Davos 2026: Amazon CEO Andy Jassy 1/21/26

0:03We did a lot of pre-buying in the early part of 2025 to enable us to try and keep prices as low as possible for customers. And a lot of our third-party sellers did a lot of forward staging in our fulfillment network for the same reasons. And that supply has run out in the fall. And so you start to see some of the tariffs creep into some of the prices, some of the items. Amazon CEO Andy Jassy, an extended interview on tariffs and consumers at the World Economic Forum in Davos, Switzerland. Consumers have been pretty resilient. They continue to spend. They continue to shop. I think that wherever they can, they are trying to trade down in price.

0:49The power and the infrastructure demands of AI. Power has been short. In the U.S., around the world, there is a power shortage. I think that it is better than it was 18 months ago and still not as plentiful as we all need. Plus, how Amazon fits into the entire AI ecosystem with NVIDIA semiconductor chips and with chips of its own. If you're building a big inference business like we are and you want to have reasonable margins, if you're not pursuing your own custom AI silicon, you're going to be structurally disadvantaged. I'm CNBC producer Cameron Costa. Squawk Pod reports from Davos. Amazon CEO Andy Jassy begins right now.

1:40It is Davos week. So many of the world's CEOs, politicians, and journalists are in a small town in the Swiss Alps crunching through snow for panels, speeches, interviews, and yes, a few parties. Most of CNBC's Davos coverage comes in the form of our interviews on TV. On Squawk Box, we bring you conversations with Anthropic CEO Dario Amodi, for example, or the heads of banks like Bank of America's Brian Moynihan, Morgan Stanley's Ted Pick, even with heads of state like President Donald Trump. But Joe Kernan, Becky Quick and Andrew Ross Sorkin are busy the rest of the day in Switzerland, sometimes moderating panels and interviews at CNBC's home base in Davos.

2:29Welcome to CNBC House. Please take your seats. Hello, everybody. Welcome to CNBC at Davos. It's so great to see all of you here. That's where this next conversation took place. A longer format morning interview with Becky Quick and Amazon CEO Andy Jassy. Thank you to Andy Jassy for joining us this morning. And thank you to all of you for being here, too. This is new for me, first time I'm doing one of these interviews like this, and I'm really excited to do it with Andy. He covers so much ground, and I know everybody here knows Amazon, and everybody here knows Andy Jassy, but I think it's really hard to understand the scope of the company, what it is and what it does, without knowing Amazon by the numbers.

3:17So let's walk through that just a little bit. Amazon, first of all, has a market cap of more than$2.5 trillion. dollars. If you take a look at their employees, it's one and a half million employees. They are the second largest private employer on the planet. If you're looking at revenue for the company, for the most recent year that was reported, 2024, it was$638 billion. And I think if you want to break down just the rate of growth at some of their units that have been pretty spectacular, AWS, the cloud services unit of the company, this year I think is on an annualized run rate to have revenue of$132 billion.

3:54That's up from$108 billion last year. And if you roll back 11 years, it was only$4.8 billion. That just tells you about what Andy has done just in terms of the unit that he used to run, where things are going, and how much growth there is. They run everything from projects like Vulcan, which looks at robotics. They've got AI projects like SageWorks and Bedrock. They have things like Amazon Pharmacy. They have Amazon Prime Video. So it's hard to really understand the scope until you start looking through some of those things. Andy, I thought we could start today by talking a little bit about how you spend your time.

4:30Not because I want to know everything you do in your day, but because I think it would show a little bit about what your priorities are for the company. How would you break down a typical day or week? Well, first of all, thanks for having me. I appreciate it. It's great to be here with all you. You know, I would say that it obviously varies day to day and week to week with what's going on. You know, when I started doing my current job in 2021, if you'd asked me whether I would spend a lot of time in the retail business, I would have guessed not that much. And then all of a sudden we had an issue with cost to serve in our fulfillment network in 2022, and I spent a lot of time in 2022 and 2023 on our retail business.

