AMD Financial Analyst Day | 🔴 WATCH LIVE | November 11, 2025

Good afternoon everyone. Thank you for joining us. It's a special time for technology and AMD. Our mission is high-performance and AI computing. We've been consistent with our strategy: compute technology leadership, data center as the most strategic market, AI across the portfolio, software investment, and standard plus semi-custom solutions. Progress: data center grew from $2B in 2020 to over $16B this year. EPYC is in 10 of 10 top hyperscalers, over 60% of Fortune 100. Instinct GPUs with MI300, MI325, MI350 ramped faster than any product, used by 7 of top 10 AI companies. We have about 40% revenue share in key data center segments. AI business compressed to annual cadence; MI450 series is a step function. Client and gaming: 28% revenue share, over 50% of desktop CPU channel, AI PC early. Embedded: design wins over $50B at 21% CAGR. Semi-custom: new design wins in aerospace, defense, automotive, data center, communications totaling $45B starting ramp in 2026. Strategic investments: 25,000 engineers, M&A including Xilinx, Pensando, ZT Systems, software acquisitions, venture arm. Revenue now about $34B, significantly improved profitability. Market trends: insatiable AI demand, customers accelerating investment. AI compute equates to intelligence. CPU demand accelerating with AI deployment. Inference growing faster than training. Sovereign AI accelerating TAM growth. TAM greater than $1 trillion by 2030. Our strategic pillars: compute technology leadership, data center leadership with open ecosystem, software (ROCm as premier open-source AI stack), and powering AI everywhere. Partnerships: 6GW deal with OpenAI, Oracle for public MI450 instances in Q3 2026, Helios rack with Meta on open standards, DOE supercomputers. Revenue targets: AI revenue CAGR over 80% to tens of billions in 2027; server CPU share >50%, client >40%, embedded >70%; total company >35% CAGR with data center >60% and core >10%. Now I'll hand over to Mark to discuss technology.

Thank you, Lisa. I've been in the industry four decades and never seen such pace of innovation. AMD has the broadest portfolio of computation for the AI era. Key IPs: Zen CPU, CDNA GPU, RDNA gaming, AI engines, NPUs, Pensando DPUs, Xilinx FPGAs. Common foundation: Infinity Fabric, SoC capability, chiplet and packaging leadership, software (ROCm), security. We made bold bets a decade ago: Zen, 2.5D packaging, Infinity Fabric. We executed: five generations of Zen, chiplet architecture, 2.5D and 3D stacking. CPU roadmap: Zen 5 with native 512-bit AI engine, Zen 6 on TSMC 2nm with performance and efficiency variants. GPU: annual cadence with CDNA4 (MI355), CDNA5 (MI400 series) with HBM4, MI500 in design. Flops doubling every year from 2025. Certis technology: PCIe Gen 5, 112 Gbps, now 224 Gbps for Helios, 448 Gbps in future. Infinity Fabric: fourth gen powers top supercomputers, fifth gen for MI400 with Helios. Chiplet and packaging: 30x increase in silicon capacity from first EPYC to Helios. Helios integrates next-gen CPU, GPU, interconnect, certis, with ZT Systems for rack scale. Software: ROCm battle-tested in HPC and hyperscaler, expanding to enterprise. Gaming GPU: RDNA3 with AI upscaling (FSR4). AI engines: second-gen NPU powers Copilot+ PCs, third-gen in design. Trends: data center explosion, agentic AI driving CPU workloads, edge AI starting. Also robotics and quantum partnerships. Thank you.

We don't see that the data center is dominated by one particular element. Instead, we see GPU racks as absolutely central to the data center, of course, to power the LLMs and power the AI engines at the core of these AI factories, but they're useless without the sea of data that fuels AI, without the storage systems to give them the data to train, to give them the data to infer, to give them the data for agents to actually operate. And then of course those agents, the tools now that LLMs use, all of the databases and other systems of records that need to be accessed for LLMs to actually deliver business value run on general purpose compute racks. And so we see a rich and vibrant data center in order to deliver these AI factories. And so we've built our data center portfolio over the last few years to address these needs. Vamsi and Dan will talk about our GPU and CPU roadmaps in just a moment and the software that makes them sing. And then I'll come back in a few minutes afterwards and unpack our networking strategy and tell you more about how we're putting all of these elements together into compelling system and cluster level solutions. So with that, let me first introduce Dan McNamera, the SVP of our server CPU business. Thank you.

