Good afternoon, everybody. Thanks for joining day two of Citi's Tech Conference. My name is Tyler Radke. I co-head the U.S. Software Sector here at Citi. We are happy to have IBM. We have the Chief Commercial Officer and Senior Vice President of IBM Software, Rob Thomas. Rob, thanks for joining us. I think it would be great for the audience here, if you could just give us an overview of your role within the IBM organization.
Yes, today I run software products, and I also lead our go-to-market, so I wear two hats. I did both jobs independently before, now together, so I spend roughly half my time on each of them. On the software side, that means: what products are we building? How are we engaging with clients? How are we investing for the future? A decent bit of time on M&A. And on the go-to-market side, it's all about, I'd say, continuing the go-to-market evolution that we started a couple of years ago, building a more technical go-to-market, building our customer success teams, and I spend a lot of time with clients around the world.
Got it. Got it. Maybe give us a sense, post-separation, on IBM's high-level strategy. What are you doubling down on, and, and how has that changed over the last couple of years?
On Arvind's first day in the job, the letter that he wrote to employees, which was shared publicly, said IBM is going to be the hybrid cloud and AI company. I think we've been very consistent in sticking with that, and you can start to see it in payoff and results because focus is a very powerful thing. That's also led to even more focus around what businesses we're not going to be in. So we divested some of our healthcare applications. We recently announced our intent to divest The Weather Company. So we've gotten very closely focused on what does it take to be the best provider of technology for hybrid cloud and AI.
We do that primarily through two motions, which is part of how we redesigned our go-to-market around technology, so a team that's focused just on selling technology, building, bringing very deep skills to clients, helping them implement technology, and then consulting, which is being on the front end of how clients are thinking about their transformation with technology as an underlier and being a key partner in that. Lastly, I would say a big part of executing the strategy and the go-to-market is how we've embraced the ecosystem. We've built new partner programs, we've built new strategic partnerships with a bunch of companies that we can talk about as we go. But I think people are getting the sense now that today's IBM is a little bit different than maybe IBM of the past, and we're really optimistic about the direction.
That's great. So you spend a lot of time with customers, obviously, as, as the head of IBM sales teams. What, what are you hearing on the ground? Certainly, there's, there's been a lot of caution out there on the, on the macro front, but are you starting to see new projects get reprioritized? How, how does the environment compare, relative to a year ago?
It makes a big difference where you are when you ask that question. I've been around the world so far this year. I've been Indonesia, Singapore, coming up, I'm doing Japan and the Middle East and India. I've been to South America. So there are macro factors that we all read about are happening differently in different places. I would say what is dramatically consistent is companies are more optimistic about the role of technology in their evolution or transformation as a company than perhaps ever before. And I think some of that's driven by demographics. I mean, many of the countries that you go to, there's not really enough workers for everything that has to occur as you think about on a 5- or 10-year basis. So the only way to deal with that is through automation, through technology.
And so I see clients really aggressive about thinking about how to apply technology, how can we go faster? Obviously, at this point, I can't go anywhere without there being a generative AI discussion, as you can imagine. I'd say it's a little bit different by country, but the one common thread is there's more optimism on technology in the enterprise than I've probably seen in a while.
Yeah. I guess on the generative AI point, and I'm sure we'll go into the specific product areas, but just give us a sense for the, I guess, maturity of those conversations. Is it, "Hey, Rob, what is generative AI?" Or is it, you know, "What can I, you know, procure from IBM?" Just give us a sense for, you know, how those conversations are evolving in terms of translating into something more than just a conversation.
To give you a little bit of the timeline, we started investing aggressively this in 2020, and it was kind of an unpopular investment at that point because nobody really knew quite what it was. It took a lot of CapEx to get started, but we had a thesis that there was something real here that would solve the problems that we all faced in the machine learning era around a lot of work needed on data labeling. It was very manual, it was very time-consuming, so that's played out. I think ChatGPT was a wonderful thing to happen because it kind of got everybody's interest. And so we started working with clients in January around watsonx, which we then announced formally in May, and we made available in July. There's tons of experimentation happening. What we found is you have to quickly connect this to use cases.
Okay, losing the noise? Hello. I think it's cutting in and out, but-
... You have to quickly connect this to use cases.
Yeah.
