International Business Machines Corporation ($IBM)

[indiscernible] Bank of America Global Tech Conference. Delighted you could all make it. See a lot of familiar faces. Thank you all for joining us again. I'm Wamsi Mohan. I cover IT hardware and supply chain for Bank of America. Delighted to welcome IBM here today. Representing IBM, we have Ric Lewis, who is Senior Vice President of the Infrastructure Group.

So Ric, welcome. Thank you for doing this with us. Very exciting time to be in infrastructure. It's the place to be seems like when every day you hear more and more CapEx dollars are being spent on infrastructure. So I would love to get your thoughts on what you see how IBM's position is in infrastructure to kick it off?

Yes, sure. So I've spent the last 37 years in infrastructure. It's never been more fun or more exciting. There's no doubt about it. And I think the strategic nature of it and how important it is to every boardroom and where the future is going and how it's changing every business, not just IT businesses, et cetera, make it pretty exciting. I think interesting thing is over time -- there was a time when IBM was thought of as an infrastructure -- boxes kind of a company. And IBM has grown to be so much more, consulting and software and lots of organic things going on and lots of acquisitions, et cetera. But at its heart, we still do a lot of infrastructure and our Z, Power and Storage. Now you're hearing about quantum and all the things that go with that or IBM Cloud as well. So we're seeing similar momentum that you're seeing in some of the infrastructure companies that are all over the airwaves here in the latest few weeks, especially. AI Lift is a real phenomenon going on in the industry. Even if you say, well, it's all about GPUs, it's not all about GPUs. I would argue it's all about data. And that data needs moved. It needs stored, it needs fed, it needs processed. It's also about agents, and those agents need coordinated. They need run, and they're not all on GPUs. So there's just a lot of AI Lift is what I would call it in the industry, which makes it really fun to be in infrastructure and IBM is a big part of that.

Yes. No, that's a great point. So maybe on the AI uplift, right, as you think about some of the places where you're observing that in terms of -- historically, you've seen a lot -- let's start with Z, right? So Z, you've seen many cycles in the past. I know you alluded to at your Investor Day as an example, like different types of MIPS have different value. And AI MIPS is something that you saw coming. Can you give us some sense of like how that's being monetized?

Sure. So first, when we transact the mainframe, the Z business, we sell MIPS. We don't actually just say, here's a box. We're going to charge you X for a box. We sell it by the MIPS. So throughput is what matters. And in the last several generations, 3 plus, we've been building momentum on that. And I would say 3 generations ago, it was more about more capacity needed or technology refresh is what drove a given cycle. And even in the last decade, that first wave, we were growing kind of 110% program to program. Then in the last one we put AI, the initial AI, we had AI and Z before there was a ChatGPT or any of that. Clients were using it for more machine learning type fraud detection, et cetera. We saw Z's growth rate jump to 120% to 125% program to program on a given program. And now with this latest generation where we have Spyre and all the AI capabilities that we've built in from scratch and workloads are moving beyond kind of fraud detection to more multidimensional things from code development to being able to do inferencing on things like insurance predictions and actuary tables, all that kind of stuff, Monte Carlo analysis, whatever, all of those things inside of Z have now accelerated that growth program to program. We're seeing in the latest in z17 at 135% program to program. So not only has the Z mainframe franchise been growing, its growth is accelerating, not decelerating. And so that's just Z that we're seeing tremendous AI uplift. And I think Part of that is the industry. But quite frankly, I'd like to selfishly say part of that is us. We invested early and often in building those technologies that were really suited well for the AI wave that has now come. And one thing I want to say there is the cool thing about Z is our customers, our clients help codesign it. They tell us what they need. And by telling us they needed to address the $1 billion fraud industry and by telling us they needed to be able to do real-time processing, Swiss Mobiliar, for example, up their throughput of insurance claim approval kind of application things by about 7% to 10% by using the built-in inferencing going on. So by telling us what they needed to do, it's forced us to kind of develop new technologies like AI and Z and provide a tremendous lift. So we're really excited about Z. It's the biggest part of my portfolio. It's not the only part. There are other significant parts, but that biggest part is just exceeding expectations left and right, including in Q1, we had our biggest Q1 ever of Z at this phase kind of as the last quarter of a given introduction year. So really great momentum.

Yes. So maybe just to touch on this a little bit more, right? So as you think about the growth in infrastructure, it used to be that we used to talk about infrastructure kind of being flattish through cycles. That seems to have changed.

