the AWS side? Thanks a lot.
Executive (Title): Yeah. The way I would describe what we see right now in the AI space is it's really kind of a barbelled market demand where on one end you have the AI labs who are spending gobs and gobs of compute right now along with what I would consider a couple runaway applications. And then at the other side of the barbell, you've got a lot of enterprises who are getting value out of AI in doing productivity and cost avoidance types of workloads. These are things like customer service or business process automation or some of the fraud pieces. And then in that middle of the barbell are all the enterprise production workloads. And I would say that the enterprises are in various stages at this point of evaluating how to move those, working on moving those, and then putting them into production. But I think that middle part of the barbell very well may end up being the largest and the most durable. And I would put in the middle of that barbell too, by the way, I would put just the altogether brand new businesses and applications that companies build that right from the get-go run in production on top of AI.
And so I think that, you know, to me, when I look at this, what's happening, it's kind of unbelievable if you look at the demand of what you're seeing already with AI, but the lion's share of that demand is still yet to come in the middle of that barbell. And that will come over time. It will come as you have more and more companies with AI talent, as more and more people get educated with that AI background, as inference continues to get less expensive. And that's a big piece of what we're trying to do with training them in our hardware strategy. And, you know, and as companies start to have success in moving those workloads to, you know, further and further success and moving those workloads to run on top of AI. So I think there's, it's just a huge opportunity. It's still in the relative early stages, even though it's growing at a very unprecedented clip as we've talked about. And then I think, how do we see our relationships extending with other companies like OpenAI? I would tell you that this movement and what's happening in AI, it's very broad. It's going to be a lot of companies. It is a lot of companies already.
There's a number of AI labs, but almost every company you talk to, almost every conversation we have on the AWS side starts with AI. We have very significant relationships with a lot of different companies. I think we announced an agreement with OpenAI in November. We're excited about that agreement. It's a big one. We have a lot of respect for the company, and we hope to continue to extend our partnership over time. But this AI movement is not going to be a couple companies. It's going to be thousands of companies over time. Thank you.
Michael Morton (Moffitt Nathanson): This one's on the retail business. Andy, you've talked about how you're passionate. This is going to change experiences across the board. And you've shared some encouraging data points on Rufus. And we're seeing all the other internet platforms roll out agentic protocols. I would love to see how you think this plays out for the retail business and the onsite ads portion of the retail business is what seems like it could be a compression in the funnel as consumers get better answers over time. Anything there would be great. Thank you.
Executive (Title): I'm very optimistic about the customer experience that will ultimately be what customers use for agentic shopping. And I think it's good for customers. I think it's going to make it easier for them. It's a big piece of why we've invested as significantly as we have in our own shopping assistant in Rufus. And if you haven't checked out Rufus recently, I really encourage you to do so. It's gotten much, much better and keeps getting better every month. We have about 300 million customers who use Rufus in 2025. Customers who use Rufus are about 60% more likely to complete a purchase. And so you're seeing a lot of usage of it and a lot of growth, and I think it's very useful. And I think at the same time, we will have relationships with third-party horizontal agents that can enable shopping as well. We have to collectively figure out a better customer experience. It's still... these horizontal agents don't have any of your shopping history. They get a lot of the product details wrong. They get a lot of the pricing wrong. And so we have to try to find a customer experience together that's better and a value exchange to make sense for both parties.
But I'm very hopeful that we'll get there over time. We continue to have a number of conversations. And then I think you're going to have to look at, as time goes on, which types of which shopping agents are consumers going to use. And it kind of reminds me in some ways of the early days of kind of all the search engines that were referring traffic to retailers. And it's still a relatively small portion of the overall traffic and sales. But of that fraction, you have to ask how many consumers are going to prefer using a horizontal agent where it's kind of a middle person between the retailer and the consumer versus wanting to use a great agent from that retailer that has all its shopping history and that has all the data right there and makes it easy if you're just spearfishing for something to shop for it right there. Or if you want to do discovery, you can do it there and it's got the best data on shopping. I think a lot of customers are ultimately going to choose to use a great shopping agent from that retailer. Because if you think about what consumers really want in retail and a retailer, they want really broad selection. They want low prices. They want really fast delivery.
