저자: LisaSu · 외국인
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AMD CEO Lisa Su는 애널리스트데이에서 AMD 매출 연 35% 성장, AI 데이터센터 매출 연 80% 성장(2027년 수십억 달러 가능)을 제시하고, AI 가속기 시장이 2030년 1조 달러 이상으로 커질 것이라고 주장했다. 고객사들이 생산성 향상을 체감하며 capex를 늘리고 있다고 근거를 댔다. OpenAI의 대규모 적자 질문에는 컴퓨팅 수요가 여전히 공급 부족이라며 투자 확대가 필요하다고 답했다. 엔비디아가 90% 이상 점유율을 가진 시장에서 MI350 시리즈와 파트너십으로 10% 이상 점유를 목표로 한다고 밝혔다. 영상 설명은 AMD 주가가 2억 달러 시총에서 3800억 달러로 성장했다는 점을 강조한다.
다듬은 글
We're turning a $2 billion company into a $380 billion powerhouse. That is Lisa Sue, CEO of AMD, speaking plain truth about the massive transformation she has led. And if that does not get your attention, she goes even further, saying, "We see a trillion dollar AI opportunity by 2030." Today we are breaking down her CNBC interview, showing you exactly what she said and giving you my take on why these numbers and her vision matter for investors, tech, and the future of AI.
I'll play the clip first and then we'll dive deep into what Lisa Sue's words really mean. Hit the like button, share this video, leave your thoughts in the comments, and subscribe so you do not miss the next big financial update. Now, let's hear what Lisa Sue has to say. AMD hosting an analyst day yesterday.
It's the first time in three years. The chipmaker says that revenue growth will expand 35% a year over the next 3 to 5 years and the company's AI data center is expected to grow at 80% a year and potentially hit tens of billions of dollars in sales by 2027. Joining us right now is the AMD CEO, Lisa Sue.
A note on this AMD stock up phenomenally. You can see since she took over 7,589 589%. Um Lisa, I think when you took over this was a $2 billion market cap. I think today it's above $386 billion. Um congratulations counting. Well, it's great to be here with you guys this morning. Thanks for having me.
It's great to see you, too. Last week you had earnings that came out that uh beat all expectations and yet the stock actually declined. I think people were waiting to see what you said at the investor day. They liked what they heard, especially when it came to the revenue, the annualized growth that you're expecting, 35%.
I think most people were looking for closer to 30%. Um, predictions are hard though, especially about the future. And I guess the big question is what makes you so confident? Well, you know, first of all, it was a great day yesterday. It's always nice to sometimes take a step back from just, you know, what's happening on a quarterly basis to really talk about long-term strategy.
And it has been, you know, as you said, it's been three years since we've hosted an analyst day. But what we thought is like there's been so much that's changed in the market just over the last, you know, 12, 18, 24 months that we kind of needed to kind of just take a step back and talk about the company as a whole.
And frankly, I mean, we're in just an amazing cycle um for, you know, technology and spec specifically around AI. So you know back to you know the major points I mean the the market is accelerating at a pace that we you know just did not understand until uh you know over the last few years. Um I think we started a couple of years ago we thought you know the AI accelerator town might be you know $300 billion and that sounded like a really big number.
Um and then each year we took it up and now when we take a step back, you know, we see this massive opportunity. Um you know, really uh over a trillion dollar um you know, overall market as we get through 2030. Um and it's a place where everybody needs technology. You know, think about it as you can think about computing as equating to intelligence.
And if you can get more intelligence, why wouldn't you want more computing? And that's kind of the market that we're in. And so um you know from that standpoint um you know we're really excited about what we have. It's a product portfolio. It's a set of partnerships. Um but it's also a vision for you know where uh computing is going in the future.
What what makes you so sure of that demand? What do you see that makes you think not only that this demand is going to be big but that it's real and that it's not going to disappear? Well, uh, you know, Becky, we spend a lot of time, um, in the ecosystem and, you know, being in this industry for as long as I've been in this industry over 30 years, I think you see a lot of cycles and you see, you know, a lot of technologies take off.
Um, the key is, uh, what people are saying as they're actually utilizing the technology. So, we work with all of the largest hyperscalers in the world, all of the largest enterprises. And if you looked at, you know, sort of the AI trajectory over the last couple of years, I think people started with tremendous excitement.
You know, chat GPT came on board. Everyone was like, "Wow, you know, this is pretty good." Um, and then enterprises started using it. And and frankly, uh, the early enterprise usage was u a little bit slow. I mean, people were kind of just trying to figure out what to do. Uh but if I tell you what we've seen in the last 12 months, uh we've seen uh every one of our largest customers say we can see the inflection point now, Lisa.