It has definitely changed. Yes. And it's something we're super proud about and excited about. I came into the group 5 years ago, and we had one very simple big hairy audacious goal, and that was, 'let's have this thing grow and let's have it grow across all dimensions,' across Z, Power, Storage, across our cloud and across our support business, which is associated with all that. And we're doing that now. We're low single digits. We have aspirations to continue to accelerate that. I think some of the things we're seeing with the AI Lift that I talked about before, make us feel like I think we can accelerate that. But it's taken making sure that all of those pieces are growing and carrying their weight in the overall portfolio.

I think a lot of people look at IBM and they don't realize the depth of technology stack that exists on something like Z, on something like Power where it goes -- it's pretty vertically integrated. Maybe if you want to spend 2 minutes on that just because I feel like a lot of people don't necessarily put all of those things together as owning those pieces of the stack that are so valuable.

It is a big part of -- the last question was about monetization. That's a little bit of how we monetize. We don't have intermediate pieces of the stack that can say, well, we want to take all the value out of that. It's our stack, it's our chips, it's our silicon, it's our boards, it's our firmware, our operating system on top of that, and it's our application software, whether it be database kind of capabilities that we have on Z or things that we load on our other platforms. And Z is the obvious case. You'd say, well, that's kind of a closed ecosystem and is self-contained. But even with Power, we have MMA, matrix math acceleration, going on inside of our power processor. We put Spyre cards inside of our power machines. So again, a full stack kind of delivery thing. Now up at the top level, we support multiple OSs. So we don't close that whole ecosystem. We run UNIX capability with our AIX and obviously, SAP. But we also run databases natively on that. And we also integrate our container platforms into that. Yet another area that's really growing well in the AI area is people are doing new applications. They don't want to do them in the old virtual machines. They want to do them on containers. So we have a ready built full stack power system that has containers built in. Similarly, we have storage, AI in a box that has containers built into it. So we really try to provide that differentiation at the full stack and make sure that we can provide a differentiated experience that helps with clients. So it's something we're really good at. It's fun for me because I look and I go, 'Oh, chips are hot right now.' We do chips. 'Oh, boxes are hot right now.' We do boxes. 'Oh, operating system work and containers are hot right now.' We do that. So it's really a good thing for IBM.

Maybe just to think a little bit about AI and the impact that it's having on the business and maybe on this cycle. As you think about monetization, right, it looks like there's a lot of pricing that is driving the results of a lot of these peer companies in infrastructure because of shortages, because of various reasons. How are you thinking about pricing from an IBM context, from an infrastructure context? I know that some of the commodity pricing is obviously being reflected in a lot of the revenues that other infrastructure players are reporting. But how do you think about where commodity pricing is and where your pricing is and maybe there is a disconnect between the 2 also.

Sure. So a few thoughts on that. So first, let's maybe just try -- let's start with supply and then let's work to kind of demand and pricing. So supply-wise, there have definitely been some shocks in the ecosystem, just dramatic demand increase for memory, dramatic increase for disks and things like that. For us, one, we're really good at supply chain management. We've been doing it forever, over 100 years. We even use our own AI technology in our supply chain management. So we're great at it. Second thing is when you're selling systems that are not, I'll just say, commodity, I mean, we're doing a full stack, we're doing differentiation, et cetera; that means we have more margin in those systems. That means we have more margin to move when we need to apply it to getting supply for those kind of things. So that's really a powerful dynamic for us. And we use that when we need to. But what's interesting and that I love about this whole situation is it has actually changed demand as well. And what I mean by that is when memory costs have gone up, when CPU costs have gone up on the rest of the market, that means people want to be a lot more efficient, even hard drives, when hard drives go up, my tape business is now growing double digit pretty reliably because people need a place to put bits and disks have gone through the roof and tape looks pretty economical and affordable. So all of this cost and supply chain shock has actually resulted in demand for my power servers because we make better use, frankly, of memory that you put in a box. We're more efficient with how we utilize that. Increased demand for storage, it's increased demand for tape, it's increased demand for the software, the integrated software that is put. So all of that generally has been a good thing for us. Then you add on to the fact of, okay, you're a value supplier, so you can price appropriately. And when the commodity prices for memory and things increase, then we adjust our price appropriately. We make sure that the clients understand we're pricing for our value and here's the part that is the component increase cost, and they're happy to get our systems that make better use of those expensive commodities. So we end up in a win-win. So it actually doesn't hurt us at all. It actually helps us a little bit.

