Well, good morning, everybody. I'm Mike Sullivan. I'm the Head of Investor Relations at Applied Materials, and once again, I have the honor of being the first to welcome you to SEMICON West. It's my pleasure. We really thank you all for being here. Applied has a very long tradition of hosting a technology breakfast at SEMICON. We've been doing it for years, and we've been looking forward to seeing you pretty much all year and spending time with you. A big focus of this year's SEMICON, of course, is really understanding what is the state of the AI build-out and what does it mean for companies all across the entire technology ecosystem. The figure of merit that everybody's focused on is tokens per second per watt.
When you look at today's presentations, what you'll see is that ultimately, every AI system and every AI chip depends on two ingredients, made of two key ingredients, and those are transistors and wiring. What you'll see today is that over 60% of the transistors and wiring, 60% of those materials are put there by Applied Materials. What that means is we have an enormous opportunity and responsibility as a company to make them even faster and much more energy efficient. We know the entire AI ecosystem is waiting for breakthroughs, and inventing those and accelerating those, it's a challenge that we love. It's a challenge we accept. You saw a video a second ago. Yesterday, many of us were in Sunnyvale, California, for the unveiling of the EPIC Center. All of the world's top chip makers were there.
Intel, TSMC, Micron, KIOXIA was there, SK hynix, Samsung, all there talking about how they're going to be working with us to develop these innovations, accelerate them, and bring them to market together. We're extremely excited about that. What I wanted to do just now quickly is give you today's agenda. Traditionally, what we do at SEMICON West is we focus on our core Semiconductor Products Group, and that's Prabu Raja and his team. Of course, they're here, and they will be speaking. This year we're doing more. We've invited Gary Dickerson to give you an update on the state of the industry and on our strategy. In addition, we've asked Keith Wells to join us this year for the first time, and he's going to give you insights into our fast-growing process control business.
We've asked Tim Deane to come and explain how we're accelerating the growth of our services business. Usually at SEMICON West, because we're in quiet period, our CFO is kept hidden in Santa Clara. This year, we've invited Brice Hill to talk about our financial progress as a company and our plans and targets for the future. We're going to be giving you a lot of new data today. Then all of our presenters, they're going to take the stage to answer your questions. I've got two final quick housekeeping items for you. Number one is, as I mentioned, we are in our quiet period, so if you have near-term questions, we're going to answer those for you, but next month on our earnings call. Finally, I've already had people saying, "Where's the presentations? Where are the slides? I can't find them on your website."
P lease know that you don't need to write anything down. We have a tremendous amount of new information. A lot of the forecasts that we had in the past have changed. Many of them have increased, so there's a lot of new data. There are new financial targets. All of those are going to be available on our website as Brice concludes his presentation. That's going to be at about 9:45 A.M., so please relax. You don't need to write anything down. I promise you it'll be there at 9:45. That's about it for me right now. I'll come back and help you with the Q&A. But in the meantime, thank you again. It's so great to have you with us, and I'd now like to welcome to the stage Gary Dickerson. Hey, Gary.
Well, thanks, Mike, and thanks for all of you joining us here today. This is an incredibly exciting time for Applied Materials. Many of you probably remember nine years ago, this thing is—o h, there we go. Nine years ago, we had our AI Design Forum, and many of the top innovators in the data center were at that event. Over the last decade, Applied, we anticipated that AI would be the major driver of the industry, and we've been creating enabling capabilities to position us to grow quickly going forward. That's what you're going to hear today. AI is driving the global economy, it's driving the semiconductor industry. The fastest-growing wafer fab equipment segments in the industry driven by AI are leading-edge foundry logic, DRAM, and advanced packaging.
In all of those areas, Applied is number one and positioned to outperform, and you'll see that today in the subsequent sessions. One thing that, I've been in the industry for a long time as an innovator. I'm an engineer. I love innovating with all of our partners. Always there's a focus on technology innovation and performance innovation, and especially for AI, innovating in chips and packages for tokens per second per watt is a race for every one of our customers. They're racing for every new inflection to be first to market with design wins. We have these incredibly deep relationships, I'll talk about that today, with all of these leading companies. But the thing that I would say has changed more than I've seen any time in my career this year is the focus on capacity innovation, yield, and output innovation.
We're in an environment where demand is much bigger than supply. The chips have never been more valuable. So yield innovation, more good chips per wafer, higher- yielding packages is incredibly important, and it creates great opportunities for Applied Materials. We have been creating advantages that position Applied Materials with the most enabling technologies, and I will describe that. In materials innovation, Mike talked about over 60% of the materials in the chip are coming from Applied Materials. Integration innovation is incredibly important. Mike talked about EPIC, and we had all of the key R&D leaders through the technology stack on Sunday. Yesterday morning, it was really amazing. We had hyperscalers. We had the top companies designing next- generation AI servers. We had all of the top chip manufacturing companies, design companies, materials companies.
One of the things that for me was very notable, every single one of the—t hese are the top R&D leaders in the entire technology stack that were there, which is very rare, if ever, to have all of those people in one room. What they said is it's not good enough to innovate on just components. You have to innovate from a system level. We talk about high- velocity co-innovation coming together because the workloads are changing very quickly, and the need for higher velocity innovation has never been greater than today. This integration innovation capability that we've built at Applied Materials, certainly it's co-optimization through that whole tech stack, co-optimizing with all of the technologies. Mike talked about how Applied is the leader in transistors, wiring, advanced packaging. Again, co-optimizing across that whole flow is incredibly important.
Applied has leading integration innovation teams working 10 years out in the future, co-creating those future chip and packaging architectures from a system standpoint. Again, that's never been more important than today. As I mentioned, good chips per wafer. Yield in advanced packaging is incredibly important, and Applied has leadership in the highest resolution materials analysis. We're 2x bigger than our nearest competitor in eBeam, which Keith Wells will talk about later today, is incredibly enabling to accelerate innovation for transistors and wiring and high- speed memory and advanced packaging. These capabilities are tremendous. Tim Deane, who leads our services business, will talk about how we've created advanced service technologies with AI that will accelerate more good chips per wafer and more wafers out. We'll also talk about, Brice later will talk about value creation.
Applied being positioned to grow very quickly in wafer fab equipment. Over 20% increase in the coming years in revenue per tool in our services as we're accelerating R&D, enabling more good chips per wafer, enabling higher wafer output. Again, just for me, I'm meeting a lot of these top CEOs every month, top R&D leaders constantly. I probably will see all the top CEOs in the next two weeks. That's because, again, they're all racing to drive performance leadership at these inflections, and I have never seen the pull stronger than today in yield innovation. The top priority for them is good chips per wafer and more wafers, especially again, when the chips are so valuable. You'll also hear about how we're growing our gross margins and operating margins through the day today. I've been, again, in the industry for a long time.
I've always thought what we do is incredibly cool. I believe that we deliver miracles all the time in the semiconductor industry. There was a period of time where there wasn't growth in wafer fab equipment. There was a period of time when you had the transition from 200 mm to 300 mm. Then Moore's law started slowing down, and more of the growth was driven by power, performance, area cost, and time. You see a 14% compound annual growth rate. We're not going to give a specific WFE forecast today, but what I would say is that I have tremendous confidence computing demand is going to grow at a tremendous rate. The compound annual growth rate is going to be very strong. Very confident in that. You'll hear today also how Applied is using AI across everything that we do.
The pacing factors are fab space, certainly supply chain components, energy, financing. Some of those factors will impact the rate of growth. Value pricing can increase the rate of WFE growth. I have very high confidence as we are working across this whole ecosystem and technology stack, and I see how we are using AI inside Applied Materials, it is fundamental to our competitiveness, and I will describe that also, and Brice will talk about this later today. You will also hear from our Chief AI Officer, who started his PhD at 16. Brilliant guy. We formed an AI leadership team three years ago. Very clear ROI inside Applied, and we will describe that. Leading-edge foundry logic and DRAM compute memory. This shows the percent wafer starts for mobile, PCs, and data center. What you can see in just a few years, there has been a tremendous inflection.
A few years ago, in leading-edge foundry logic, mobile was the major driver of wafer starts. Now, data center has crossed over, and data center is growing at a tremendous rate going forward into the future. In DRAM, you see the same thing. Data center, high- performance computer, really driving wafer fab equipment starts. The great thing for Applied Materials is that in both of these segments, we are the leader. We are enabling the key inflections for performance and power and the race for our customers for their design wins. I think as all as you know, the chips in the data center are huge. They are at the reticle field limit. That drives tremendous growth in wafer fab equipment, and this is going to continue to accelerate in the coming years. New AI applications driving growth and diversification.
Yesterday we had key R&D leaders that are responsible for innovating with the next- generation AI servers. We had hyperscalers. We had really all of the companies that are leading the AI technology stack, at this event yesterday morning, and it was really amazing. What they talked about was that workloads are changing very, very, very quickly. There is a tremendous need for improvements in tokens per second per watt or tokens per joule, one of the R&D leaders talked about. What we have seen from a standpoint of Applied Materials in calendar 2026 is a significant growth in agentic AI compute demand. So we have increased our wafer fab equipment forecast going forward because of this increasing demand. On top of that, in the future, you have physical AI.
On the right side of this chart, what you see is the mix from a silicon area perspective. So you are going from more GPU- intensive architectures to, in agentic, a more CPU- intensive architecture. For Applied Materials, we are very agnostic about this mix. What I will show is that more of these devices are moving to the leading edge faster, and that is where Applied Materials has higher market share, and it positions us well for significant growth going forward. This is an AI factory pod. How many people here know what a pod is? Not too many people. So a pod is a modular building block for an AI factory. What you see here, this contains all of the components that go into a pod. An agentic AI consumes about 2x-4x more wafers than a generative AI pod.
In this next chart, basically you will see that the number of wafers is increasing, 2x and 4x, depending on the configuration. This is Rubin and Rubin Ultra. Then you look at the device mix per pod, 85% of the content of the agentic AI factory is leading-edge foundry logic, DRAM, and advanced packaging from a standpoint of wafer starts. Applied Materials, what we have talked about earlier this year, is about 80% of the incremental growth in WFE this year is in these three segments. We see this growth continuing forward. Our position inside these three segments is very strong. We have, as I mentioned earlier, these deep co-innovation relationships with all of these leading customers. We, again, we have high clarity because we are co-creating these architectures with these leading companies.
When I am meeting, next week I will be with CEOs and R&D leaders, when we are meeting, we are focused on the top five to 10 enabling technologies for next- generation technology nodes. They are laser- focused on that. Applied Materials has the majority of those enabling technologies. Again, we have integration innovators that are working in trusted, deep partnerships with all of these leading customers, enabling the higher velocity for these inflections. The focus on improving the tokens per second per watt in the data center is driving more chips to the leading edge. That is what you see here, how long it takes for different generations of technology. What you see here, server CPU, GPU, networking, ASIC, all of those chips are moving faster to the leading edge, where Applied Materials has a very strong position. I talked about this earlier.
The race for AI computing leadership is the most important race in the global economy, in the semiconductor industry. As I mentioned, there is this technology race with chips, and multi-chip connectivity is incredibly important, how you connect all of these computing components together. In Applied, as I mentioned, we have the deepest, the strongest relationships in co-creating innovation in these areas. As I talked about earlier, never in my career have I seen a stronger pull from customers for more good chips per wafer and more wafers, faster. That is what is on the right side of this chart. Again, Applied Materials, over many years, we have been building leadership capabilities in materials innovation, in uniquely integration innovation with our connected and co-optimized technologies, our integration innovators, and our innovation platforms. That is exactly what EPIC is all about. I will talk about that in a minute.