It's this. AMD Embedded has become a high margin growth engine for AMD. We used to be a focused FPGA business. We are now a multi-dimensional powerhouse built upon adaptive compute, embedded, x86, semi-custom silicon, and physical AI. Each a growth engine on its own. Our momentum will make embedded a defining chapter in AMD's success story. Thank you. With that, I want to welcome our CFO, Jean Hu.

Hey, Jean. Thank you, Lisa. It's great to see everyone. Thank you so much for joining us today. You have just heard from Lisa and the team about our strategy, our technology product portfolio, and our focused execution, which is driving tremendous momentum across our entire business. Now it's time to connect the dots to your financial model, and in particular, how all of this positions us to address the very large market opportunity ahead of us and our long-term financial model. Fundamentally, as a management team, we are here to build a compounding business model to drive revenue growth and significant earnings per share expansion to create long-term value. So, when you look at our financial framework for value creation, it has been consistently anchored on three core elements. First is about accelerating top-line revenue, targeting the most attractive market opportunities, driving technology and product leadership. Second is about delivering compelling profitability, expanding margins, and driving operating leverage. And the third, which is most important as all of you know, is about disciplined capital allocation, not only to fund the growth for the future but to maximize returns for our shareholders and owners. So by laser focusing on these top three priorities, this management team has demonstrated a phenomenal track record of execution and value creation. I'll do a quick recap of the last decade of how this team has executed. First on revenue. If you look at 2016, the company's revenue was only $4 billion. We have been able to drive significant revenue expansion to an expected $34 billion, with a CAGR of 26%. On profitability, what our team has done is compound the fast revenue growth pace by expanding gross margin. In 2016, the company's gross margin was barely 31%, and we expanded gross margin to 45% in 2020, and we expect to deliver gross margin of 54% this year. And of course, the gross profit expanded much faster than top-line revenue growth at a 34% CAGR. This team also translated the operating leverage into our overall operating profit increase. If you look at the operating profit in 2016, it was barely $43 million, and this year we're expected to generate over $8 billion in operating profit, which is a 79% CAGR. So it has been tremendous how this team has executed financially. On capital allocation, it's about how we have invested over $100 billion through organic investment and acquisitions, and how those investments have positioned us for acceleration of our technology, product leadership, and also market leadership. This team is very, very focused on return on investment on organic investment. First, we prioritize R&D investment. So if you look at our operating expense and CapEx, the vast majority of investment is on R&D. We have a very rigorous internal resource allocation process each year. We examine the market opportunities, the assumptions we made on different investments. Every project gets examined, and every investment gets examined. The team is not afraid of investing ahead of the curve. You heard from Lisa and Mark how we establish innovation and long-term leadership. But it's also the case that I joined three years ago, and I'm still impressed and amazed at how disciplined the team's plan has been. If the assumptions we made were wrong and if the project would not generate the returns we estimated, they are also not afraid of killing the project and reallocating the resources to the most important projects which generate the highest return. Over time, Mark talked about how we built the foundation for future technology leadership and how we shifted resources to allocate to data center and AI. On the acquisition side, we apply the same discipline. What we have done is not only focus on strategic acquisitions, they have to generate significant returns versus our alternative capital use like organic investment or buyback. That is really important for the team. A very good example is the recent acquisition of ZT Systems. We acquired the ZT design team, and at the same time we separated the ZT manufacturing operation and divested that business. So through both the acquisition and divestiture, not only did we achieve our strategic objective, like Forest said, to accelerate time to market significantly for our MI450 generation product, more importantly, we generated significant cash for our shareholders through the divestiture. So Lisa mentioned that we have built a tremendous execution machine and the playbook on acquisitions and integration, so we can really deliver returns for our owners. When you look at the discipline and capital allocation the team has done, it really drives significant business transformation and acceleration of our financial momentum. Lisa and Forest talked about how we really transformed the business to data center, like $2 billion in 2020. Now it's over $16 billion, almost half our business. You know, for a CFO, what's really most exciting is it has higher gross margin. So structurally, we are focusing on the highest growth opportunity and high growth margin. And then on financial momentum, we have accelerated our financial momentum. If you look at 2025, we expanded revenue growth by 32% based on our estimate for our Q4 guidance. Both client, gaming business, and the data center contribute to this increase in revenue. On gross profit, we expanded gross margin to 54%, and in the second half of this year we are ramping MI350 significantly, but we are able to continue to expand the gross margin. Primarily, it's driven by the newest generation products we're introducing across Ryzen, EPYC, and Instinct families. So it's very exciting how we continue to drive the richer product mix across all our businesses. On operating income, we are leaning in, investing aggressively this year. We continue to deliver over 33% of operating income. So it's a very powerful business model. We are pleased with our financial performance in 2025 and building on this strong financial foundation. I want to talk about the opportunities in the future and our future long-term target model. And of course, it all started with opportunities. I think this team has invested during the last decade to position ourselves to be able to capitalize on the very large opportunities Lisa highlighted. The data center opportunity we expect to go from $200 billion this year to over a trillion dollars in 2030. So within this very large market opportunity, we do see a significant step up of our growth trajectory. If you look at the last five years, we were able to deliver a very impressive 21% top-line revenue growth, which is driven by significant data center expansion at 52%. And our core business, which includes the client, gaming, and embedded business including Xilinx, growing 10%. Looking ahead, as Lisa and the team talked about, we expect our data center business to expand more than 60%. Then talk about the significant server TAM expansion driven by AI adoption and how we can target market share gain to more than 50%. And Forest and Vamsi talked about the inflection