And then they want a retailer that they can trust and that takes care of them. And I think horizontal agents are pretty good at aggregating selection, but retailers are much better at doing all four of those items. And so I'm very optimistic that people will use our shopping agent. It's off to a great start. I also expect that we'll work with other third-party agents over time as we work on the issues I mentioned earlier. Thank you.
Brian Nowak (Morgan Stanley): I want to ask you one about the global retail business this year. I know there's a lot of areas of investment in it that you're talking about to sort of make, improve the service, make it more durable over the long term, et cetera. But I'm assuming there are also sources of efficiency you expect to see this year. Can you sort of help us understand both sides of the ledger on retail this year? Where are some of the areas where you see the potential for sources of efficiency and cost to serve savings? And then where should we be thinking about the areas of investment to sort of drive more durable growth, you know, robotics, et cetera, how does that sort of break down?
Executive (Title): Yeah. So I would say, um, on the side of continuing to invest, to keep growing the retail business, the kind of core drivers of demand continue to be the same. We're going to work really hard to expand selection. And you've seen what we've done over the last several years. The expansion of selection has been broad. And you'll see it on both ends of the spectrum. We have a lot more of those luxury brands that have built presences in Amazon had success and found that we could manage their brand presentation the right way. And they've been very happy. I mean, you only have to look at L'Oreal as an example too, just how fast that business is growing and how happy our partners have been. And at the same time, we are working really hard to continue to expand the amount of everyday essentials that we offer our customers. ==The growth in everyday essentials in our business is really remarkable, as I mentioned in my opening comments.
One out of three units now that we move are everyday essentials.== What we find there is that the more the customers can rely on us for everyday essentials and the lower ASP items, they choose to do more of their downstream shopping with us in every way. We're just more front of mind. Yeah, I think a big piece of why we have captured more and more of those everyday essentials, and you see it also in our grocery business with perishables too, is just our speed of delivery improvements over the last three years has been really market. I mean, it's customers, it's the one thing I get stopped on the street most often about, which is I just can't believe how quickly from when I order something, I get it to my door and how reliable you are. I think, you know, along that story, speed of delivery piece, it's also quite interesting what's happening with quick commerce. And we have this offering called Amazon Now that we've largely started outside the U.S. and India and the UAE and Mexico that gets thousands of items to customers within 30 minutes. And it really is, it's quite interesting how quickly that is growing.
And I think that it's just another one of those things like everyday essentials that when you're able to order more and more from Amazon, you just think of Amazon first if it's a great experience that we're offering for whatever you're looking for. But if you look in India, which is the place we've rolled out QuickCommerce the fastest, customers who try QuickCommerce are shopping with triple the frequency than they did before they tried us at QuickCommerce. So those are all areas I think are pretty excited that we're expanding. You'll see us continue to expand what we're doing on the perishable side too, which we're quite excited about. And, you know, we are able to deliver perishables same day in thousands of cities around the world now. And the cities in which we have those perishables available, nine of the 10 top items that are ordered in that geography are perishables. So we're just having a lot of success with that too. And people buy perishables from us. After they buy perishables, they're shopping with us twice as frequently. So a lot of good things to like there.
And then, you know, on the efficiencies, we are, I mean, we always have a very long list of these that we're working on, Brian. And, you know, it's true today as well. Like if you look even, you know, I mentioned, I talked a lot about regionalization earlier in our fulfillment network and particularly in the U.S. you know, over the last couple of years. And I said, we weren't done honing that. And that's true. It's just, we, you know, we don't talk about it every time, but if you look at what we've done there, we've extended the number of regions, you know, it was eight, it's now 10. We've extended regionalization to what we do with our inbound delivery to be much more efficient, being able to get more items closer to customers more quickly. You know, we have made a lot of, we're doing a lot of work and we've made a huge amount of progress in being able to get more units into each box. And as we're able to get more units into each box, it obviously saves shipments and we drive better operating income when we do that. And we've made very significant progress there, but have a lot more planned.