Yield innovation, I will talk more about that. Most critical technologies for AI computing roadmap are shown here. Again, there is a race with all of these companies producing these technologies to be first to market with design wins. It is a very exciting race. We love co-innovating with all of these partners. Applied is the leader across all of these different areas. This shows leading- edge foundry logic from 5 nm to 1.4 nm. You see mobile high- performance computing and data center. Remember that data center is driving more and more wafer starts going forward. Here what you see is that wafer fab equipment per start is increasing node over node. You see Applied's addressable market growing to more than 50% through this time period. You see our share of served market growing.
When Prabu, which is one of the most brilliant and trusted innovators in the industry, is up here next, he will tell you how we are enabling these inflections, how Applied has built over many years capabilities that are unique to enable these technology inflections. If we look at advanced DRAM, same thing. WFE dollars per wafer start, served market growing to more than 60%, and Applied gaining share in served market node over node. This is maybe for the people that are not deep into the technology, you have these different technology nodes. 6F² is a certain technology for DRAM compute memory. Then you are going to 6F², CMOS Bonded to Array, 4F², 3D DRAM, all of these things. Main thing, the main thing, as you move to these future technologies, especially as you are going more vertical, Applied is in a tremendous position.
Those of you that have been around for a while know that we gained around 10 points of overall DRAM share over a number of years. We are growing quickly in this segment. With these three companies that are all EPIC partners, we have incredibly deep co-innovation relationships. Over 60% of the served market in leading-edge foundry logic and in DRAM, Applied has the most enabling materials innovation technologies. We have unique integration innovators. For our customers, again, it is a race for who will be first to market with the best technology for design wins. So, great opportunity for Applied going forward. This shows the WFE market segments percent of total wafer fab equipment, the technologies inside those market segments from Applied Materials, and then our positions.
So if you look at, again, enabling these major inflections, enabling the race for better chips, better packages. In deposition, Applied is about 2.5x larger than our nearest competitor. In material modification, and Prabu will talk about this next, we are greater than 2x larger than our nearest competitor. In eBeam, which is 200x higher resolution than optical, you cannot fix what you cannot see, Keith will show how that business is growing over 50% this calendar year. That technology is incredibly important to accelerate innovation in transistors and wiring and packaging. Again, 2x approximately larger than our nearest competitor in eBeam. We are a leader in conductor etch in foundry logic and DRAM. So this enabling portfolio is why customers are working so closely with Applied Materials to co-innovate.
I can tell you again, when I am with these R&D leaders, when I am with the CEOs, it is so much fun. Again, I really believe we create miracles all the time. We make the nearly impossible possible. So having this technology portfolio that we have created over a number of years, positions Applied to be incredibly strategic for our customers and for fast growth going forward. I have talked about the materials innovation and the ability with these technologies also to connect everything together. That is important. I have talked about integration innovation with co-optimization of these technologies, and you will see integrated platforms where you are taking multiple technologies and connecting them together under vacuum for better electrical performance, Applied is unique in those capabilities. We are unique in the integration innovation teams that we have at Applied Materials. We have built these teams over nine years.
They're world-class in engaging with all of our customers. The innovation platforms, I will talk about EPIC next, how that fits into this race and integration capability we have. As I mentioned, we have the highest resolution material analysis capability with eBeam, and we have AIx. AIx is Actionable Insight Acceleration services that are accelerating good chips per wafer and wafer output. I will talk about that also in just a minute here. So eBeam, eBeam is a business for Applied Materials, high resolution, about 200x higher resolution than optical. You can see into advanced structures in ways you cannot see any other way. Keith will share with you today many applications that are accelerating R&D innovation with our customers and accelerating Applied's R&D velocity across our entire portfolio.
This is an incredibly important technology, strong pull from customers, growing more than 50% this year, and will continue to grow at a very high rate going forward. In eBeam, again, Keith or in his metrology inspection business later today, he will talk about three growth engines. Optical is growing over 50% this year. We have a lot of a pipeline of enabling technologies that we're bringing to market. That business will grow fast next year and also going forward. And eBeam, growing over 50% this year, also growing significantly. This acceleration across the entire portfolio with this unique technology is incredibly important for Applied Materials. Again, all of this data, AI, you need actionable insight and actionable data.
This gives you massive actionable data that you can feed into AI-enabled servers, that's what our AIx platform is, to accelerate yield, good chips per wafer output, and accelerate R&D. The service business. I have to say, I love Tim. I love all of our team. Tim is fantastic, and he, again, is so deeply connected with our customers. All of them are in a race. Every chip is worth a tremendous amount of money. So more good chips per wafer, more wafers faster, is really what we're driving in our service business. We created this AIx Actionable Insight Acceleration server platform many years ago. We've been innovating with advanced sensors in our platforms, and today we have over 37,000 chambers connected inside customer fabs with AIx. The majority of those are remotely connected.
What we're seeing, and this is also where we're deploying these advanced service technologies, AI with predictive diagnostics, we can match the chambers faster. Tim will talk about that later. That's really critical for good chips per wafer. Again, there's many innovations that we're driving here. This business growing more than 20% this year, in the mid-teens going forward, and again, just tremendous value for our customers. EPIC, we have all of the top leading companies that are in the race for AI compute innovation as part of EPIC. What we do inside of EPIC is we are working with customers through the technology stack, partners through the technology stack, many nodes out in the future, N+1, N+2, N+3, N+4, and co-creating these architectures. I've already shown how Applied is the leader in material innovation, integration innovation, yield innovation.
Our customers, they are bringing their top innovators to co-locate with Applied Materials innovators. For them, it is early access to these innovations. We have an incredible pipeline of innovations. Our teams are amazing in delivering innovations that are critical for these fast-growing segments that are enabling AI improvements. Our customers want early access to those innovations and then integrate that into their devices. So having those innovators co-located is a really big deal. Inside of EPIC, also, what we are doing is we are running loops. We have over 100 test vehicles, we have customer reticles, and we can innovate in the transistor very fast. We can innovate in wiring very fast, in modules, in high- speed memory, or in packaging very fast. Again, for customers, what is really important is being first to market with leading next- generation technology.
After that performance innovation in the chip and the package, they want to transfer that technology first time right into their R&D facilities, and then ramp yield, good chips for wafer, packaging yield, as fast as possible. It is a race for every one of these companies. For Applied Materials, we are designed in earlier with our products, systems, and services. We also have incredible visibility to what matters, where to invest, where not to invest, because we are co-creating 10 years out into the future with this platform and with the relationships that we have with customers. For the customers and for Applied Materials, we are driving R&D productivity and efficiency. Okay, let's hear from customers.
At EPIC, Micron engineers and researchers will work side by side with Applied Materials teams to co-innovate the manufacturing technologies needed to scale next- generation memory economically. By aligning our roadmaps and bringing our teams together, we can move faster from research to commercialization.
This center is a milestone in semiconductor equipment R&D, bringing together global chip makers, equipment companies, and world leading research institutions to design the future of semiconductors.
AI is driving the need for breakthroughs at both the device and package level, from faster transistors and better interconnects to advanced packaging. Meeting this challenge requires trusted partners working closely together, and EPIC gives our teams the opportunity to work side by side on new materials and process technologies.
The brightest minds from AMAT and SK hynix will tackle the toughest, highest value inflections in the AI memory roadmap across HBM, DRAM, and NAND. Combining SK hynix memory expertise with AMAT equipment and manufacturing leadership is how we will jointly navigate the incredible complexity of AI on memory scaling.
The next frontier of AI will be defined by how seamlessly we integrate compute, memory, and connectivity into high- performance systems. By pairing Applied Materials' engineering and manufacturing capabilities with Broadcom's system and custom silicon design, we are bridging the gap between hardware requirements and packaging innovations. This will accelerate the path from concept to production for next- gen AI systems.
Okay. Again, all of our partners are incredibly excited about EPIC and our ability to co-innovate faster together. Let me just spend one slide on materials innovation in adjacent markets. We recently updated, I believe in our last earnings call, that these businesses are around $400 million per quarter in terms of run rate, and I wouldn't model anything near term beyond that. Let me describe these two businesses that are in this other category. Our display business is a little over 20% operating profit today. We've announced recently this MAX OLED technology. What's important here is this technology enables OLED to go to larger display sizes, IT, TV, automotive, and eliminates the fine metal mask, which has been the major technology constraint. We're working with leading display companies to implement this technology.
Again, the key focus here is the same thing that I talked about earlier, is bringing those yields up to the tipping point for this technology to move into high-volume manufacturing. We are making progress, but again, I wouldn't model anything different today. Our SAM goes up significantly as OLED adoption increases. One thing also about our display business, we are bringing our leadership in display deposition and eBeam into semiconductor panel packaging, and that will be worth a significant amount of money, not in the display business, in our semiconductor business going forward. The other area, just very briefly, very early on, again, I wouldn't model anything at this point, Applied has announced recently this SENZ brand. We have created waveguide technology that has the leading optical performance at the lowest cost.
I can tell you there's a tremendous amount of innovation in this technology for AI glasses. Around 90% of the flow to build these waveguides are Applied custom innovations. Here, the strategy is to sell waveguides and eyepieces, but again, for both of these businesses right now, I would still model the roughly $400 million per quarter, and I think Brice later will talk about, combined, these businesses in our future view are over $2 billion. They are multi-billion dollar upsides, but I wouldn't model this yet. Again, as I said earlier, I have never had so much fun. I love working together with all of our partners. Next, Prabu will talk to you about our semiconductor business. As I mentioned earlier, Prabu is one of the most brilliant and trusted innovators in the entire semiconductor industry.
I talk to him probably five times a day, every day, seven days a week because again, we love this innovation. Now, let me turn this over to Prabu. Thank you.
I think it's always difficult to keep up the energies. I don't like to come after Gary. It's difficult to keep up the energy. I think if you really look at those, if you look at those, always think about, if I were to do one page, what do I do? One page, my messages. We saw this AI inflection early. We invested in this inflection early. We built our AI compute leadership over many, many years, over more than 10 years. Now it is the opportunities. It's a big tailwind for us. This is a simple message. We built this leadership. I spend lots of time with the customers, and the discussion what I heard very different. Now I am going to tell you why I am confident that we are going to outgrow the market. We are going to gain the share. That's what my presentation is about.
Really look at those, the foundation. AI is all about power, performance, and bandwidth. That is what all AI is about. The foundation for this AI compute is leading-edge logic, high-speed memory, advanced packaging. When you say leading-edge logic, transistor and more wiring. High-speed memory is DRAM, high-speed DRAM, and high- bandwidth memory, and packaging is all about chip-to-chip wiring. Really look at all these three segments, the fastest growing segments now today, and like I said, we are number one in each of these segments, and we are enabling these segments. That is why I am confident about these two points, or more than two points of share increase. Talk about advantages. What is your main advantage? Really look at those. Like I said, we saw the inflection early, we invested in it early. That is why we are number one in each of these segments, leading-edge logic, DRAM, and advanced packaging.