of our data center AI business, which we expect MI450 to start to ramp in the second half of 2026, and we see a trajectory to tens of billions of dollars of data center AI revenue in 2027. And of course, a trajectory Forest talked about to be more than 80% CAGR for our data center AI business. Then coming to our client, gaming, and embedded business, they are vital and the diversifying element of our business model. Jack talked about the client business, the tremendous momentum of ASP increase and market share gain will continue to drive that share gain to more than 40% of the market. And Celio just talked about the significant embedded business design wins and the market recovery which will outpace the market growth going forward. So when you combine that together, we expect the overall company to expand more than 35% in top-line revenue growth. And if you look at our long-term financial model, we expect top-line revenue to grow more than 35% during the next three to five years. We expect our gross margin to be in the range of 55% to 58%. And we expect our operating margin to be more than 35%. The tax rate of 13% to 15% and the free cash flow margin more than 25%. So, as a management team, we are very excited about building on this business momentum we have today and executing toward this long-term financial model. Of course, I'm going to double click on two areas. I know you are going to ask me about gross margin and operating leverage. First on gross margin, we do have multiple drivers we can continue to expand our gross margin. First is scale. It's classic operating leverage. You guys all know our team does a great job leveraging scale volume to drive gross margin expansion. Second is optimization, which is about yield, test time improvement, design for cost. Those are really important for AMD because we actually have a broad product portfolio and we target all different end markets with very high volume. Some of our products last for a long time. So when you make yield and test time improvements, you actually can make a significant impact on gross margin over time. Our operations team has done an excellent job there. I'm very confident they will continue to do so. Third is mix, which remains the primary driver of our gross margin. I'm really excited about several tailwinds we have. First on the client side, Jack talked about how the ASP increasing, moving up the stack, has helped us on the revenue share. Frankly, it also helped us with our gross margin expansion. More importantly, we do think we have upside to continue to expand client gross margin because right now it's still very much lower than the corporate average. But we do think the opportunity to expand gross margin going forward is going to help the company generate tremendous bottom line and cash flow. Secondly, on the mix side, then talk about the server business continued momentum and market share gain. More importantly, we are at an inflection point to gain more share on the enterprise market side. Every point of enterprise market share gain is significantly accretive to our overall gross margin. And Celio talked about the opportunity to outpace the market growth with really high margin business, especially AMD Xilinx's FPGA business is very strong in aerospace, defense, industrial, testing, emulation. We see significant gross margin expansion and growth from those businesses. So with those tailwinds, I feel really good about continued gross margin expansion. And then let's talk about data center AI business. First, Forest mentioned earlier, we are not selling rack-level system solutions. Our business model is not going to change. We are selling GPUs, CPUs, sometimes DPUs. So it continues to be the same gross margin structure like we have today. And today it is true our gross margin is slightly below corporate average because our objective right now is really to scale our business to make sure our customers get better TCO and also getting more market share. So in a fast-growing market, maximizing gross margin dollars is our number one priority. But over time, when we continue to add more capabilities each generation, we also can optimize our designs for workload with scale. We can optimize manufacturing business and operations. We do see our gross margin to continue to steadily improve over time. So when you put it all together, there are puts and takes. That's why we are guiding a range of gross margin from 55% to 58%. The mix dynamics certainly determine that, including the pace and rate of our data center AI business ramp. But overall, we feel really good about the trajectory to continue to expand gross margin going forward. Then operating leverage. 2025 is an important year for us to invest. Given the large opportunities we have, the team is leaning in to accelerate not only the hardware roadmap but system software investment. We also did the acquisition of ZT Systems and several software acquisitions to add our capabilities to address this large market opportunity. But we are very committed to drive revenue growth to be faster than operating expense growth. On the R&D side, we'll continue to set it as a priority. But we are driving AI adoption across all our engineering teams to improve productivity of the company. On the SG&A side, we will continue to tightly manage operating expense and also drive automation and AI adoption to drive operating leverage to drop to the bottom line. So when you look at our long-term model, combining the 35% top-line revenue growth with more than 35% operating margin, it's a very powerful combination. And we do expect to drive our earnings per share to be more than $20 in the forecast period. It's very exciting, and the whole team wants to execute on this model to deliver just like the track record this team has showed you in the past. Now let me switch to capital structure and capital allocation. Our business model generates very strong free cash flow. If you look at 2025, we expect to more than double our free cash flow versus last year. And we have a pristine balance sheet and very strong investment grade. We do view that as a strategic asset. It's a tool in our toolbox we can use to continue to drive the company's growth trajectory. And we are also committed to return cash to shareholders. Since 2021, we have returned $8.6 billion in cash to our shareholders through buybacks. So our capital allocation principle continues to be the same. First and foremost is investing, especially when you look at the large market opportunities ahead of us. Organic investment and acquisitions to really enhance our capability to continue to deliver returns to our shareholders. And from a shareholder return perspective, we'll continue to commit to do buybacks to return cash to shareholders, of course offsetting the employee stock dilution first, but we'll do additional buybacks when opportunities arise. Overall, we will continue to maintain our strong balance sheet and financial flexibility to continue to invest for the future. So in summary, it's a very exciting time to be part of AMD. We are targeting over a trillion dollar market opportunity, and we are driving top-line revenue growth more than 35% and operating margin more than 35%. And our disciplined capital allocation approach will allow us to continue to compound earnings per share to drive EPS to be more than $20 during our forecast period. With that, I will invite Lisa to come back to give closing remarks.