It's part of, by the way, that improvement is part of what helps us do things like I was talking about earlier in adding to a delivery in near real time. And then, you know, robotics, as you mentioned, is another big one for us. You know, we have over a million robots today in our fulfillment network. They take care of all sorts of functions, but still a fraction of what I think we're going to be able to enable over time, which will allow our, you know, we'll always have a lot of people that we employ in our fulfillment network, but they'll leave to the robotics things that you know that are more repetitive so it's better productivity for the business more safe for teammates and there's real cost efficiencies in that as well, so a lot on both sides of the ledger as always. Thank you.
Eric Sheridan (Goldman Sachs): Maybe a few parts just on AWS. Can you speak to the current state of your revenue backlog as of Q4 and also discuss a little bit about what you see both for internal use cases and external client needs with respect to any imbalance between supply and demand around AI efforts and how you think about closing the gap on those as more capacity comes online through 2026? Thank you.
Executive (Title): Yeah, that's a lot of parts. I'll start with the first one, which is on backlog. Our backlog is $244 billion. That's up 40% year over year. I think it's up 22% quarter over quarter. We have a lot of deals that are in the pipeline. As I mentioned earlier, there is a lot of demand for AWS right now in the AI space and also in the core AWS space. Your second question was internal and external use cases. And then the impact around supply and demand. You know, the vast majority of our customers, the capital that we spend and the capacity that we have is consumed by external customers. Amazon has always been a very large AWS customer, a very helpful AWS customer because they're very demanding and they use the services very expansively and stretch the limits as we launch things. They've always been a very important big customer, but always a very small fraction of the total. And that's true today in AI as well as the overall AWS business. Internally, we have all sorts of ways that we are using AI. We have over a thousand AI applications that we've either deployed or in the process of building.
And they range from our shopping assistant in Rufus that we were just talking about, to Alexa Plus, which is a really large-scale generative AI application, to applications in our fulfillment network that allow us to have more accurate forecasting predictions, to how we do customer service in our customer service chatbot, to how we are making it much easier for brands to create advertisements and to optimize all their campaigns across the full funnel of advertising options we have. In live sports, if you watch Thursday Night Football, you can see defensive alerts which predict which player is going to blitz or pocket health. In every one of our businesses, you see a very broad use of AI to improve the customer experience and in many cases just to completely reinvent what was possible before. I mean, it's pretty neat to use something like lens where you know you may see something you want to buy you can just take a picture of it in the app and it finds the item on the detail page you buy it one click it's kind of magic.
You know externally, I would say, you know, it's kind of what I said earlier, you have AI labs consuming lots and lots of capacity, both for training as well as for the inference and the research across what they're doing with their different applications and models. We see enterprises, all sorts of workloads, customer service automation, business process automation, fraud, completely reinventing their applications, agentic coding applications, legal applications. Suno is a really cool example of an AWS customer that's kind of reinvented how you can write music and build music. So really across the board. And I just think on the supply and demand, what I would tell you is we're growing 24% year over year on $142 billion annualized run rate business. So we're growing at really an unprecedented rate. I think every provider would tell you, including us, that we could actually grow faster if we had all the supply that we could take. And so we are being incredibly scrappy around that. If you look in the last 12 months, we added 3.9 gigawatts of power.
Just for perspective, that's twice what we had in 2022 when we were an $80 billion annual run rate business. We expect to double it again by the end of 27. We added 1.2 gigawatts of power in Q4, just quarter of a quarter. So it's, so we, you know, we are, our team is being aggressive and scrappy and inventive and adding capacity as fast as we can. I, you know, we'll add a lot more in 26 and 27 and 28 for that matter. And, um, and we're very optimistic we can continue to grow in the ballpark of what we have. Thanks for joining us on the call today and for your questions. A replay will be available on our investor relations website for at least three months. We appreciate your interest in Amazon and we look forward to talking with you again next quarter.