We built broad and enabling portfolios for these inflections, and we can connect them in unique ways to solve technology challenges, which no one else can do because of our broad portfolio, because we know how to connect them. We are building EPIC, a new R&D collaboration model with our customers. This is for faster innovation to customer commercialization and a higher innovation success rate. I will go through in details. Our AI leadership is built over years, not today. If you really look at those, we invested in R&D centers, we invested in capabilities, and we built partnership over years. If you really look at the R&D center, come back to R&D centers, we saw the packaging influx much, much earlier. We invested in the packaging R&D center in Singapore in 2012.
We saw the materials influxes, materials engineering, and started this materials lab with the NUS in Singapore in 2018. Also, you can see the full flow lab in META Center in Albany in 2018. Now, the EPIC, it take into a whole new level, all about high- velocity co-innovation with our customer. That is why our customers love it. We also built unique capabilities with innovators who could connect all the way from materials to process, to equipments, to device, to systems. They understand better, they know how to connect it. And we build the partnership for complementary capabilities. This is a good example. We do not have bonding, and we built die- to- wafer bonding, we built a partnership. Also we acquired companies. We know panel is coming. We acquired companies, Tango, PVD panel, NEXX, and also a plating panel, and also Sigray for X-ray.
If you really look at it, this provides us great foundation for our future growth. AI is driving WFE market. In AI-enabled WFE, the fastest growing segments are foundry logic, DRAM, and advanced packaging. We are number one in each of these segments. In the past five years, Applied Materials has outperformed the market in all these segments. In the next five years, the market outlook is even more favorable. 75% of an incremental WFE growth will be in these segments. Like I said, AI is all about power, performance, and bandwidth. There are architectural influxes that will enable these devices, power, performance, and bandwidth. In logic, you can see gate-all-around. Better transistors, more transistors, and more wiring. Backside power, even more wiring. DRAM, going through the influx, and High Bandwidth Memory. Even 6F², a lot of innovations left.
4F² and 3D DRAM for higher density and lower power. Packaging, system-level packaging, 1,000x more IOs and lower power. Applied has leadership in all these inflections. Today, I will show you how we are growing our SAM and share in these critical inflections. Really look at this. All the inflections are going 3D. One thing if you look at common laws, everything is going 3D, which means more materials engineering. This gate-all-around transistor example is a case study for materials engineering in action. Gary talks about miracles. This is where it is happening right now. Really look at this. You think of it what a gate-all-around transistor looks like in the picture. In reality, how it looks, this is how it looks like. At atomic level, atom by atom, how it is arranged. Really look at those. Where is the complexity?
Between the two nanosheets, 10- nanometer space, 100 Å, 10 nm. There are more than five distinct materials, one on top of each other, each one of them 1 nm-2 nm thickness. Now we really look at those. The interfaces between these materials need to be engineered for best performance. Interface dominate. Interface are thicker than the materials itself. So you got to play with the interfaces. That's where materials engineering coming in. Every angstrom matters. Every angstrom matters. Even depositing, etch, modify, analyze. Every angstrom matter. You need this atomic level precision at an industrial scale. That is commercialization. This is the power of our unique and connected portfolio. Really, Gary talked about this slide. Applied has a broad portfolio across depositions, etch, modifications, and metrology and the inspections.
We are leading in many of these technologies, and we have unique ways of connecting these technologies for a better device performance. Like you saw on the last page, we understand these inflections better, and we know how to address them by connecting our technologies through co-optimization and integrations. Co-optimization, where independent technologies are optimized for a better performance. You saw the last page. Integration, where multiple technologies are integrated in one tool under vacuum. You saw last page. Five different materials or more. The interfaces, all 1- nanometer thickness. They cannot be exposed to air. If it's exposed, it's gone. You don't see that. That's where it need to be integrated. Also where we don't have— we are extending these technologies to our partners where we have complementary technologies. These connected solutions solve industry's most critical challenges. Example, co-optimization. This is one transistor contact.
I can tell you, this is one of the most critical step in the device. Traditional step, it takes three steps to do that. You will see that etch, deposition, and an epi deposition. Traditional model, if you do, it limits the transistor performance. You don't get good performance, let me put it this way. In a new co-optimized approach, what we do? Where etch, CVD dep, epi are improving the performance very significantly. The number one bottleneck for the customers today is transistor performance. Device makers target 15% performance node over node. It's a full node I'm talking about. These co-optimized solutions deliver 5% performance gain. This alone deliver 5% performance gain. Value for our customers, device performance, and yield. Value for Applied Materials, cumulatively, these products will deliver over $2 billion revenue for Applied Materials until 2030. Another example, a wiring. Wiring consume 50% of the chip power today.
As the wires become smaller, node over node, resistance goes up and further increase the power consumption. Our portfolio defines wiring roadmap. Our portfolio really defines wiring roadmap. We talked about these solutions. If you put multiple steps, they cannot be exposed to air. This integrated solution, this product is a good example. This integrated IMS solution reduce the resistance node over node. I have been in PVD, this is for many, many years. Every year we are the bottleneck for wiring. We find a way to remove the bottleneck, and we make it happen. You can see node over node. These copper wiring products will deliver $3 billion revenue in 2026. This is just one of our integrated product. Our integrated solution portfolio revenue grew 20% to 30% of our system revenue today. Let me tell you how important Applied Materials is for AI compute.
Over 60% of the materials on a chip today are created by Applied Materials equipment. We have leadership products in transistors, wiring, and advanced packaging, not just a new product, going back decades. In the last 12 months, we launched 13 new products for these three segments, transistor, wiring, and advanced packaging. EPIC takes it to a whole new level. If you really look at those innovations from the universities on materials all the way to commercial chip, take 10- 15 years. That is too long. It is a sequential process. It is very slow. It may not work anymore. In the EPIC, what we do is a parallel model, compressing the time limit by 2x, where you can see that materials, product, and development of customers all work together to solve the problem. Look at the customers and partners. Universities co-innovate with us under one roof.
Parallel development, value for our customer, earlier access to materials, earlier access to technologies. This means for them, faster innovation, faster R&D, faster ramp, and faster commercialization, HVM. For Applied, it will tell us where to invest. R&D dollars efficiency, and more important, we are designed in early in our customer. Imagine these kind of complicated, complex structures. We are designing much earlier with our customers on the advanced nodes. We talked about unique advantages. Let me talk about what the big opportunities we have. AI is driving more demand for applied logic transistors and wiring technologies. Why? Larger dies, more transistors, better transistors, and more wiring. Our leadership in logic transistor and wiring, these technologies are moving to memory now. Also, our leadership in wiring technologies is extending to packaging. On-chip wiring is moving to chip-to-chip wiring right now.
All of this will deliver strong SAM and strong share growth for Applied Materials. Here is an analysis of modern mobile chip versus AI training chip and agentic chip. Three key observations. The logic silicon area transistor grows 70x from mobile to agentic AI. The number of logic transistor grows 20x mobile to agentic AI. The number of wiring layers triples. Remember, wiring is one of Applied's largest business, where we have very strong product. This is how AI compute is driving growth across our businesses. For decades, we innovated logic and wiring technology. I keep repeating, logic and wiring technologies. AI is all about moving data faster and with a lower power.
Because of that, our leadership technologies in transistor wiring are moving into memory right now. DRAM is more aggressive, most aggressive in adopting these transistor technologies, moving from planar to High-k/metal gate, then moving to FinFET. In DRAM, the number of wiring layers are more than doubling from conventional DRAM to HBM DRAM. Also remember, NAND is following transistor technology DRAM, both in wiring. In wiring, in fact, it is more right now. You can see 5x- 10x . This inflection will increase Applied SAM and share. Let me now show you how our SAM and share are growing in each of these node. If you look at this leading edge, the SAM grows around from $12 billion at 3 nm to $15 billion 1.4 nm , and our share increases by 3 points over this transition.
In DRAM, we said in the past that 6F² will be around $6 billion. Right now, you can see that from 6F² to 4F², I think it is increasing over 40%, and even for 3D DRAM, revenue is even more. We expect to increase our SAM share by 5 points. Wiring. I talk about wiring, again and again talk about wiring. We are number one in on-chip wiring over many, many, many years. We are taking that leadership position from on-chip wiring to the chip-to-chip wiring connections, High Bandwidth Memory, 3D IC logic. The same technologies we use to drive copper roadmap inside the chip are being adopted to connect the chips using micro bumps, using bumps, using TSVs, using RDLs.
Because of this, our advanced packaging is now expected to grow more than $5 billion within a few years, and we expect to outgrow the market in next five years. Let me give you one example of our leadership in the packaging in HBM. Applied enables three-quarters of the packaging process steps from TSV formation to micro bumps, both front side and back side of the wafers. We are number one HBM packaging with more than 60% SAM share. HBM continues to grow, and we expect over $1 billion this year alone. The next big packaging inflection is hybrid bonding. When you look at this, people don't realize that there are many steps. You can think of it as three groups, the process before bonding, the bonding itself, and the process after bonding, we call post-bonding. Applied Materials portfolio addresses 80% of the steps across all these three areas.
In bonding step, we partner with Besi, where we have die-to-wafer bonding, we call it Kinex, integrated tool. Our portfolio is just as strong in both pre- and post-bonding steps. Hybrid bonding is already being adopted in HBM, 3D IC logic, and also co-packaged optics. The next big opportunity is in HBM. Hybrid bonding will double our SAM as compared to micro bumps and TSV. Another major inflection transition is silicon wafer interposers to panel. I repeated many times. Earlier, I told you we invested in packaging earlier, 2012. That has given us leadership position in wafer-level packaging. Today, we are doing exactly the same in panel packaging. Earlier, we saw the inflection early, we are investing in early.
Applied has already built a broad portfolio for panel inflections, including both organic and inorganic, such as recently we talked about NEXX for panel copper plating. Also, a few years back, we bought a panel PVD company. We saw this early, and we are investing early. We are very well-positioned with the customer and confident to further grow our share. I will close today with a few words on our growth opportunity in ICAPS. An important part of ICAPS, what we don't normally talk about, important part of a data center build-out is power and photonics. These are growing very rapidly, and we expect over $1 billion revenue this year. Overall, I see that ICAPS market is growing this year, benefiting from 28-nanometer transistor. A lot of these nodes are transitioning to 28 nm, where Applied has a really good position with the High-k/metal gate transitions.
In the future, we expect the physical AI to be a big growth driver for ICAPS. To summarize, AI is growing WFE to much higher levels, and Applied SAM is around 55% of the WFE market. Next, around 75% of all of the WFE growth we expect through 2030 to be where Applied has number one leadership positions. Leading-edge foundry logic, DRAM, advanced packaging. As I showed you, Applied is increasing both our SAM and our share in all these three segments, three areas. As a result of this, Applied expects to gain over 2 percentage points of WFE share by 2030. This growth includes our out-performance in metrology and inspection market, which Keith will now discuss. Thank you. Now over to Keith.
Thank you, Prabu. Hey, it's great to be here this morning. I'm Keith Wells. I'm in charge of our Imaging and Process Control group, but you can think of me as the M&I guy at Applied. That's what I do. We drive all the M&I business within Applied, and that's what I want to talk to you about today. We have three theses that are driving our growth in M&I. First is we see remarkable growth in optical inspection. I'm going to go into this in a little bit more detail in a minute, but this is a very, very big market. It's $9 billion. Today, we only serve about $2 billion of the $9 billion market with our products.