Like we can see, you know, demand is accelerating because people are now starting to get real productivity um out of the AI use cases and you know, we have all of the largest hyperscalers in the world saying they're investing more in capex because they can see the uh return on the other side of it. So it it is uh something that we always are looking for the signals in the market but the signals in the market right now say that we're still at the very beginning of the technology but you're starting to see significant productivity improvements.
really think that they can see the returns on the other side or do you think there's a little bit of a big gamble going on? Which is to say that there's a bunch of them will tell you quite openly, look, I'd much prefer to be ahead than behind. Meaning ahead than behind. I'm worried that if I don't invest enough now, I won't have enough capacity later, but I can't necessarily fully math out how it's going to work out on the other end either.
I I I don't think it's a big gamble. I think it's the right gamble. And the way I would say it, Erin, is we can also definitely see uh that more computing and more investments equate to a faster pace of innovation. I think that's definitely there. Um I think you can also see all of the uh all of the the pointers to you know more productivity and more capability.
Now exactly timing of ROI if you're talking about you know is it you know 12 months or 24 months I think that's where it becomes a little fuzzier uh but I would say that look our largest customers are extremely disciplined companies and you know they have the balance sheets to invest and this I'll give you an example the one that everybody talks about is OpenAI.
Yeah. So OpenAI in 2028 is expecting to lose $74 billion by the way they have $13 billion in revenue right now. I believe that's the number. They believe that between somehow between 2028 and 2030 that they will all of a sudden become a profitable business. So they have to make a swing from a $74 billion loss.
Something magical has to happen in the course of 24 months. So the question I would ask you as somebody who by the way has to think of them to some degree as a customer slash creditor of sorts, how you think about that math? [clears throat] Yeah. So, uh again, Erin, I would take a step back and say, uh when you look at the entirety of what, uh the AI, you know, sort of technology, uh companies are you have the largest hyperscalers, you have, you know, I call it the the AI native leaders like OpenAI, Anthropic, others.
And what the underlying foundation is the same. They all need computing. Now, relative to, you know, your your comment about u Open AI, I think Open AI is a phenomenal company. I mean, oh, I do too. I use it every every second. I love I love the business. I love what they're trying to do. I just don't I'm trying to understand the math.
Let's start with the vision and then we'll come to the math. When you look at the math, the the the vision will say you need more computing. That today computing is a limiting factor in how much people can adopt AI. Um and you you can see that in a number of different places and so yes you have to invest ahead of the curve so that you can get the entire user base um on there but if you just take a look at the growth in users and not not just at OpenAI but across the entire AI ecosystem we're seeing that growth and we're seeing that growth because there is true productivity coming at the other end of it and you know from that standpoint you know I think we are all like I said we're disciplined business people but we see a incredible opportunity in front of And absolutely if if one has the capability to uh to address that with you know a fantastic balance sheet you would absolutely do that.
Let's talk about your plans for AI data centers. Um you are scaling pretty rapidly. You see the growth there in terms of revenue being greater than 80% over the next several years and potentially getting to have more than a 10% uh market share in that business over the next few years. um to do that you're going to have to go through Nvidia because there by some estimates they have more than 90% of the market share right now.
What's your plan for doing that? Well, I would say once again this is an amazing market with tremendous growth and whenever you have a market that is let's call it early in the cycle and also on a steep growth curve. It really favors innovation and it favors partnership. Um you know from you know our standpoint technology roadmap we're super excited about the new products that we're bringing out.
We have um you know our MI350 series currently in production. Uh we have a big step up with you know new rack scale architectures uh coming next year. What we also have is um a really strong set of partnerships. You know Aaron mentioned uh OpenAI. We have partnerships with Oracle Meta all of the large hyperscalers.
And the key in this type of market, Becky, is that um everybody wants to have, you know, sort of multiple solutions and and frankly there's no one solution that, you know, fits all. Um you can see with different workloads, you're going to want to have the best technology for each one. And uh we do believe we will have a you know, significant piece of this market.
Um I think between large hyperscalers, enterprises as well as um you know sovereign nation states that are out there building um large data center installations. Um I think you know we are an excellent option and we've we've talked about some of the key partnerships to do that. . So, let's get right into it.
The interview starts with a look at just how far AMD has come under Lisa Sue's leadership when she took over the company. AMD's market cap was around $2 billion. Today, it's sitting above $380 billion, and that's a growth of almost 600%. The host even pointed out that since 2014, when she became CEO, the company's stock performance has been nothing short of phenomenal.
Lisa Sue was on the show to discuss AMD's Analyst Day, the company's first in three years, where they made some ambitious announcements. AMD is projecting 35% annual revenue growth over the next 3 to 5 years and its AI data center business is expected to grow 80% a year potentially reaching tens of billions of dollars in sales by 2027.