Have you seen enterprises -- I mean, from what you're saying, it seems like enterprises are changing their buying decisions. But are you seeing any shift in demand acceleration because people are worried about not being able to get access to the compute power or the storage or anything else that they need?

I think it is motivating -- it's interesting. There's 2 parts of that. Is it pull forward? I don't know. I think there's a big enough wave here that we and the other infrastructure vendors aren't thinking this is pull forward. This isn't -- well, I'm not going to say I'm buying everything I need for the year right now. We think it's actually true increased demand. And that increased demand in the long term results in what kind of looks like a pull forward, which is really, I better get some now because I'm going to need more rather than I better get some now because I won't be able to get it. And that's a really important distinction. It's more of the former. I better get some now because I think I'm going to need more, and that's what we're seeing as a behavior from clients.

Yes. And it seems very consistent across the board, like I think everyone seems to think that there is just a very strong demand environment because there are use cases to deploy on this infrastructure that if you don't, you get sort of left behind and there's a sense of urgency to go ahead and deploy this.

Absolutely. I mean businesses are being disrupted daily now. AI has moved from experimentation to production. And not in wholesale, we're still early innings. But it is definitely in production now in a lot of companies, and those companies are disrupting other companies. And so it's an imperative to make sure that you're on the curve.

So maybe talking about disruption, I think there were some worries, maybe transitory, but just on the fact that AI potentially can help refactor some of the code base on the mainframe and what does that eventually do to customer stickiness or usage of the mainframe? How do you think investors should think about that?

This is one of the most fascinating topics. What -- I think at times, people are tempted to say, 'Oh, the reason people are on a mainframe is because you can't translate all that COBOL code.' We've been translating COBOL code now for 3 years. I'll give you an interesting factoid, but people who are doing Watson Code Assistant for Z, which will help you comment and transact -- and translate COBOL code are actually growing at faster MIPS utilization than any of the other customer database, kind of like 2 to 3x faster. What we're finding is actually 2 things. One, fit for purpose is what rules kind of the space, just like you want to do AI transactions in the GPU because matrix math is key to AI inferencing and training and all those kind of things. If you want to do high throughput transaction processing at a global level for the most fastest, most secure, most resilient platform, it's a mainframe. So that's what you use it for. It's not about, 'Oh, COBOL keeps it so I can't move or whatever.' We have clients translating COBOL to Java and other things every single day. It's about I can do a lot more transactions. They are a lot more secure, and it would cost me a ton of money to try to do all this in a cloud environment. So we don't see that. What we actually see is what might have been perceived as a barrier to exit might have been a barrier to entry. And what I mean by that is I'm worried about skills. What if I end up some of these code -- now I'm not saying people are bringing new COBOL a bunch of that stuff. But what they're saying is if this is the world's fastest transaction and most secure and most resilient, stays up all the time platform, my only worry is, 'Well, I don't want to write COBOL.' Well, you don't need to. You can write whatever you want. Our Linux system or what we call a specialty MIPS, the noncore old-school database MIPS has been growing 3 to 4x faster than the core MIPS for a long time, and that's because clients put other workloads on that. And as the cost of Linux-based machines, AKA x86 boxes running Linux has gone through the roof, Cost of Z hasn't gone through the roof. It's similar to what it was. So that Linux value proposition on our Z looks even better than ever, and it's still the fastest transaction processor and secure environment never goes down. Don't have constant patching to try to deal with all that to make sure that you're up on the latest security. So that's what I mean by this barrier to exit or whatever turned out to be -- another example, our IBM i, we're seeing a massive resurgence. This is the old AS/400 running on our power systems, massive resurgence in new workloads landing on IBM i because people were worried about 'Well, I don't have RPG code expertise.' You don't need RPG code expertise. We now have software tools that can write whatever language it is you want. You just say what application you want on an IBM i box running on Power. And you don't have to worry about the ransomware attacks that you get on x86, you don't have to worry about the machine going down. You don't have to do all that. So we're seeing a significant growth, not just double digit, but higher double digits in IBM i AS/400 business right now because of this barrier to entry being dropped by. Now we have programs, including IBM Bob that do this really, really well and allow people to put new workloads and new applications on top of that infrastructure that's so reliable and secure. So it's actually working out well for us. We're happy about it.