What I set out to do when I came to Applied six years ago was to create a complete portfolio so that we could address the $9 billion in this market, and it takes a few years. This is not simple to make a lot of these technologies come to market. We won't really talk about these today, but I can assure you that in the next few years, you're going to see new products introduced in the optical market to go after this business and capture more of this TAM. Second thesis around our growth is we are the leaders in eBeam, and I'll give you many examples through the presentation today. Gary talked about it, Prabu talked about it. We'll show you in real concrete terms why we are the leader in eBeam with our technology.
And then finally, you have heard it throughout the presentation today, we are going to talk a little bit more about how synergistic we are to help drive the Semi Systems business, and how that will result not only in growth for our business, but growth for Prabu's business. Let us go into a little bit more detail. First of all, Gary already told you this, but in optical inspection, we grow 50% in revenue from 2025 to 2026. We see very strong CAGR going forward in this segment. Customers want alternatives, we are providing alternatives, and we are benefiting from that. We also see positions, as I said, in the segments of these markets that we do not participate in today. There are $7 billion of additional TAM out there that we can address, and we will be introducing new products over the next few years to address those.
It will not be easy, but in some cases, this is owned monopolistically by other companies who fundamentally our customers are pulling very hard to. They want solutions. They want alternatives. So I think that is a very strong thesis to our growth plan. Second is eBeam. Again, 50% growth between 2025 and 2026, mainly driven by the need to drive yields. Very important. And we see strong share gains over the next five years in this segment. And what we did a few years ago is that we brought out cold field emission technology, which is very high brightness electron sources coupled with high-energy electrons. And by doing that, we were able to gain 2x in revenue over our nearest competitor. That technology, those architectures, created differentiation and have really driven this business.
And we intend to keep our leadership in electron optics by producing many new tools over the next few years and introducing them. And finally, the big theme here is how do we co-innovate? How do we work together with the Semi Systems, with our AGS group, to give them thousands of data points so they can do experiments, they can increase the R&D pace by 3x. We now can do that in EPIC, that will come online. We will co-innovate. I am very excited about this. We are the only company that has both advanced process, advanced metrology, and the ability to test it in labs. No one else out there can take those three things and put them together. I am very excited about it. And what you are seeing is the financial results from this.
We expect $3 billion in systems and service revenue in 2026 over that, and then very high growth going forward. So that is our three theses. Now let us talk a little bit about the uniqueness. Gary presented this slide, and what I really want to do after I just recap this slide is to go into actual examples that prove our points around this. So huge, expansive portfolio. Thousands of data points generated by our cutting edge electron metrology and inspection capabilities going into our analytical platforms. And the proof points you see over on the side. One is that we are due $2 billion alone in eBeam metrology. So the market is voting for this type of capability. In addition, we see the acceleration of both Semi Systems and AGS innovation.
And then, as I said again, finally, when we get to EPIC, I think it is all going to come together and we are going to be able to move very fast and innovate faster than any other company out there. Let us turn to some examples. Prabu, in his presentation, talked about how important it is to have high-performing transistors. Here is an example of how we enable high-performing transistors. Epi is key to the performance of the transistor, and when you do epi deposition, sometimes you get voiding. You saw it on Prabu's slide. You do not want voiding. How do you determine whether there is voiding there or not? What traditionally has been done is a TEM. They said, "Explain TEM."
"You are geeky, Keith, so you need to tell people what TEMs are." What a TEM is you go into a wafer, you scrap the wafer, you cut a very, very small slice out of the wafer down deep into the architecture, you pull that out, you put it into a transmission electron microscope, and you image. You hope you cut in the right place. You probably get five to eight transistors to look at. It does not give you much data. People love it because people love pictures, and they feel very good about the picture they see there, and they can see the void in that image, and they go, "Okay, I need to work on my epi deposition recipes." Very slow, very inefficient. Imagine you have an electron metrology tool that could go to thousands of points across the wafer and detect voids.
You do not have to guess where to cut. You can create a full wafer map, and that is what we are showing there, a heat map that shows you, look, there are voids in the red areas. There are not voids in the blue areas. What do we do? We take that information, and we start tuning our processes in order to eliminate the voiding. We do that much, much faster than relying on TEMs. This is what has been driving much of our growth in this area because people clearly see, they see. If you can see it, you can fix it. Not only is this used in R&D to accelerate R&D, it is also used after the fact in HVM to monitor the process.
It is not just a business about R&D, it is also a business about putting this in line and monitoring it, and then getting adoption with wafer starts. More good chips out. Here is another example that Prabu gave, and how do we help them? This is about wiring. A very typical thing in wiring is obviously via fill and polishing. This happens many, many times in any process. You saw those high stacks that Prabu was showing you in his presentation. What do you want to do? First of all, you want to deposit your metal, and you want that deposition to be uniform and non-pattern- dependent. How do you figure that out? Again, what we are able to do is after a PVD deposition, we are able to go in and see, are you overfilling? Are you underfilling? Or do you have pattern loading effects?
You can now, again, with a full wafer map, thousands of data points go in and accurately tune your PVD deposition better than you ever could in the past. No TEMs. The next thing you need to do once you get the PVD done correctly is you need to polish. So you go in with your CMP, and you polish it. The problem is you can over-polish or you can under-polish. So you can have protrusions or you can have dishing. You do not want either. You want to get the polish right. Again, the PROVision goes in there, takes thousands of data points across the wafer, and gives you feedback about how good your CMP process is. We put these together, we greatly accelerate our ability to deliver yield to the customer and ramp the process.
Once again, this is an HVM application that people use to monitor their processes. So that is how we help in transistors, that is how we help in wiring. How do we help in DRAM? DRAM, as Gary alluded to, is adopting CMOS. But they are adopting it on an older node, a FinFET type device in most cases, instead of a gate-all-around type device. When DRAM customers came to us and said, "How can you help us make sure that we are accelerating our logic and transistor learning?" We said, "Well, of course, we have done this in the past." This is an epi example, again, a slightly different epi structures. But what you are seeing here is you do not want those epi structures to merge. You want a deposit such that they are clearly separated so you get optimal transistor performance.
We said, "Well, several years ago, we put together the ability to image an open epi formation," which is what you want, or a closed epi formation, which is what you do not want in order to get a good transistor. We said, "We can deliver that to you in the matter of weeks. It is easy. We know how to do this." Both in our labs and at major customers, they now use this to help tune their processes and look at reducing variability across the wafer. We often talk about yield, a good die, a bad die. That is not exactly what yield is all about. Yield is also about minimizing variability. So if you have transistors, some part of the wafer that run slightly faster or slightly slower in another part of the wafer, that is bad. You do not want that.
You want all transistors to run the same. The way you do that is to do massive measurements in order to reduce variability across the wafer. Again, another big driver of our business. This is a new market. This is exciting. This is where I feel like I can geek out a little bit. Imagine when you saw Prabu's cross-section of the atomic- level gate- all- around, imagine if you can go in and measure that nondestructively on the device. That is what we created here. So we took our CFE technology, which is very, very high resolution, and we pointed it down at individual transistors, and that will generate X-rays. Now, if you put the right detectors around that, you collect the X-rays, and you can actually identify very, very sub-angstrom thin film thickness and also composition. You can do this on device and in line.
Not only is it something that we developed in the labs over two years with our IMS group in Prabu's area, but it's also something that we're now doing out in the customer. Why does the customer want to do this? Because traditionally, the only way you understood whether or not you're making the transistor correctly is to wait till electrical test, which is weeks later. You don't want to wait weeks. You want to make sure that transistor is performing correctly, the variability is low. So what we're able to do is to give the customer the ability to look at their transistor performance in line weeks before they actually have a functioning device. So we think that this new market, which we're very excited about, is worth several hundred million dollars, and it's not in our P&L today.
It's growing, and I'm very excited about this. Now, we all talked a little bit about advanced packaging in our presentations today. The thing about advanced packaging is it's all about yield. You're taking known good chips, things that yielded already, and you're going to put them into a very complex package. The last thing you want to do is to destroy that known good chip. So the intensity of metrology inspection has gone through the roof in this market because people realize the value of known good packages out. So a few years ago, our customers came to us and said, "As these are getting more and more complex, what can you do in the eBeam area? You've got eBeam products in the front-end line."
"Can you modify them and adapt them for the back-end line?" We did that, and we're seeing revenue from that already across multiple products. But the other thing they came to us and said is, "Can you get us a cost-effective optical inspection solution? Some of these optical solutions are tens of millions of dollars. We want an alternative. We want something that's far more cost-effective." So when we understood that, we started a completely new platform to address this market. This market went from a few hundred million a couple of years ago to now well over $1 billion, because customers want to inspect every die for small particles before they place it. Because a small particle in the wrong place on a via is going to destroy that known good die and destroy that package potentially.
So the value of optical inspection in advanced packaging has exploded. We're also not going to talk about it today, but we also have X-ray solutions in this area too, that allow us to see very subtle effects in the bonding in the advanced packaging. So finally, just to recap, 50% growth in our core businesses from 2025 to 2026 with extremely strong CAGR going forward. Okay? So very excited about that. Two, as I said, in new products, I came to Applied Materials. I worked at KLA for 27 years. I love metrology inspection. I overlapped there with Gary. Gary and I worked together there. We're very passionate about this. What we wanted to do was to build out a portfolio.
We want to have every product that can address the large markets in optical inspection, every product that addresses the large market in eBeam technology. Then we have some other things that we are pushing that I talked a little bit about today with advanced packaging, which we see extremely strong growth in, and then also the material metrologies and other X-ray applications. Very excited about what we can do there. Then finally, what we are also doing is helping our partners within Applied to innovate faster and to bring solutions faster and help with their growth. It is extremely synergistic, which I hope you saw from the examples today. Thank you very much for having me. Thank you. Now it is time for Tim to come on up.
All right. Good morning, everyone. Thanks for joining us this morning. It is a pleasure to be here. In Gary's presentation, he talked about AI computing leadership and how there are two paths to growth, the technology race, which Prabu and Keith just talked to you about, and all the innovations that Applied's bringing to the market. Then the capacity race, which I would like to talk to you about now, and how the services team, enabled by our industry-leading AIx c onnected platform, is helping customers optimize both yield and output with their existing installed base. This is the fastest way to profitability for our customers. Then how, as they bring in new capacity, we are able to ramp that capacity faster. So we are driving yield innovation, ramp innovation, and output innovation all within our AIx c onnected platform.
Before I go into the details, I want to spend a little time on the graph here that Gary introduced earlier in the presentation. Many of you are familiar with the S- curve for a factory. Yield and output on the Y-axis, time on the X-axis. This outlines essentially the life cycle of a product as it moves through a factory. There is the R&D phase, where we spend a lot of time with our customers optimizing their process as well as the hardware. There is the critical ramp phase, where our customers are trying to, as quickly as possible, optimize yield and output. Then there is the high- volume manufacturing phase, where we are trying to reduce variability in the factory so that the fab is operating at maximum output and yield.