Okay. Well, that was a lot of information for one afternoon. So I promise to keep the closing remarks very, very short. But maybe if I just give you a little bit of perspective. I mean, I've been CEO of AMD for a little over 11 years. I'm super proud of the team that we have, and I think the key message is we've always been really clear about what our priorities are. It's about delivering great products and great technologies to the market. It's about having very, very deep and strategic customer relationships. And I can say for sure that there has never been a more exciting time to be at AMD. If you think about the incredible market opportunity that's out there, if you think about the product portfolio that we have, I think we know how to execute, and we know how to execute at scale, frankly. It's quite different running a $4 billion company to running a $34 billion company. And the only way you do that is with a fantastic team that really knows how to optimize every aspect of the business. And we also have, I think, a history of very strategic and deep partnerships. I think what you're finding right now in the market is the market is favoring those who can partner, those who can bring people together, because at the end of the day, I'm a firm believer that there is no one company that has every solution that's needed in the market. Frankly, what we love is building those partnerships that are like one plus one is much greater than three, in the sense that we bring to our customers something that they could never get on their own, and they're bringing us insight that we would not get on our own, and that's how we're putting this all together. And the other part is to ensure that for all of you as our shareholders and our supporters, we're also committed to having a very exciting market return for you. And I think Jean said it best, so we'll follow up with her numbers. We've shown you a lot of numbers today, but perhaps the three most important ones are best-in-class growth with greater than 35% revenue CAGR, greater than 35% operating margin, and greater than $20 EPS. So with that, thank you again for spending the last few hours with us. We are super happy to be able to spend some time to talk about the long-term view from AMD. And I think we're going to transition into Q&A at this point. Thank you.