5:07But, you know, so it varies depending on what's going on, but I would say roughly there are three big buckets. One is our existing really big business areas like retail and AWS and our ads area. And then I think the second bucket, which is probably the place I spend the most amount of my time, is on new businesses, either businesses that are relatively new or that haven't launched yet. So these are areas like Prime Video or healthcare business or our low-Earth orbit satellite that we call Amazon Leo. or Zoox, or, you know, and I would say AI more generally, you know, is just, it's AI, we have a big piece of AI in every single one of our businesses, and we're building models, so that's, you know, that would be the second bug, kind of new, big new initiatives, and the third would be really around just the company, and particularly the culture, you know, and that's another one I didn't really think I would, you know, when I was thinking about coming into this job, I didn't I spent a lot of time wondering would I spend time on the culture.

6:10But, you know, for most companies who've had success of any size, especially as you get larger, the culture has historically been one of your secret sauces in your being successful. And that's true for Amazon, too. But just as you get bigger, there's a lot of ways the culture gets stretched. And it takes work to kind of make sure that you operate the way you want to. We want to operate like the world's largest startup. And, you know, it takes work and it takes energy, and the leadership team and I spend time on that too. What does that look like in an example of something? To say you spend time on culture, what do you do differently?

6:45Well, you know, one of the things that I have a group of people that I spend time with on a regular basis just on the culture. We actually call it Culture Club when we get together, a nod to the old band. And we talk about the things that we think are going well in the culture and the things that we think are getting stretched in some way. And one of the things we realized over the last couple of years, as we had grown so quickly and added so many people as we were growing so fast in retail and AWS and ads and a bunch of these new businesses, was that when you add people, you add layers. And when you add layers, it means that historically, the group of people that we had always hired, really smart, ambitious, customer-focused owners who did the work, who own their destiny on the two-way door decisions, which is the majority decisions that our folks make, that when you add layers, you end up with pre-meetings for the pre-meetings for the meeting.

7:44And people show up at meetings and they don't make recommendations anymore because they know it's going to be two meetings later before you actually make a decision. And we didn't like that. And we weren't moving as fast as we thought we could move. And we want owners to really feel like they own their own destiny. And so we spent a lot of time talking about that as a group and deciding that really one of the big issues that we had to address was we needed to flatten some of the layers. And so if you want to move like the world's largest startup, you need to be as lean as you can be in pursuing the surface area that you mentioned earlier that we're pursuing.

8:19You need to have as few layers as you can possibly have, and you need the people doing the work to be able to make those decisions quickly and learn from them if they don't work out right, and advance them when they do. And so that's an example of something we just decided we were going to flatten the layers, and we were going to increase the ratio of individual contributors to managers by at least 15 % across the entire company. And to take an initiative like that across our service area, you know, it takes effort. It takes a team being on the same page, and then you got to go make it happen.

8:48Can you talk a little bit about Rohit Prasad leaving AI and the incoming DeSantis, who's kind of got a larger portfolio that's going over that? What was the meaning behind that move? What's it going to mean? I like you calling him DeSantis, too, by the way. We're all going to use that a lot. But, you know, I have a lot of respect for Rohit. He was at the company, you know, over a dozen years. He was an instrumental part of building Alexa and all the natural language understanding and the automatic speech recognition. And I think that he did a lot in helping us not just move quickly to pursuing our own models, our own frontier models, but what he built in the first couple of versions of Nova.

9:35I think that we have conviction that over time, the very best frontier models are going to have to work very closely with the chip in which they operate on. I think that the best models are going to be really optimized on chips. They're going to run really quickly. They're going to have a little latency. They're going to be very cost effective. And we wanted to bring together the teams that build our own custom silicon, Tranium, which is our own custom AI silicon, and the team building our largest frontier models, which is Nova. And Peter DeSantis has been at Amazon for, I think he's been there about 27 years.

10:13He has done a lot of things, but I've worked with Peter since really the start of AWS. Peter had just become a director of the company when we asked him to go run EC2, which is our compute service, but he started working on that about six months before we went to launch. Built that, ran all our compute pieces. He ran all our infrastructure, which for us are our data centers, our network, and our hardware. Then he ran all the different AWS services for a while. But one of those was he ran all of our chips. So we felt it was important to bring those together. Peter is incredibly strong technically and has been involved in our model building as well as our chips.