Through our AIx platform, we have created capabilities that help our customers in all three phases of this lifetime. As EPIC comes online, you will see that we are actually able to advance that even faster. As fab utilization has improved this year, AIx adoption has increased this year, our revenue has grown more than 20% in calendar year 2026, and we have increased our future model to a mid-teens compound annual growth rate going forward. So EPIC is really going to change everything. It is not just about co-innovation of our new platforms with our customers in the collaboration areas of the facility. It is also about enhancing the co-innovation of our service products with our customers. How is this different?
Because we have customers co-innovating with us in this facility on dedicated systems, we are able to connect our AIx, AI-enabled servers to those platforms much earlier than we have been in the past. We can monitor the tools as they are developing with the customers' recipes to get a good baseline fingerprint of the tools. Our service engineers from AGS will be operating hand-in-hand with customers in that collaboration space, which will allow us to get a good baseline on how these tools operate in production. Then when the tools are transferred from our facility in EPIC to either the customer's R&D or HVM facilities, we will be able to ramp those processes faster, leveraging many of our capabilities, including CrossMatch. Let me talk to you a little bit about how service works in the AI-enabled era. As all things, service starts with the tools.
We have an Endura here. It has a lot of specialized sensors on the tools, and all of our tools generate tens of thousands of sensor parameters. We feed these into the AIx platform. What is that platform? It is a platform that focuses on actionable data. Tens of thousands of sensors means there is a lot of data. We do not need all that data to solve every problem, but we need to figure out which data streams are most critically important to solve the problem that we are working on. We run that through our insights engine, which is our analytical tools, our AI-enabled capabilities that are developed by our subject matter experts, and we build that on 59 years of equipment design technology, which is our domain knowledge, to create a suite of capabilities which we use with our customers in their facilities.
As Gary mentioned, we have 37,000 chambers connected today. About 80% of those are very securely, remotely connected capabilities in partnership with our customers. We have more than 18 quarters of data that shows consistently that we get 30% faster service resolutions and even less escalations when we compare the same tool set connected to our AIx servers versus a tool in the same fab that is not connected to AIx servers. What does this mean for customers? It means that as they look at all the variabilities that I mentioned earlier in the factory, whether they are tool matching variabilities, process recipe variabilities, the maintenance health of the tools, minor part variabilities that might change the output of the factory, when we run them through our AIx innovation engines, we can tighten the distribution of variability across the fab.
This drives more output from the facility as well as higher yield from the facility. I have highlighted a few of the capabilities that we have developed in the AIx portfolio today. This is not an exhaustive list. These are just some of the key ones that we are working with customers on today. Let me talk about one of those in a little bit more detail, and that is CrossMatch. CrossMatch is a critical capability, and it works like this. When a fab and Applied Materials work together to optimize an R&D process, we have done it visually here by moving that gold dot into the center of the target on the right-hand side. This is the best possible outcome that we can get on a given tool and process. We define that as a golden tool and a golden wafer.
As a customer ramps through that very steep ramp period in the life of a factory, there are billion dollars of opportunities for our customers if we can ramp that fab faster, particularly in the current environment. So we take the CrossMatch capability, and we move all the tools as we ramp them to overlap very nicely on top of the R&D developed process. That gives us one golden tool in R&D moving to multiple golden tools in high- volume manufacturing. We have been able to execute software with our partners in the business units in the product side, and we have been able to do this now 50% faster than we have been able to do in the past with this automation. This drives more good wafers out and more wafers out of the facility for our customers. So it is good for yield, it is good for output for our customers.
It is great for us because it makes us much more efficient than we have been in the past in ramping these facilities and allowing our customers to drive to a maximum output. Let me talk about a couple more examples that we have in the portfolio. Now, before you look deeply into this slide, I want to explain what this looked like before we had the AIx portfolio. So, this is an example where we have to replace an electrostatic chuck or an ESC over time in an etch process. For those of you that know this process, it is a very challenging environment in the chamber. There are challenging chemicals which will eventually start to attack the edge of the e-chuck, which is what holds the wafer down in the chamber. And you start to get a failure, maybe delamination at the edge of the electrostatic chuck.
Historically, we did not know when this was happening until well after Keith's tools would identify the problem through a review process, and then they would go back and stop the tool and evaluate whether we need to do a change. All that productivity that was lost and good wafer outs were lost through that cycle time waiting for the metrology to identify the issue. In our first generation of our AIx solution, which is in the left panel, we were able to create a health index by which whenever we saw that challenges at the edge of the electrostatic chuck, we could immediately stop the process, and we would not put that WIP at risk in the factory for our customers. But we knew that was not good enough. We wanted to create a second-generation solution, which we see in the middle panel.
We took our AI-guided models with our subject matter experts, and we created an algorithm by which we can clearly see how the life of the chuck is progressing in the chamber. The little triangle shows when the failure happens, and again, we can now use a time-based algorithm to understand when that will happen in the future. The right panel is a real-life example with a customer on how we executed this change to our AIx platform with this Gen 2 solution. So the triangles represent when the electrostatic chucks actually failed, and the horizontal blue bars show what our prediction model predicted they would fail. And you can see a very high correlation. In fact, we now have the ability to predict 30 days in advance when a chuck is going to fail with more than 90% accuracy. So why is this important?
For a customer, as they're looking at their WIP or their wafers in process and what material is coming to a tool, they can now take an unplanned event, which would be the failure in the past, and turn it into a planned event, and they can time that when they have the best lull in their incoming WIP, so it has the least impact on the factory. For Applied, it's great because we have a very complex assembly here that we can bring in from our logistics system, and we can have a trained engineer there, and we can do a controlled replacement of the chuck as opposed to an unplanned replacement of the chuck. It's good for the customer, it's good for Applied. Let me give you another example. Get it to advance here. This one is an ICAPS example. This is a high- density plasma, HDP-CVD.
We've had these chambers in the fields for decades. Whenever we do maintenance, there are a number of nozzles around the inside of the chamber that have to be replaced over time. The historical way we did this was we'd open up the chamber, our engineer would replace the nozzles, they would close the chamber, pump it down, run a wafer, send that off to metrology, get the results, and then we'd have the graphic that you see on the left. An experienced engineer would then open up that chamber, and based on that map, they would replace the nozzles in a different configuration to try to optimize the non-uniformity on the wafer. They would close the chamber, pump it down, send it to metrology. This would happen up to six times with an experienced engineer to optimize the non-uniformity on the wafer.
With AIx PRO, we're able to do that now in a single review of the metrology map. AIx tells us where we should position the nozzles. We go back and we verify that, and we take six iterations down to two iterations. It saves about 65% of the time for maintenance and drives more good wafers out for our customers. So it's a great outcome. Let me share a third and final example here, and this is yield innovation. Gary talked a lot about yield innovation and how important it is for our customers today. So in partnership with the equipment team, we've developed a unique sensor that sits on the front end of the etch system, in this particular case. That sensor is connected up through the customer's manufacturing execution system and also connected to our AIx servers.
The purpose of this sensor is to allow us to fine-tune the placement in each of the etch chambers. We connect it to the MES so the customer can periodically direct the tool to do this recentering again. Then, of course, it's connected to our AIx server so we can optimize that position with our algorithms. This is extremely important. You can see in the center panel that the etch effects that we see at the edge of a wafer really drive yield fallout. We get these tilted etches which don't land on their contacts. They result in open and lower yield. In most wafers today, 6%-10% of the die are on the outside edge of the wafer, and yield is lower there. So if we can move those etches to completely vertical, we're able to land more contacts, get better yield for the customer.
When we showed this data to the customer, they immediately fanned this out across their entire installed base of these tools, and we have a second-generation solution in process right now. I have talked to you a little bit about AIx this morning. I would like you to hear from one of our customers, and that is Manish Bhatia, who is the President and Chief Operating Officer of Micron Technology. Please run the video.
Micron is a leader in applying AI across semiconductor manufacturing, leveraging more than 1 billion monitoring points across our global fabs. Our partnership with Applied has shown that meaningful results come from combining the best capabilities across both organizations. Applied and AIx leverage unique analytics, service engineering expertise, and predictive capabilities that have solved problems that would have otherwise gone undetected. The collaboration has strengthened yield performance, improved productivity, and created a powerful model for data-driven manufacturing excellence. Micron's global adoption of AIx provides significant benefits for our technology development and manufacturing organizations and is a critical component of our valued partnership with Applied Materials.
Manish and Micron have been a great partner as we fanned AIx out into their factories, and I appreciate him contributing to the presentation today. I would like to wrap up with a single foil here, and this is a summary of the business overall for Applied Global Services. You can see we had a long period where there was no growth in the business, and as we shifted to outcome-based services in the mid-teens, we were able to drive a low double-digit growth compound annual growth rate. But as we have moved into the AIx area, we have actually increased the model, and we think long term, mid-teens is the plan going forward. You can also see that we have increased our subscription rates from the low 40% to nearly 70% in the plan going forward in 2030. The model is really quite straightforward.
As the installed base grows and we are able to put more tools into our service network with AIx enhanced services, we are able to drive more benefits for our customers. These benefits are in the form of our AIx services, as I communicated today, driving yield and output innovation. We have got 37,000 chambers connected today. We expect that to grow to over 90,000 chambers by calendar year 2030. As we drive incremental value for our customers, better cost of ownership, we are rewarded with long-term contracts. They are currently greater than two and a half years, and at a more than 90% renewal rate. In fact, our AIx services are statistically higher renewal rates than our service overall. This is going to allow us to continue to drive profitability and a 20% revenue per tool growth between 2025 and 2030. Thanks so much for your attention today.
I really appreciate it. Next up is Brice. Thank you.
Good morning. Nice to see everyone. Thanks for attending our breakfast, and thank you for your interest in Applied Materials. Today, we talked about how we're growing and enabling the most enabling portfolio in the industry. I'm going to put that in perspective from an R&D perspective, and then also talk about how we've delivered 10 years of excellent financial performance while executing that strategy. We'll talk about how AI is accelerating our outlook and growing demand across the industry, how we are investing to double our lab and manufacturing capacity for the company. We'll talk about our outlook, the targets we have for 2030, growing profitability and shareholder returns. We'll also talk about our capital allocation priorities and how we will invest going forward, continue to reinvest in the business, and continue to grow our shareholder returns.
On this chart on the right, we show how R&D grew over the 10 years from over $1 billion to over $4 billion. Some people ask me when they're asking about Applied Materials, "Oh, if I'm interested in the company, aren't I just buying the whole industry because you have a large portfolio?" I wanted to share, that is not how we think about adding to our portfolio, that we're adding scale or adding size. The way we think about it is what you heard today, being the most enabling company for our customers and for innovation. I'll just summarize a few of the examples here that we went through. A couple different color codes. On the blue side, Prabu and Gary both talked about how the company's strategy shifted early on in this time period.
On this slide, we note the PPACt strategy in 2017, shifting from, in the prior period, making the tools perform better, focusing on the operations of each tool, shifting to actual chip performance. So the PPACt strategy and platform, performance, power, area, cost of the chip, the actual device, not just an individual step that we were doing. Prabu talked about transistors. He talked about contact. He talked about wiring, all the wiring layers that are in the chips. As we work with customers to optimize those as bundles of solution from Applied Materials that can be reused by the customer, we're really able to help deliver a smaller form factor, lower power, higher performance, which is where you get excellent performance at the chip level from the customers. At the same time, we also hired and built expert integration teams that understand how the chips come together.