Sure, Tim, thanks for the question. Look, the way I would say it is the following. We are super excited with OpenAI and the strategic partnership we announced. I think it sets a foundation. Given its size and scale, six gigawatts over four or five years, I think that is a key foundation. But the way you should think about it is our goal is to have a very broad set of customers. There are multiple customers that we are engaged with right now at similar scale, multi-gigawatt scale, multi-generation, with the notion that MI450 is an extremely competitive solution. I don't want to underdescribe the big there. We've done a great job with the MI300, 325, 350 family, but MI450 opens up a lot more TAM for us. With the work that we've done on both the hardware and the software platform, we've been deeply engaged with a number of customers all throughout this period. I would say even since the OpenAI announcement, it's really opened up some additional opportunities with the notion that there is an insatiable demand for AI compute, and MI450 is an excellent solution. That's the anchor point for the type of growth we're talking about. So yes, OpenAI is an important foundation, but we will have multiple hyperscalers in the same time frame, multiple customers at gigawatt scale, and multiple customers that are looking at multi-generational roadmaps with us. I think as we go forward, we even get more tailored to some of these workloads. Every time we engage at this type of scale, we learn and we get even more tailored to the solutions. I think you saw that in Dan's roadmap when he talked about what we did in EPYC. I think we're seeing a very similar trajectory with the depth of the partnerships with the broad customer set.

On the component cost question, it's a great question. As Lisa mentioned, it's very complex. But Forest and our operations team have been working very hard to ensure not only we have the supply of components, we know exactly the cost of the component. So we have been very disciplined about that to ensure we can support our customers.

Yeah, absolutely, Vivek. Many aspects to that question. Let me try to get through it. Look, when we look at TAM as well as revenue projections, I think we do it first of all in the near term it's bottoms up. Bottoms up to look at what exactly are our engagements with customers, especially when we're talking about things like 2026 and 2027. Frankly, the lead times for wafers, for memory, for components is so long that we need to have that very detailed conversation many quarters out with our customers. Then as we get into the medium term, it's more strategic conversations with customers. We don't do much from a true tops-down perspective because that's a little bit math. But the way to think about our thoughts on the TAM, the TAM we believe in this strategic time frame includes GPUs, it includes ASICs and accelerators. Our view of that has not really changed. I think we've been consistent. I think there's a place for ASICs in the accelerator TAM. ASICs tend to be good if your models are a bit more stable and if you know exactly what's going to happen next. GPUs, we're innovating at such a fast pace, at an annual pace with all the new data formats and all the new algorithmic things that are coming out in the models. GPUs, we believe, will still be the predominant percentage of the TAM. So ASICs maybe 20% to 25% of the TAM, and the rest of that being GPUs. And then in terms of how we think about China, China is a complex and dynamic situation. Certainly as it relates to us being able to service China, as we said in our latest earnings call, we've taken China out of our revenue forecasts because it's too hard to call right now. We'd still like to sell to China, no question. But relative to the TAM, it's also a small piece of our TAM. That's the best visibility we have at this point in time, and we'll continue to update it as we go forward. Hopefully I covered your questions.