That kind of forecast immediately raises questions and the interviewer asked the key one, what makes her so confident? Lisa Sue's answer was straightforward but revealing. She said that the analyst day was a chance for AMD to step back and look at the big picture rather than just quarterly results. It's been 3 years since they held one and in that time the market has transformed especially with the explosion of artificial intelligence.
She explained that the AI revolution has expanded faster than anyone initially predicted. A few years ago, AMD estimated that the AI accelerator market might reach around $300 billion. That was already a huge number. But as adoption has accelerated, that estimate has tripled. Today, AMD sees a total addressable AI market exceeding $1 trillion by 2030.
She compared computing power to intelligence. The more computing capability we have, the more intelligent our systems become. And she posed a powerful rhetorical question. If more intelligence means more capability, why wouldn't everyone want more computing? That's the foundation of her optimism. It's not just about products or partnerships.
It's about the direction of the entire computing industry. When pressed on whether this demand is truly sustainable, Lisa Sue pointed to AMD's experience working closely with the biggest players in the world, companies like Amazon, Microsoft, Meta, and Google. She's been in the semiconductor industry for over 30 years, and she's seen technology cycles come and go.
What gives her confidence this time, she said, is what she's hearing and seeing directly from customers. When chat GPT first launched, there was a wave of excitement, but early enterprise adoption was slow. Businesses were experimenting, trying to figure out how to use AI effectively. But over the past year, something has changed.
Lisa said that all of AMD's largest customers now tell her the same thing. They're seeing real productivity gains from AI, and the demand curve is steepening fast. These companies are investing more in capital expenditures because they now believe the returns on AI are tangible. In her words, "We're still at the beginning of this technology cycle, but it's finally showing measurable improvements in productivity." The interviewer challenged her again, asking if all this investment might just be a massive gamble.
After all, some companies admit that they're spending heavily on AI just to make sure they aren't left behind. Even if they can't fully predict how it will all pay off. Lisa Sue's response was that it's not a reckless gamble, it's the right one. She explained that more computing and more investment naturally lead to faster innovation.
The timing of return on investment might be uncertain whether it's 12 or 24 months, but her point was that AMD's biggest customers are financially disciplined organizations with strong balance sheets. They can afford to make these bets and they're doing it because they see where technology is heading.
Then the interview shifted to one of the most debated topics in AI profitability. The interviewer brought up OpenAI, saying that projections show the company could lose $74 billion in 2028, even though it currently makes around 13 billion in annual revenue. For OpenAI to swing from a $74 billion loss to profitability by 2030, would take something extraordinary.
Lisa Sue's response was calm and measured. She said, "It's important to understand the vision before getting caught up in the math. Whether it's Open AI, Anthropic, or the major hyperscalers, they all depend on computing as the foundation of their business. The real constraint right now isn't lack of demand, it's computing capacity.
There simply isn't enough infrastructure to meet the growing appetite for AI applications. She said investing ahead of the curve is essential. If companies wait until they fully understand how the returns will play out, they'll already be too late. The user growth across the entire AI ecosystem is undeniable, and those users are generating real productivity outcomes.
That's what keeps the cycle moving. Lisa described AMD and its customers as disciplined business people who recognize a once- in a generation opportunity. And if a company has the financial strength to invest in that opportunity, she said it absolutely should. The interview then moved on to AMD's plans to expand its AI data center business.
The company expects to grow revenue in that division by more than 80% annually and capture over 10% of the market within a few years. But that means going head-to-head with Nvidia, which currently dominates the space with over 90% market share. Lisa Sue acknowledged Nvidia's lead, but said that the AI market is still in its early stages and growing rapidly.
In her view, early stage markets reward innovation and partnerships. AMD's strategy, she explained, is built on three main pillars. A strong technology roadmap, deep partnerships, and product diversity. On the technology side, AMD is currently producing its MI 350 series accelerators and preparing to launch new rack scale architectures next year, which she says will be a major step up in performance.
On the partnership side, AMD is working with nearly all major hyperscalers, companies like Oracle, Meta, and others. Lisa emphasized that in a market this large, there's no single one-sizefits-all solution, different workloads require different types of hardware, and AMD's goal is to deliver the best technology for each unique use case.
That's how she believes AMD can carve out a meaningful share of the trillion dollar opportunity ahead. The key takeaway from Lisa Sue's interview is her long-term vision. She doesn't see AI as a temporary boom. She sees it as the next great computing era. This isn't about chasing hype. It's about building the infrastructure that will power the next decade of technological advancement.
Lisa's leadership style reflects patience, discipline, and boldness. She knows that timing the market is impossible, but positioning the company for where the market is headed, that's what matters most. AMD's journey under her leadership is already one of the most remarkable turnarounds in tech history.
And if her projections prove true, the company could play a major role in shaping the future of artificial intelligence and high performance computing. So when you listen to her talk, you can feel that quiet confidence. Lisa Sue isn't just predicting growth, she's building it, and her message is clear.
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