We built our integrated materials systems group, where we put multiple tools together in a cluster so that you can build the component under vacuum. Prabu talked about how as we're assembling those materials, they never touch air, and those produce some of the highest quality solutions for our customers. We also started the META Center, and the META Center is where we can do short loops or longer loops. If there's 22 steps in a process where you're building a part of a chip, we can do all 22, control that for the customer, and build the highest performing solution. That was really the first major change, thinking about the inflection from Moore's law, sort of the shrink environment, to no, you have to focus on materials, you have to focus on integration.
The second one we highlight on this slide in the yellow is the company also understood that the way to advance system performance, think about data center AI server systems, is you have to put a lot of chips on a platform, on a package, on a substrate. Think about GPUs, CPUs, accelerators, network stacks of HBM memory. All of these have to go on a package. We talked about the interconnect capabilities, we talked about panel processing. So the yellow investments that you see on this page, where we have a partnership with Besi on hybrid bonding, we recently made acquisitions that help us with X-ray technology and thin interconnects on the packaging, and we had our Tango acquisition, which helped us with our panel platform.
Continued to focus on what do we need to have in the portfolio to be the most enabling for our customers to solve that next generation of performance challenge. The last one we highlight here in gray is the AI investments that we made. The AIx platform is taking the massive amount of data from our tools and producing solutions for our customers that help them drive the tools to the highest yield and highest performance in their factories. We call that actionable insights, and we continue to add sensors and capabilities to our equipment that give that amount of data that we can use to drive performance for the customers.
Keith also talked about how we significantly increased the product roadmap in our metrology and inspection business, and that's so we can see the problems that need to be fixed in our lab, and we can also serve the customers with the equipment they need to see the same things in their HVM. Finally, some of you saw that our EPIC center that we just unveiled yesterday. EPIC is where we bring all of these solutions together under one roof to work with our customers on the long- lead challenges that the industry had, and hopefully you had a chance to see that. So with all of this R&D, we feel extremely well-positioned as we look forward to new technologies and process technology in enabling our customers. So 10 years of excellent financial performance.
The graph on the left, the bar graph shows the revenue growing over the 10-year period at a 12.2% revenue CAGR to $34.3 billion. Gross margin on the top line grew 680 basis points to 50% over the time period. That is non-GAAP gross margin. Non-GAAP operating margin up over 1,100 basis points over the same time period. Earnings per share CAGR 22%, nearly double the revenue CAGR over the time period, benefiting, of course, from buybacks, which we will cover later. 21% average free cash flow, so the business is a high-profit cash flow business. The last two points are really important, I think, for investors and investors that may not know the story as well as others. We can reinvest in this business.
We are reinvesting more than 50% of our cash generated back into the business, R&D, CapEx, working capital, small acquisitions, to grow our footprint, grow our solutions, grow our service capabilities, and continue growing the business. So greater than 50% reinvested, and there is a greater than 30% return on invested capital that we have averaged over these 10 years. We expect that actually to be increasing as we move forward while we continue to invest in the business. So executing the strategy of building the most enabling portfolio that we described over 10 years, delivering excellent financial results. I will zero in on gross margin. Of course, there is a lot of interest on the path of gross margin. It is indicative of the strength of your product line, which we say is becoming more and more enabling. So 680 basis points over the 10 years.
The drivers, if I break out the drivers for the change and increase in gross margin, the largest one, and what I want investors to think about most is the portfolio itself. More and more enabling. Every time we build a solution that is critical and helps the customer innovate, we spend a lot of effort on that, and it is providing value to the customer. If we do a good job on pricing, we have worked hard on our pricing process for the last four years. If we do a good job on pricing for the value that that tool is providing, then you see the value of the portfolio increasing, and that is the number one driver of the increase across this time period. Number two, our Semiconductor Systems business, that is our largest business. It is our reportable operating segment. We report our gross margins for that business.
It is over 55% in the recent quarter. As that business is growing faster, as the business has accelerated, that gives us an uplift from gross margin. Finally, we have operational efficiencies. We have diversified our manufacturing base. We have a large operation in Asia and Singapore. We have diversified our supply chain that helps us grow and scale our profitability, and that has helped from a gross margin perspective also. As we look forward and we get to the end of the presentation, we expect these same drivers to be in place. We expect fast growth in our Semi Systems segment. We expect to continue to innovate at the portfolio level and produce enabling solutions, and we expect to continue to expand our manufacturing operation going forward. So we think we are well-positioned to grow the value from a gross margin perspective.
Switching and thinking about the forecast for a second as we are talking about investing and spending and the financial parameters for the business. On the right side of the page is sort of a fun graph. More than a year ago, when we were having this conversation, we were talking about a $1 trillion semiconductor industry by 2030. Now you can see that the estimates are between $1.7 trillion and $3.2 trillion. Fair enough, some of this is pricing at the device level, and you do not need more wafer starts for pricing. But there is plenty of wafer starts required when you saw some of the system requirements at the package level that showed all those devices that have to go into AI systems. Fabs are being built at a faster and faster pace.
When we look on the left side of the page, it is not just the AI and the semiconductor devices. All of the arrows are indicators that we follow. All of the arrows are pointing in the same direction. Hyperscaler CapEx, over $1 trillion . Token consumption accelerating. The use of AI agents accelerating. The cost of those coming down. Package sizes, the number of transistors on a chip, the number of chips in a package accelerating and making that package business grow strongly. Fab utilization leading-edge logic, 100%. DRAM, 100%. NAND, almost 100%. ICAPS are our more mature process node customer processes. Healthy zone now, after a couple of years of digestion. It is a favorable environment for WFE to be sure. We talked about how leading-edge logic, DRAM, and advanced packaging will be the engines of the growth for the next few years.
We talked about our strong position in that those markets will be responsible for approximately 75% of the WFE growth looking forward in this forecast range. With our leadership, we expect to grow our market share more than 2 percentage points. Finally, Gary highlighted it will not probably be a smooth curve of growth. People are talking about and studying data center energy availability. We have said that clean room capacity will be a key determinant of how much equipment can be consumed in any particular quarter. Then supply chain, we have raised our forecast on our supply chain every single quarter this year. Everybody is racing to add output. Those things will determine how smooth the ride is as we move forward to serve this demand function. All right. Thinking about the global investments that we are making, the map gives you an indication.
First of all, EPIC was our largest investment. Some of you saw it yesterday. But we invest strongly in the United States, so the EPIC Center is a headline investment. We are also investing in Arizona, Massachusetts, and Texas. Texas, where our largest manufacturing site is. So manufacturing labs, research center, logistics centers, all of these, in the U.S. In Italy and Israel, new manufacturing capacity, new lab space, training center, new manufacturing capacity in R&D labs. In India, R&D offices, lab infrastructure, and supply chain investments. Singapore, we just celebrated the opening of our second manufacturing facility there and the expansion of our capabilities. That is helping us serve almost the entire Asia customer base from our Singapore operations. Then in South Korea and Taiwan, more customer-facing investments. So a significant amount of reinvestment in the business.
We're investing to grow our capacity from a manufacturing perspective and a lab perspective more than 2x across this horizon. EPIC is a good example of that on the lab side. Diversifying our supply chain globally over this time. CapEx, I don't have a specific target for CapEx, but CapEx was approximately 8% of revenue this year, and we say it will decline as a percentage of revenue as we move through the forecast horizon. Okay, AI. Fantastic results at Applied Materials. We put a few examples here to share with you. The first one in our hardware development, our actual product development, we've piloted the use of AI in terms of simulation and helping speed up the actual process and achieved a more than 4x on the pilots that we've run along these lines.
We're implementing that on 20 products now, and we'll expect AI and the types of models that help you do the hardware development to massively accelerate the pace of hardware development going forward. On the software side, software development, 100% of our software developers are using the AI method. Faster coding, testing, release cycles. This is amazing to get to 100%. We report the average productivity gain of 44%, but I'll tell you, some of the individual projects we see are 200%, 300%, 400% improvement. So 44% is across the entire company. Just amazing. From an adoption perspective, we have more than 80% of our employees using it every single week. Token consumption rising fairly dramatically, 45x in one year. We feel great. We think it's investable. We're not surprised the industry is investing. We're not surprised at the pace of AI data centers required.
We're not surprised at any of this based on our experience. Now I'd like to play a short video from Dr. Yu Cao, our Chief AI Officer at the company. Please cue the video.
I am Yu Cao, Chief AI Officer at Applied Materials. Applied created this role because AI isn't a side project for us. It's central to how we design products, run processes, and serve our customers. Applied sits on both sides of this market. We are a critical supplier to the AI build-out, and we are also a serious enterprise buyer and adopter of AI. Here's what we see inside Applied. Every software engineer now writes production code with AI with very substantial productivity gain. Across various organizations, engineers report multiple hours of time savings per week, and they are reinvesting that time into harder problems, not easier ones. Over 80% of our employees use AI tools every single week. We spend real money on this because the return is real. It's a P&L decision made by our management team and rejustified every quarter.
As models get cheaper and more efficient, our spending goes up, not down. A lower cost per token doesn't shrink the demand. It unlocks work that simply wasn't economic before. We see efficiency as an expansion mechanism, not a ceiling of spending. For Applied, the prize is acceleration. AI-enabled design is taking years out of our product development. We're also targeting multi-year compression of the materials discovery cycle. That is a value creation story first. Faster time to market, more share, and faster time to solution for our customers, with cost savings as a secondary benefit. We are early in the AI revolution. The opportunity ahead of us is larger than what's behind us, and every layer of it starts with materials engineering. Thank you.
Oops. Excellent. Thank you, Dr. Cao. Thinking about AI and operating leverage, I shared how we're using AI in some of our product development, software development, et cetera, and seeing fantastic opportunities. When we think about our operating spending for the company, first thing to share for the investors is our operating spending as a share of a percent of revenue has dropped from 22% at the beginning of the 10-year horizon to 17% today. You can see the R&D curve I mentioned before was growing to $4.2 billion, 72% of our spending. When we think about adding resources in the company, what sort of investments we're making, most of our additions are focused on R&D and the portfolio of spend becomes more and more tuned to R&D as we're going through.
In fact, you can see that SG&A, we bent the curve a little bit in the past couple of years. Revenue is growing faster than R&D, but we're continuing to invest. I gave you the focus, which is the most enabling portfolio. We expect that on SG&A, with the adoption of AI and the adoption of automation at a faster pace going forward, that we'll get significant efficiencies from our corporate functions and from SG&A in general, which will allow us to continue to grow profitability and operating leverage. Next, I'll cover our 2030 calendar year targets. The first one on the top left, we've talked about 2 percentage points of additional share. We're not giving a WFE forecast, and the reason is, of course, that's changing at a rapid rate.
What we are giving you is how we think about it internally and what our own framework is. We expect to outgrow WFE. Our target is to outgrow WFE. We think more than 2 percentage points of share we'll gain across this horizon. Again, you heard the reasons. Leading-edge foundry logic, DRAM, advanced packaging. We are gaining share today, and as those continue to evolve in technology, like to 4F², like to 3D DRAM, like to CFET, like to panel packaging, hybrid bonding, we will be gaining share with those transitions as the industry moves forward. It's not a WFE model, but you can model our equipment business based on growing faster than the industry. For the Applied Global Services business, Tim talked about a mid-teen CAGR growth rate, and we model that as greater than $12 billion by 2030 with that type of growth rate.