So on that point of like where you -- I think that's super interesting that the people who have run Watson Code Assistant for Z are consuming like MIPS at a higher rate. What applications are they now running that they weren't running before?

It's a variety of things. A lot of container kind of loaded applications, a lot of Java. It turns out that a world-class transaction processor runs Java extremely well, and it runs a gamut. Usually stuff that -- remember, you kind of have this fit-for-purpose ecosystem depends on what your core thing is. Are you processing insurance claims? Are you processing bank transactions, credit card transactions, et cetera. It will be the surrounding stuff that latency gets a good benefit of being co-located to that is typically it. But we have other people -- we have clients. We've referenced publicly some big banks that say, 'Hey, I have a mainframe estate. I'm just going to do server consolidation of generic non-mainframe-related workloads on Z Linux systems because I don't have to manage data centers full of racks of stuff that need patched and updated, et cetera. I get 2 mainframes and I can run all those workloads and I'm home free. And it fits the same profile I have for all the transaction processing that I have going on in the organization.' So it's a little bit of everything surprisingly.

Yes. Yes, that's really impressive. Maybe just to talk about sort of the broader portfolio, right? So when you think about -- you mentioned the strength across Power. You mentioned the strength across Z. How are you seeing this Z cycle maybe different from prior Z cycles, if there's any compare contrast on either length of cycle or on magnitude in terms of from where we are today -- you already had like a year of very strong Z performance from where we are today. And then maybe just touch on storage as well because -- and maybe infrastructure support, just to make sure that...

Sure. Yes. Excellent. So let's start with Z. Momentum has been accelerating, meaning we've had good acceleration each year. It's compounding now, and so extremely strong. Why do I think that is? I think -- we had talked about the core MIPS, the database MIPS that we sell and that specialty MIPS were growing at 3 to 4x. Wamsi, I've talked to you before and other analysts about this new emerging category of AI MIPS, which basically has to do with clients that are actually adding new workloads like a bunch of inferencing on their insurance processing that I talked about before or a bunch of inferencing on bank transactions or actual customer transactions that are going on in the systems. They can do it at near real time. With Spyre, they can do multimodal AI, so not just kind of transaction focused, but let's say, you're trying to figure out if something is fraud and you can use -- the typical pattern is, okay, 2 deposits of something small, 2 withdrawals of something small, then 1 withdrawal of something really big. Well, now you can mix that with multimodal with Spyre cards, et cetera, where you can say, 'Okay, I see this transaction pattern. Does the entity that's running those transactions have a web page. Are they a physical entity? Do they have a real address? Or is it a PO box? Or is it a website in the middle' -- so things that you wouldn't generally -- it's more contextual, I guess, about what's the company that's trying to do these transactions. You can do that. So all of those means more workload. That means we're selling watsonx. That means we're selling Spyre cards. That means -- and those Spyre cards have subscriptions, et cetera. In fact, one really cool thing is for those specialty MIPS, the Linux workloads that is containers and that kind of thing, we see 3 to 4x multiplier of Z stack revenue. For these AI MIPS, we're seeing greater than the 3 to 4x, higher 5, 6, 7, 8 kind of multipliers on the MIPS that we're selling for AI. So that's just more in the ecosystem, more software sold, more cards sold, more subscription, more services, et cetera. So that kind of tells you the Z story. On storage, I think that you've seen the industry catch up on, 'Oh, it's not just going to be chips and GPUs. It's going to be boxes, too,' because somebody's got to run the agent, somebody's got to feed the data. I think the industry hasn't caught -- and memory, memory companies exploding, going big right now. I think the industry hasn't caught up on -- it's all data. There's tons of data, training data that you want to keep track of, data that you need to feed, sometimes redundant copies of data. We say you don't have to make redundant copies in our system because you're not moving it to a cloud or whatever you already have that data. But that data needs stored, and we're definitely seeing huge stored and fed, and we're seeing a huge pickup in our storage along those lines. We have our Fusion platform, which is AI in a box that makes it easy. We have Scale, which is the -- IBM Scale, which is the best way to feed NVIDIA GPUs. We have -- in fact, the National Oceanic and Atmospheric Association does that for worldwide weather, and there's no other platform that could feed these GPUs at a level that we do. And so storage software is big. But as we move that storage software, there's a huge amount of storage hardware that goes with that. On mainframes, it's our DS8000. In the distributed space, it's our flash systems, but that stuff is growing double digits and north. And in fact, the stuff that our software runs on, so Flash and Scale and those things, we see that growing at like 50%, 60%. So storage as an industry is kind of quiet. It hasn't gotten this big pop that chips and boxes, server boxes have got, but I see that coming because I see the demand there. And then all of that needs supported worldwide in a global kind of way. That's our TLS support business, and we've been really happy with that. TLS, if you watch our results, it will look kind of strange this year where you're like, 'Hey, that seems to be struggling.' A lot of that is mainframe refresh. When people buy their new set of mainframes, which are overachieving, they get a warranty. That warranty, then they're not paying me for service on it. It came bundled with the system when it comes. So it takes a little while for the TLS part of that business to kind of go back up again. So we're watching for that and feel really confident in it.