Yeah, Joe, let me comment on that. That was part of Vivek's question. Look, I think the key thing for us and for the market is no one enters a market to be a very small share, right? So we enter a market thinking that we can be a meaningful portion of the market we're developing. We're delivering value. That value is coming in technology capability. We are doing things in different ways. We're offering products that have leadership in certain capabilities, and we're also offering overall total cost of ownership. All of those things are important. So certainly from a market share aspiration, we mean to be a meaningful portion of the market, meaningful double-digit percentage of the market. Now, the market changes, all kinds of things change, but our view is that there is no other silicon TAM that is as exciting as the data center TAM and especially the data center AI TAM. So we have gone all in in terms of strategic investments in this area. I think we have a very, very strong roadmap. I mean, you heard the very early pieces from Forest and Vamsi about what we're doing. MI450 was a significant step up. MI500 series is another very significant step up. With that, we see opportunity to really differentiate in this market, especially as there's really a diverse set of workloads. What you need for the highest end training may not be the same thing that you need for your best throughput in inference. I can say for sure it's probably not the same. As a result, there are ways that you can tailor products such that you will get best total cost of ownership. When you're investing CapEx at this scale, it is absolutely worth it for the largest hyperscalers to find the most optimized solutions. That is what we see. The conversation is much more workload specific today than, 'Hey, do you have a GPU that works?'

Yeah, I think, Stacy, the way I would say it is since we're giving a three to five year TAM and the outer years have a little bit less visibility than the near-term years, we would expect the near-term years to grow faster than 80%. So greater than 80%. And I think we are comfortable with tens of billions of dollars being in the zip code of where some of the thoughts are overall.

I think you covered it. I think when we look at the current consensus for 2025, it's roughly in line, and we do expect like Lisa said to grow faster.

Yeah. So, Josh, thanks for the question. I think the best way to say it is we have very deep relationships with the hyperscalers and all of the hyperscalers and many of the top AI native companies. You can imagine that everyone is super interested in MI450, and we expect that MI450 will be deployed at very significant scale. In terms of multiple gigawatt customers, my comment is really around just the scale of forecasts that we're getting from customers on their near-term needs. So there is a desire for a significant amount of compute. We are working with the supply chain today to make sure that we have the broad ability to support all the compute that is required. I think we have built a supply chain for the type of growth rates that we're talking about, and the customer momentum is very strong. So much of the work right now is continuing to work with Vamsi on some of the software aspects of it, but it's really an execution mode for MI450 as we get those fully ramped up and validated. We would expect to convert a number of those opportunities.

Yeah, sure. Aaron, maybe I'll start and then I'll let Forest talk about optics. Look, semi-custom has been in our strategic tool chest for the last number of years. I really believe in this business model. It's actually not a product. It's actually a capability to take our IP and really tailor it for specific applications. I think Celio has done a particularly good job at taking all of the semi-custom components and our technology IP to some of his top embedded customers, and they've seen a lot of value in that. So you saw in their aerospace and defense customer, automotive, a number of communications sockets as well where there isn't something that's very easy to pick off the shelf, but we have all the pieces for them to put it together. To your specific question about data center, we have several data center semi-custom opportunities. They tend to be more not the compute unit itself but some of the attach around the entire system, including some networking components and some other specific components. I think if you were to fast forward and talk about how we could imagine semi-custom evolving, I think you can imagine semi-custom as built off of our GPU compute capability. The beauty of chiplets is you really can customize pretty easily. You could take our entire foundation and say, 'Let me take this compute die off the AMD standard product and put on a customer-specific standard product.' I don't know what you call that. Do you call that a GPU or do you call that an XPU or a GPU plus? But at the end of the day, what we're trying to do is provide workload-specific optimization for the highest volume sockets. As I said to Vivek's question, I still believe that standard product GPU will be the largest driver of growth just given the rate and pace of innovation that's happening there. But there may be opportunities for us to do customized GPUs as well if there are specific workloads or use cases. I think it just broadens our overall capability in the data center space and really across the computing space.