That business, Tim highlighted how it is an excellent source of recurring revenue for the company. Other revenue. In our other category, Gary headlined two businesses, our display business and the MAX OLED investment that we have that we are looking forward to significant adoption and growth. Then the SENZ waveguide photonics business that Gary talked about. We expect those businesses to be more than $2 billion by 2030. 54% non-GAAP gross margin is our target for 2030, and 40% non-GAAP operating margin representing expanding operating leverage beyond the margin improvement. The bottom left, you see our tax rate. We have a 15% estimated tax rate for 2030. Those should give you the elements of our own targets, how we are thinking about the company, and allow you to size the company as the market expectations continue to change for WFE.
From a capital allocation priority perspective, hopefully no surprises here. First, just reiterate the message. We are reinvesting more than 50% of our cash generated back into the business, and I gave you a good perspective on CapEx, R&D, et cetera. We will continue to maintain a strong and flexible investment-grade balance sheet. Then the bottom bullet, we are committed to 80%-100% return distributions of our free cash flow over time.
You may have questions about what will be happening with the dividend or what will be happening with buybacks. On the dividend, our board will make that decision next year per normal. Our history here is since 2005, when the dividend was initiated, it is a 14% CAGR. We doubled the dividend per share over the last four years, so significant focus there. Then from a buyback perspective, over the last 10 years, we decreased our shares outstanding by more than 50%. Again, committed to 80%-100% distribution of free cash flow going forward.
Just a summary of key messages. You heard about how we think about growing our R&D, how we focus on what we add to the portfolio. It is about being the most enabling partner for our customers. We delivered 10 years of excellent profitability executing this enabling model. AI demand is accelerating the whole outlook and certainly the outlook for our business. We are doubling. We are investing to double our lab capacity and double our manufacturing capacity from even today, so higher than the last time I said that. We are going to continue with our targets to grow our profitability, grow our shareholder returns, continue reinvesting in the business, and continue to focus on being the most enabling company.
Thank you for your attention. Appreciate everybody attending, and I will ask Mike Sullivan to come back up and take us to the next steps. Thank you.
All right. Well, thank you so much for hanging with us here. We are going to bring all of the speakers back out and do a Q&A session. We know you have a lot to do at SEMICON West, so we promise to have you out of here by 10:30. If you still have a question when we are done, we will ask the presenters to stay here and we can always help you then if you still have a few minutes extra. So we will bring out some chairs. We will bring out the group. Our thought here is we do have, of course, a webcast audience. What we would like to do is make sure that we have microphones available. Please don't start to ask a question until the mic's there, because our audience won't know what you asked, and we want them to hear it.
We have mic runners, [Cindy], I believe, on this side. We have Sonal on this side. Marty, my doppelganger, is in the middle aisle. If you have a question, go ahead and raise your hands and let Marty understand and the team understand that you have one, and he will do his best to come out. Please, everybody, come on out and join us.
A few hands.
Fantastic. All right, great. We have a question right here.
Great. Thank you. Vivek Arya from Bank of America Securities. Thanks for a very informative presentation. Gary, I was hoping to get your perspective on two near-term industry debates. One is this recent news about China perhaps getting to a 4F² memory. I was wondering what you have seen on the ground. What is your perspective? If they do get there, what does that mean for WFE share of wallet for the Western tool makers? The second one is this whole debate around memory de-specing, right? What does that do? How much of that is real? What does that do to the overall TAM of memory going forward, if there is indeed de-specing in some of the new AI? Just China and de-specing—
Sure.
—if you could address that.
Yeah. I think relative to compute memory in AI, and again, we had the EPIC events over the last couple of days, there is just so much innovation that is happening in compute memory. How you also connect it to logic, again, we were there with all of the leaders that were driving AI server architectures going forward. I just believe that that pace of innovation is very, very fast. I believe the three companies that are leading today will continue to lead into the future. Because, again, there is just so much co-optimization. Those leading companies that are designing those new architectures, what they said when we had that event yesterday morning, and all those people were there, is that they have already very deep partnerships for compute memory, for logic innovation, but they need to even go faster because those workloads are changing.
I have very high confidence there is going to be tremendous growth rates there still in compute memory DRAM, and there is going to be tremendous innovation at the component level, in the packaging level, and the system level. The de-specing, Brice can—
Yeah, we looked at de-specing, and our conclusion at this point is DRAM we expect to still be constrained. What we think the system architects are doing is they're determining that you need less DRAM for some of the different AI workloads. So training was very heavy, different amounts for inference, different amounts for agentic. We think what's happening is they're tuning those systems to maximize the amount of output that you can get from a compute perspective for those different workloads, optimizing the amount of memory that's used on each of those systems. So that's our perspective. We expect DRAM will remain constrained for a period of time.
Yeah, that's right. Having seen the analysis, the other thing to bear in mind is in the training workloads, they still want as tall of stacks as they can get their hands on. The new workloads that may not need as much as that because they can't drive utilization all the way up to the top of the HBM stack, those incremental workloads, they are new, and they're additive to the market. Everything's increasing. It's not a cannibalization. It's an increase in demand in an area where you may, instead of having your IO and your storage in the same space, put your storage elsewhere in the system. So it's just a repartitioning. All right. Marty? Yeah. Great.
Yeah, thanks. C.J. Muse with Cantor Fitzgerald. First question, Gary or Prabu, much of your discussion on the leading edge was focused on compute and DRAM. Curious if you could speak to how you're attacking optical networking from pluggables all the way to CPO, waveguide, hybrid bonding, new materials. Can you speak to that? Brice, on gross margins, only up 400 basis points in this four-year timeframe. I would think mix-wise, just from silicon, you're up 100 basis points-200 basis points. We'd love to hear what would drive the incremental and are you being conservative? Thanks so much.
I'll start, C.J. Relative to photonics, we talked about that being a very fast-growing business for us. Photonics and power, there's tremendous innovations that we're driving there. Hybrid bonding is a very important innovation. More and more vertical architectures, more bonding, better performance, better power, and better thermals. I think on some of these architectures, it's not just the better performance tokens per second per watt, but also yield. We have deep partnerships with all of these leading customers, and we're making tremendous progress on the yields. That really, C.J., is super important on when those inflections happen. The second part of the question was?
Yeah, then we had another question on gross margin.
Yeah.
For Brice.
Sure. So 54% is our target company gross margin. Of course, I'd remind investors we're over 55% on the equipment itself today. So 54%, approximately 100 basis points each year, although we're not calling it to be a smooth ride like we talked about. We do have to invest in our infrastructure. I talked about a new factory. I talked about new capabilities from a logistics perspective. There's headwinds to manage. We think that with fuel costs and the like, rare earths, and those sorts of things. So we feel that 54% is a good target. It will require us to be continuing to launch new equipment that's more enabling. We are raising pricing as part of the process, which I shared, to address some of the costs that we're seeing. C.J., we think that's a good target.
Great.
Hi, it's Tim Arcuri at UBS. I think this is all great, and I could see how a bear, though, would say they would look at the WFE share of gaining 200 basis points through 2030, and they would look at 2025, and you lost that much share in 2025, and your share in 2024 was down actually off of 2023. So the bear would say, "Well, you're only getting back to where you were in 2024 and 2025." So how would you address that?
Well, I'll start, and maybe somebody would add. Of course, in our math, we're still modeling growth in China and growth in restricted accounts in China. We can't serve leading edge, we can't serve DRAM, we can't serve NAND in China, but we're modeling growth there. So you're right. If we zeroed in on all the accounts that we can serve, we'll have a greater share gain than that. If you look at some of the device end markets, we expect a greater share gain. But if you account for the growth that we're expecting in the restricted markets in China, and again, we're assuming no change in the trade rules, then we think that's a good target for us.
Yeah. I think an interesting point is if you do the math on it, if you look at what happened to us from a trade restriction perspective in 2025, we had access in the early 2020s to 100% of China's WFE market, then the access dropped to 90%. In 2025, it went from 90% to closer to 70%. That was a big step down. There hasn't been a change in trade restrictions that allow us to go back up to where we were. So if you do the math on this, if you look at our position and you took that factor of trade restrictions out of the equation and then looked at our share, we're actually up, and we'll show that to you offline if you'd like to see it. So we're doing very well where we can compete.
Even in China, where we can compete at 28 nm, we're doing very well. What Prabu also showed you is he dissected the growth rates of some of the markets, and he showed you the growth rate of leading-edge foundry logic over a very long-term period and DRAM over a long-term period, and showed how we're outgrowing in those periods. So where we can compete, we're doing very well, and we expect to continue to.
Thank you for doing this. Atif Malik from Citigroup. I have a question for Keith. Keith, you talked about launching new optical products in the first half of 2027. I was wondering if you can pull the curtain a little bit and tell us more about HBM or CoWoS. The market itself is very competitive with Nova and Onto and KLA, so what will be the differentiation that Applied will be bringing in this advanced packaging optical market?
Right. I think it's a very important point that, especially in advanced packaging, the optical inspection market is already crowded. We would not enter a market unless we understood architecturally how we can differentiate. I can't really go into the details, but rest assured, we spent approximately a year and a half examining what is serving that market today, what the technologies are in play there, and we feel that we're going to bring something to market that is clearly differentiated, clearly sustainable in its overall performance. We are trying to position the product to have the highest sensitivity at the highest throughput possible using cutting-edge technology. Just one other comment there. I think many of those products had been very much restricted in the amount of cost people were willing to put into them because historically, that market had been very cost sensitive.
We don't see it as cost sensitive any longer, just as I talked about today. There's so much money to be made in advanced packaging. The yields are so important that now we're starting to see an inflection where our customers are willing to accept higher ASPs in order to meet the yield demands.
I guess I'm up. Thanks. It's Stacy Rasgon at Bernstein. I actually have a question for Tim. Tim, you said you're targeting mid-teen services growth over the next five years. I'm a little confused there. You said you thought your installed base would go from 37,000 tools today to 90,000, which is almost a 20% CAGR just on the tool growth, and then you layer on, I guess you say you're looking for 20% overall increase in revenue per tool on top of that. How do you only grow at mid-teens for the services? Shouldn't it be growing a lot more than that if you hit those goals?
Yeah. The model is, as we mentioned, going from low double-digit growth to this mid-teens on a go-forward basis. I think it's important to understand when you think about connected, we were talking about connected chambers, Stacy, not connected tools, so 37,000 today to 90,000 in the future. As tools go out into the market, they first go into an installation and warranty period, and then after a year, 18 months, whatever it is, on a customer-specific case, we move some of those tools into service, depending on what help the customers need and what sort of ROI we're able to generate from our AIx-based services. So we're pretty confident in the growth rates that we have. The 20% that we see growing in the revenue per tool is really driven by these capabilities that we're introducing that are these AIx-related examples that I gave you.
But when you look at the growth in the overall market, it is really dependent upon how much of it goes to various levels of our service portfolio. We have on-demand customers who buy spares from us. We have customers who do forecast parts management. I did not go into all the details today. Total kit management, and then we move into the service portfolio where we add these AIx capabilities. So it is not a one for one as we do the transfer, but again, we see the market growing, and we see our CAGR increasing over time. As Brice mentioned in the last financial release, we are going to grow 20% this year based on the utilization recovery as well as the adoption of the AIx capabilities.