And then just on transaction processing sort of as we think about -- in mainframe launch years, typically, we've seen a little bit of deceleration in transaction processing. Through cycle, it sort of picks up. So are we kind of at that point in the cycle where we should be expecting transaction processing to pick back up?

Over the last 3, 4 generations, and we see no reason for it to change, flattish in the year of intro, single digit in the next year, which is this next year and then accelerating beyond that in the third year, then we ship again. Oh, and the cycle on Z, I often get that question. We've settled now. I mentioned that we have over 100 clients that help us codesign the next generation of Z. And what we figure out -- we have a client design council and all that. So they basically influence -- they don't even just influence us. They vote on what they want us to do with that platform. We're locked in on a 3-year cycle at this point. It's too disruptive to them to say, 'Well, we're putting this and that in, maybe this one will be 5 and the next will be 2.' They know, 'Okay, you can plan on that, we can plan on that.' So it's kind of -- it's a heartbeat. And we even structure our design cycle that way. It's a release train. You're either on the train or you're not on the train. It's coming out in that second quarter of the third year. And so that's very predictable. So that kind of tells you. We know what's going on with TPS, and it's tracking the way we'd expect it to.

Yes. I know we've only got like 2.5 minutes left, but I want to hit on a big topic that something we didn't touch on. Yes, like what are you excited about the future?

A whopper is quantum. And we've been quietly excited about it inside the company, but we've now been talking a lot more about it and announcing some really big things. So certainly, most of you probably saw our Anderon announcement, our partnership with the government. They're investing. We're investing to create the world's first quantum foundry. You say, what's a quantum foundry? Well, somebody's got to do chips for quantum. And those chips are like silicon chips. They're still silicon, but they're not digital. They're not ones and zeros. It's the analog technology that you have to build to be able to do quantum computing. And it's the first of its kind. I think it's really awesome because it shows that we're ahead of the industry. They wouldn't be betting on a second-placed player. So that's really good. We've announced that this year, we expect to show Quantum Advantage. For those of you who haven't been following the space, that basically means solving some problems that you can't solve on traditional computing in any kind of reasonable time frame. And we've got various clients that we've talked about publicly and a bunch that we haven't talked about publicly that are on the cusp of that for various science problems in medical research and chemistry and financial, I think advanced Monte Carlo kind of simulation stuff. So that's something we're really excited about. So we've talked about Quantum Advantage this year and then the world's first 2,000 qubit -- qubit is kind of a notion of these quantum state elements and first 2,000 quantum qubit fault-tolerant machine by 2029, which is when we think it's kind of -- that's its moment of, 'Oh, this is a real volume thing and cranking along.' So we're excited about it inside of IBM. Arvind likes to say it's no longer a science problem. It's an engineering problem, meaning we know how to do what we need to do, and we need to go execute it, and we're executing it, and we're on schedule to execute it. We just need to follow the steps. We can see, okay, this is where we'll be in the FET technology, the error correction technology, the cooling technology, and we're on track to go deliver that. So quantum is going to be a real thing this decade. And we already have 90 systems with clients doing quantum development on our Qiskit software, pretty excited about that. If you think about how AI team, kind of with its ChatGPT moment, there was a lot of stuff going on with GPUs and CUDA and that kind of stuff. That's the stuff that's going on right now with Quantum and Qiskit is developing, experimenting universities, medical centers, all those things. So really excited. It's good to...

Well, thank you so much, Ric. I really appreciate you being here. Thanks for bringing all your insights as usual. Always a pleasure.

Thanks, Wamsi. Always nice talking to you.

Thank you so much.