10:53And I'm very optimistic about bringing those together. I think Peter's going to be a great leader for it. Let's talk a little bit more about chips because that's a huge initiative for you. Multi-billion dollar business already. and you wrote last summer that, I think it was in your April letter to shareholders, that chip prices can and will come down. Do you think that NVIDIA is charging too much for its chips right now? Well, you know, we learned this lesson before AI in the CPU business where we had this very deep partnership with Intel, which we still do, but customers always want better price performance.

11:30And I would say that a lot of times when you have a significant leader, they have a lot of other features and priorities, and that often isn't the priority for them. And so we acquired a team in Israel called Annapurna, which is a very talented chip designing team, and we built our own custom CPU that we call Graviton, which has been very successful for customers and for the business. 90 % of our top 1 ,000 customers use Graviton very expansively. It's 40 % more price-performant than the other leading x86 processors. And we saw this same movie playing out in AI. And about five years ago, we asked that team to build custom AI silicon.

12:08And, you know, we have a deep relationship with NVIDIA. We will for as far as I can foresee. But it is undeniable that customers want better price performance. And if customers are going to be able to roll out AI as expansively as we believe they want to, and they should, the cost of inference has to come down. And so that's why we pursued Tranium. Our Tranium 2 chip is about 40 % more price-performant than the other leading GPUs. It's fully subscribed. It's a multi-billion dollar business, as you talked about. Anthropics building their next version of Claude on top of hundreds of thousands of our Tranium 2 chips.

12:45We just released our third version of Tranium, which is 40 % more price-performant than Tranium 2, which was already more price-performant than other things out there. And I just think that if you want to allow customers to have lower prices for inference, which we do, and if you're building a big inference business like we are and you want to have reasonable margins, if you're not pursuing your own custom AI silicon, you're going to be structurally disadvantaged. When you say price performance, that means how much power you get for the amount you're spending? It's when you look at the performance combined with the price.

13:20You can have a higher price on something, but be way more performance. You always want to look at the combination of what performance you get for the price. Now, the deal that you have with OpenAI, or this has been reported that you were going to take a$10 billion or larger stake with them. They recently signed with you, I think a couple of months ago, to take$38 billion in AWS usage that they're going to be using, too. We've been watching from the outside. There's so many more deals that are happening. Some of these are called circular deals. It doesn't look like that's what you guys are involved in.

13:51But what do you think about the activity that is taking place, the deals that are taking place right now? Is this just a reflection of the demand that's out there? Or do you feel like some of these things are circular? It is so unprecedented how much compute is being consumed right now. You just have to only look at how much power is needed, how many data centers are being built. there is the AI labs are consuming gobs and gobs of compute right now. And so those AI labs believe they have opportunities if they train models very expansively to keep changing the intelligence of these models. So they need a lot of compute, but they need money for the compute.

14:34And so they're trying to find ways to fund that compute. And I'd say a lot of the companies who provide that compute want to serve those customers and then have opportunities to also invest in those companies as those companies are looking to find ways to fund what they're doing. And I think those companies are impressive companies. So I think when you look at a company like Anthropic, a company like OpenAI, I mean, these are unusual companies who have been building amazing models for 10-plus years and are reshaping the way people use applications. And so I just think it's a function of the time where tons of computer being asked for.

15:17They need ways to fund it. Companies have opportunities to invest in companies. Those companies are impressive companies, and you're just seeing some of that. But I don't know if that will continue or not. Do you think it ends well? I think it could end well. I mean, I'm saying anytime you make substantial investments, if you look at the history of M &A and investments, not all of them are successful. and the hit rate is pretty variable. So I think whether the investments end well or not, we'll have to see. But I do think the companies that we're talking about just in the last few minutes are impressive companies.

15:53Open AI, for instance, I think they've signed deals to build out$1.4 trillion in infrastructure just in the last several months. That's pretty ambitious. Do you think it's realistic based on the demand you see? Well, it is ambitious. I agree with you. and I would say that they are ambitious. And I think they're ambitious and they're forward-thinking, and I know that they believe they need quite a bit of compute to train the models the way they believe changes what's possible. And, you know, I don't know the details of all those deals. Sometimes when I get a chance to look at them, I have a harder time making sense of them all, and I just don't know which ones are guaranteed to spend those amounts and which are options to spend those amounts.