Yeah, and if I could add a point there, I think we have disclosed at various points our installed base, which is somewhere in the high 50,000s. That is tools. And so, Stacy, the way to think about the growth when we talk about mid-teens is a 5%-10% growth per year in the installed base, and the balance of growth would be on new products that Tim's team delivers.
Yeah. That is great. We will hear the next question.
Hi. Mark Lipacis, Evercore ISI. Thank you very much for the great presentations, really informative. I think yesterday one of the presenters made the case that with agentic AI, you could have unlimited demand for compute, and you have the charts going exponential on industry revenues. And I completely appreciate you do not want to put a WFE number out there. I think it is a moving target. What limits the demand for your products? Is it fab capacity for your customers? Is it your customers to build data centers? Is it the power grid? What is limiting demand right now?
I think the primary constraint, Mark, that we called out is clean room. The first thing that we look at when we're forecasting medium term, next couple years, we talk about an eight-quarter forecast that we get from our largest customers. That eight-quarter forecast is which facility, how many wafer starts a month capacity, what node, specifically what tools. We have that sort of information from our customers. As they've worked to increase the amount of clean room that's available, even in the shortest term, I think that's the major, we talked about how that will meter the growth rate. That is the primary variable that we see.
One thing, maybe I highlighted, maybe I didn't, over the last two quarters, we track over 100 fab projects globally, and over the last two quarters, we've seen more than 10 new projects added just in each of those two quarters. The envelope of construction and the envelope of factory space and clean room becoming available over the horizon is growing.
Great. We have the next question is at the back of the room.
Yeah, hi. Thanks for taking my question. It's Krish Sankar from TD Cowen. Brice, just to follow up on that earlier question. You spoke about more than doubling your manufacturing capacity. Is that something you see across the ecosystem? In other words, your peers are doing the same, your suppliers, their suppliers are doing the same, or do you think that ends up becoming a bottleneck for this really impressive demand scenario you outlaid?
It's a good question, and I haven't tracked the exact comments from our peers, but I can tell you from a supply chain perspective, we have 2,000+ suppliers. We are sharing our forecast and the estimated requirements and aggregating those component requirements with all of our suppliers. It's a good thing to think about is, yeah, it's a lift across the entire supply chain at approximately that level for all of the components you need in a factory. By the way, that's happening too for the data centers. In fact, you see in our market how some of the end markets are competing with data center. You can't make enough smartphones today. You can't make enough PCs. There's not enough memory to go around. So there is a competition for resources. So there are some limits as we move forward. Our perspective is there are no roadblocks.
I don't think we've determined any roadblocks. There are going to be pinch points that have to be managed, and I do expect that the peers will be making similar investments.
Great. We have the next question here.
Thanks. Excuse me. It's Chris Caso from Wolfe Research. Brice, a question for you on the margins again, and if you could address the path to the 40% operating margin. It seems that the majority of that is coming from the increase in gross margin. So what does that imply with regard to OpEx leverage? If you could also follow with what you expect from cash flow for the business to do as you approach those 2030 targets.
Yeah. I think those are the two components of reaching a 40% operating leverage. We will expect to get 4 additional points on the gross margin, and we will expect to achieve 200 basis points-300 basis points in operating leverage. I will point back to AI automation across the company will allow us to scale the corporate functions at an extremely high productivity rate as we continue to grow. You can picture you are selling more tools to the same customer base. A lot of our functional activities will not need to expand as rapidly as revenue or the business. From a cash flow perspective, we have averaged more than 21% free cash flow for the business. We do not have a target to share for that, but that has been a long-term average. We are having to invest in the business.
I think looking at that as an indicator of where we would be, I sort of expect it to be a little bit higher, but we do not have a target to share today.
All right. Great. We may have a —okay, there we go.
Hi. Charles Shi from Needham. Maybe a high-level question. We have been hearing Applied solves most critical problems for customers, but we also hear that customers from time to time shift at the semi-critical, non-critical applications to competitors for reasons we do not fully understand. Maybe three questions related to this topic. Number one, is this in Applied's understanding this is happening? Two, if yes, what do you think the reason is for that to happen? Number three, over the next three years, how does the team plan to address this? To me, it is probably like a low-hanging fruit for further share gains. Thanks.
Yeah, I can take that, Charles. As I mentioned earlier, for our customers, 80% of the incremental WFE growth is in those three areas, leading-edge foundry logic, DRAM, and advanced packaging. Again, I am meeting all these CEOs, R&D leaders on a continuous basis. Their focus, what is consuming them is the race for design wins with the best performance. With chip innovation and packaging innovation, it is incredibly complicated integrating across those flows. New transistors, new wiring, new packaging architectures. Everybody wants multi-chip connectivity with much bigger body sizes, more reticle fields connecting together at higher performance, higher power, better thermals. Again, Applied, as we mentioned earlier, we have the leadership in creating the materials. We have the leadership in materials modification, the highest resolution materials analysis. We are in these deep relationships, co-creating architectures with all of those leading companies.
The other thing is, as I said, more so than any point in my career, they are incredibly focused on more chips out, more good chips per wafer, more wafers out, and that is the yield innovation strategy that we have been driving. For me, when I am meeting those customers, we do not have a lot of conversations, honestly, on cost right now. It is really that race for better performance and higher yields, and we are in deep strategic relationships where we are co-innovating across all of those flows for the transistor and the wiring and the high-speed memory with CMOS and logic coming to have the data going on and off the chip faster or advanced packaging. For them, the gains with what you had referred to on non-critical is honestly insignificant in comparison to design wins and the engagements that we have with them.
Great.
Now, we are innovating across our whole portfolio. We are always innovating on every piece of equipment. We have got some dynamite innovations that we are bringing to market, but again, that is not the primary focus for our customers today.
Great, then I think we have the next question here.
Hi there. Brian Chin from Stifel. I appreciate the presentation this morning. One of the things that was outlined in the slides was, or one of the factors that could be caused non-linearity or non-smoothing in terms of growth was supply chain. You've obviously asked suppliers to increase double digits sequentially, then double digits sequentially again, then again. When you think about that as sort of a short-term factor, an inhibitor to kind of the ultimate growth trajectory, is that something that maybe we would resolve in the earlier timeframe of sort of the four- or five-year horizon? There's obviously a lot of muscle memory in terms of suppliers knowing that there has been volatility over the history of the industry.
Can you inject them with money, with cash, in terms of helping them along that process of scaling out capacity at levels that they probably weren't prepared to do in the past?
Yeah. Thanks for the question. I think the good news here is we haven't got any responses from suppliers that say they don't believe us. Everybody's seeing AI, they're seeing the use. I showed all the arrows pointing in the same direction. They see the strong demand signal. They know they have to make investments. They know they have to hire people. They know they have to expand. There's no conversations about send me five more forecasts and convince me this is happening. So that's a good thing. To your point, I think we have studied the entire supply chain. We don't think there's roadblocks, meaning that we can't get to the higher levels of output.
There are pinch points that have to be managed, and there's plenty of suppliers that it takes lead time to hire people, or it takes lead time to add fixtures or manufacturing capabilities. Test capabilities a lot of times come up. We did raise expectations on supply chain every quarter. We're asking them to go as fast as they can, and that's what's happening. Again, I think not a smooth ride is probably a good expectation, but we don't see any roadblocks over the medium term, as you called it.
Great. Question. Okay. Right here.
Hi there. Sorry, I missed part of the conversation, but I wanted to double-click more on the pricing side of things. You guys have always talked about a value-based pricing model, and that's been something you've been working on. Can you talk about in this environment, has any aspect of your approach to pricing changed, any acceleration or just any more color on how you guys are going into those conversations?
Yeah, thanks for the question. I don't know if anything really has changed other than some of the solutions have become a lot more valuable, and you can see that in the value that our customers are getting from their products. As we study the value of our solutions, let's say it's a higher- yield solution or a higher- output solution that our customers will get, we can recognize the value that that might bring to a customer, and that's a factor in the pricing. Otherwise, I would say the mechanism itself and the discipline we're putting around, if we're introducing a more enabling solution, we know what it does for the process, for the customer, and what its value proposition is. We put an appropriate price on that. I don't think that process is changing.
We're just strengthening it and continuing to work on making sure we get the right price on each solution. But probably the recognition that the whole value in the market is rising, that's a factor in how we price the tools.
Okay. We have a question here.
Thanks for the follow-up. Last year, the semi industry was about $1 trillion. I think you had it in one of your charts, Brice, and WFE was, I think, about $115 billion-$120 billion. So intensity, round numbers, about 12%. In what scenario does this intensity be higher or lower than this number we had last year as we go out in time? Let's assume that it grows at this pace, then between the different food groups, whether it's litho or etch or dep or other parts, which grow faster than the others? I'm not asking for a WFE number, I'm just saying in what scenario does intensity become lower than what it is? Then if it grows at this pace, what are the different components? How fast do they grow relatively? Thanks.
Well, I'll make a brief comment and maybe, probably with Gary, you guys can talk about what grows faster from a process perspective. I think, Vivek, the price of the end device has been what's moved that equation the most. I think if you said, "Well, what can make intensity go a lot higher in the short term, or what can make it go even further down?" I think it will be the price of the memory or the price of the GPUs that would change that equation radically. Underneath, I think we shared how the process technologies, of course, are adding more steps. The packaging is adding more steps, so it's becoming more intense. Our business is growing. We don't use intensity as a factor when we're forecasting our own growth.
We're back to what are the factories, what are the end markets, how fast are they growing? That's what we look at.
I think we showed earlier those charts on the node-over-node changes. For leading-edge foundry logic, DRAM. Again, what you see there is WFE dollars per wafer start going up significantly, our served market going up, and our share of served market going up. Those architectures are more 3D architectures, 6F² with CMOS Bonded to Array, 4F², 3D DRAM. They're more material innovation enabled. Same thing in foundry logic as you go to those subsequent architectures. Then, one of the biggest innovations in the industry is multi-chip connectivity, where you're connecting computing components together with new architectures. That's very much enabled by materials innovation. From Applied's perspective, as we see those roadmaps going forward, again, we're engaged with all of these leaders 10 years out in the future, four technology nodes out in the future.
We have very high clarity on what those architectures look like, and they are more materials enabled, which is a great tailwind for Applied Materials.
Yeah. Maybe I can add one thing there. If you really look at those, we changed our numbers in few of them, if you look at today. We increased the SAM number in certain areas. As the technology getting more and more complex, a lot more steps are ordered. You do not even see it. Some of the steps come and go. The customer keep it as an IP. A lot of steps in treatments, a lot of steps in anneal. A lot of steps are being ordered. That is the reason we increased our number today in some of the SAM numbers. Every time I see it, I think I am wrong because my SAM number is going where more steps are ordered. Also in packaging, if you really look at all about thermals, the thermal interface material, how do you suck out all the heat?
A lot of new materials are coming in. We are always surprised with how many more new steps are ordered these days. The complexity increases.
Great. All right, well, thank you. To the audience, I just wanted to let you know that I hope you do not mind that we did things a little differently this year. A lot more speakers, a lot more content, but we thought it was a good time to do that. We have been very excited to have the opportunity to present to you today. I would like to thank all of our colleagues and their teams for the work that they put into this. Most of all, we would like to thank you for coming and spending time with us and for your continued interest in Applied Materials.