16:39But I know that the companies believe they need that much compute. Let's talk about data centers because that's something that you guys are also on the forefront. You just signed a deal with Rio Tento to lock up more of the copper that they're taking out of the ground. It's not just copper. It's electricity. It's all these things that there's a huge rising demand. Do we have the ability to meet that demand? And what else are you doing to kind of make sure you're getting it? Well, we have not had the power has been short. In the U.S., around the world, there is a power shortage. I think that it is better than it was 18 months ago and still not as plentiful as we all need.

17:21I mean, I think everyone would tell you while it's better than 18 months ago, we still could be fulfilling more demand if we had more capacity. And so we have tried every which way we can to work with different communities and different municipalities and different technology providers to enable more power. And we've done unique things on the nuclear side. We've invested in some SMR capabilities. We have been the largest corporate purchaser of renewable energy for the last five years. We have an initiative with water where we give back more water than we take in all the communities in which we operate.

18:01And so we're doing everything we possibly can to help try to enable more power. And we want to do it. We don't expect other people to pay for us. We expect to fund the power that we need. And we create a lot of good jobs in the communities in which we're building a lot of data centers. And we intend to continue to do so. When you say you don't expect other people to pay for it, that's been an issue that President Trump has kind of been talking about writ large. He is kind of pushing back on a lot of companies to make sure that consumers aren't paying more for this. What do you guys do on that level?

18:34Well, we spend so much money on power, Becky. I mean, we're spending a lot of money on infrastructure. We have always paid our own way. We've always expected to pay our own way. We believe very strongly in the communities in which we operate that we want to leave them better off because we're there than before we came. We've both created a lot of jobs, but we're also doing a lot of training of people. We have a number of upskilling programs. We're training hundreds of thousands of people to be electricians, to be data center operators, to work in networking and fiber. And so we're both trying to enable more capacity, but also do so in a way that's good for communities.

19:19Okay. President Trump is here in Davos this week, or is going to be here in Davos. And this may be a Davos like none other, just because of what's happening with tariffs, what's happening with Greenland at this point. Obviously, at Amazon, you deal front and center with tariffs all the time. How has it been since April with the tariffs that come in? Have you managed that? And what do you do when it looks like these tariffs are changing on a fairly regular basis? Well, you know, it's interesting to see what consumer behavior has been like. A year ago, you know, this time, we had no idea what to expect.

19:56You know, there's all this tumult. And, you know, consumers have been pretty resilient. They continue to spend. They continue to shop. I think that wherever they can, they are trying to trade down in price. They are looking for bargains wherever they can find bargains. I see people a little bit more hesitant on the higher price discretionary items. We have improved our speed of delivery so much that we have so many more people buying everyday essentials from us. It's amazing how fast that business is growing for us. You know, I think that we'll have to see what happens on tariffs. You know, we did a lot of pre-buying in the early part of 2025 to enable us to try and keep prices as low as possible for customers.

20:48And a lot of our third-party sellers did a lot of forward staging in our fulfillment network for the same reasons. And that supply has run out, you know, in the fall. And so, you know, you start to see some of the tariffs creep into some of the prices of some of the items. And you see some sellers are deciding that they're passing on those higher costs to consumers in the form of higher prices. Some are deciding that they'll absorb it to drive demand. And some are doing something in between. And so I think you're starting to see more of that impact. And we have so many items. We have hundreds of millions of items.

21:27We have 2 million sellers, many of whom are willing to pursue different strategies in how they price. Amazon's consumers overall, I think, have fared well. But we'll have to see what happens in 2026. What do you do once you run out of those strategies, like you said, like buying ahead, trying to do some of these things? Are there other levers that you can use to keep prices down? Well, as much as we can, we're trying to work with our distribution partners and our selling partners to try to keep prices as low as possible for consumers. That is our focus. I mean, it has always been our focus, but especially in times of more uncertain economies or when there's changes in trade, our priority is try to figure out how to keep prices as low as possible.

22:11At a certain point, because retail is a, as you know, retail is a mid-single-digit operating margin business. if people's costs go up by 10%, there aren't a lot of places to absorb it. And so we're going to do everything we can to work with our selling partners to make prices as low as possible for consumers, but you don't have endless options. Let's talk a little bit about the jobs picture, because you did make some news last summer when you talked about how AI is going to be something that you think will eventually lead to fewer jobs at Amazon. That's a little different than the take we heard from Jamie Dimon at J.P.

22:50Morgan, who said that if J.P. Morgan is successful, he thinks they'll have more employees years from now, but they'll be redeployed in different arenas. Have you thought any more about that? Because when you did scale back with some of the employees, you said it was not because of AI. Yeah, it wasn't. It was really, it was what we were talking about earlier. It was really around culture and being able to move quickly and have ownership. I think what I said was, you know, in the next couple few years, I could see our having fewer people than we had before. Some of that, you know, a lot of that will be just our continuing to allow ourselves to move quickly as it's important culturally and speed-wise.

23:28But I do think that jobs are going to be impacted by what's happening with AI over time. They're not in a significant way yet, but I think you'll see that. If you just think about how AI and agents will enable you to do coding and customer service and research and analytics, even just the idea of doing spreadsheets the way we've done them in the past, I think those will be pretty different. And so I don't think that wipes out all those jobs, but I think we'll still have plenty of people in those roles, and those people will start their jobs, each task they pursue at a higher, more advanced starting point.

24:07All the work that we used to all have to do before we could get to actually the thinking work, a lot of that will be done by AI. So we'll still have people who will be able to invent quicker and more easily. But I do think that you won't need as many people in all those jobs that we've thrown humans at for the last 20 years. That said, I do believe we're going to have a lot. We're hiring a lot of people now in AI and automation and robotics and our low-Earth orbit satellite that we're building in healthcare. So we're going to have a lot of people in other businesses we're pursuing, and there are going to be brand new jobs that we haven't thought of.

24:42I mean, 15 years ago, there weren't jobs like cloud architect. I mean, those didn't exist. And whenever you go through any big technology transformation, you find new jobs. I think the same is going to be true here, medium to long term. And you also said just over the summer that you already had over 1 ,000 AI projects and agents that were out there and that you were adding more every month. So can you give us an overview, an update of where you are right now, six months later, and what that looks like from the customer's perspective? Yeah. So, you know, I'd say we have over 1 ,000 applications, AI applications, we either built or in the process of building.

25:19And on the consumer side, you know, if you know what you want to buy, it's harder to find an easier way to do it, to pop onto Amazon's app or the website and search and buy. But if you don't know what you want, I think that's still one place where the physical dimension has some advantages because you can talk to a salesperson and tell them what you're looking for, and they can ask you questions to refine it, and they can put different options in front of you. And that, you know, I think AI will help quite a bit there. We've built a shopping assistant called Rufus. Rufus has gotten much, much better over the last several months.

25:55It's actually quite good. I've actually noticed. It's helped me quite a bit, actually, in some purchases I've been trying to make. And so I think that is very helpful. I think if you look at Alexa Plus, she's just so much smarter, more capable than her prior version of herself. And that's growing very quickly in our advertising area. Just not only the creative that you can build using AI, but having agents that know everything about your brand, what your presence is like on Amazon. so it suggests ways that you can present yourself, knows information about the brand itself. We have an AI agent that does that, that then creates creative for them.

26:37It's just, you know, if you look at what we do in Prime Video and Thursday Night Football with the features we build, across all of our consumer experiences, we have quite a few applications that are changing the experience. And then, you know, on the AWS side, that business is all about trying to figure out how to enable other companies and developers to build applications themselves. And so they're using AI like we always use any technology, which is to solve problems. And so if you want to build an AI app, you need a good model. So in Bedrock, we have the broadest array of capable models. Increasingly, what I think people are realizing when they build models is they want to be training their models earlier than they've been with their own proprietary data.