There are three use cases that have kind of jumped to the front of what we're doing. Number one is automating repetitive tasks. It sounds obvious, but there's a lot of jobs in the Fortune 5000, call it, where people are doing repetitive tasks over and over again. Generative AI can have an immediate impact on that. Next is customer service. Applying large language models to things like watsonx Assistant, you can get incredible containment rates where you don't even have to have humans involved, meaning 90%+. Then lastly, this one takes a little longer, but application modernization. Clients thinking about, how do I use something like watsonx Code Assistant, modernizing my technology infrastructure, moving to cloud-native applications?
I think we might get you another mic here.
Moving to cloud-native applications and using generative AI to make that process easier, so things like Code Assistant. So at this point, a lot of experimentation, but as we start to, I'd say, focus in on use cases, you can see how companies will get a pretty quick ROI.
Got it. Now, that's helpful framing. And the other topic that we've heard a lot from, you know, other software companies in our coverage is cloud optimizations. And maybe could you share a little bit what you're hearing from clients there? I know, you know, it's certainly something that's been in the world out, you know, for at least a year. Do we think we're near the end of it? Is it, you know, still a couple more quarters to go? What are you hearing on the cloud optimization front?
Well, we bought Apptio-
Yeah
... which shows you where our, where we've placed a bet, which is, I don't believe that this is a short-term phenomenon or a fad. Companies will always think about every year, how are you optimizing your investments in technology? And with Apptio, we get three pieces. We get Apptio One, which is about any of your technology that's on-premise, Cloudability, which is cloud optimization, and then a lesser-known product called Targetprocess, which is, what is my labor spend that's tied to my technology spend? So I can look at total cost of ownership. So I don't think this is a one-shot thing. I think this will continue because as companies want to free up budget for generative AI or quantum or whatever they want to do, they're always gonna be looking at, How do I become more efficient?
How do I become more productive in how I'm spending? And so we're really bullish on what we're doing with Apptio.
Okay, makes sense. So I think it's been about four years since IBM acquired Red Hat. It was, you know, one of, if not the biggest, software acquisition at the time, you know, really placing your bets on hybrid cloud, open source. Can you talk about the journey so far with Red Hat? Where do you see the biggest growth opportunity going forward as you think about that business?
The thesis when we acquired Red Hat was that the world would be multi-cloud and hybrid cloud. I'd say for the first few years, nobody really believed that that was gonna be the case. Most of the client discussions I had, everything was about: We're choosing one public cloud, we're gonna move everything there. I think that completely changed a year and a half ago, maybe two years ago, where now I don't talk to a single client who's not saying, "Our strategy's hybrid, we're gonna be on multi-cloud." At this point, Red Hat is the best answer for hybrid cloud. You can see it in our numbers. We've talked publicly about how OpenShift is now over $1 billion, growing 30%+, so we have a lot of momentum with OpenShift. OpenShift also drives a lot of Linux.
I would call it the hidden gem in Red Hat, that's maybe not so hidden anymore, is Ansible, which is about how do you do automation and what you're doing in DevOps. As part of watsonx, we've announced watsonx Code Assistant for Ansible, so you get code generation for developers that are building in Ansible. And so we're really pleased with Red Hat. I think since we acquired, it's roughly 4x the revenue base, so we've gotten major momentum. I think the world has kind of come around to our original thesis, and now it's just about continuing to accelerate this.
Yeah. And I guess staying on the open source topic, obviously, Red Hat is probably the most successful success story in open source. How important is open source in your conversations with enterprises?
We've been on open source as a strategy since 1999, I would say, where we first got behind Linux. I know Red Hat gets all the credit, but I don't think Linux would have gotten to the point it did if IBM hadn't endorsed it back in the late 1990s. I think that was a pretty seminal moment for both Linux and for open source. Then you fast-forward through the years, we were early contributor and committer around products, projects like Hadoop and then Spark. A lot of the work we did in Spark really became fundamental to how we build software. Spark is embedded in many of our products right now. So then you get to Red Hat. Obviously, that was a huge step for us in terms of open source.
Now we're always thinking about, as we are applying open source, are we better off being the builder, committer, contributor ourselves, or do we partner for it? An example I'd give you, on open-source databases, when we looked at that market, it's like, it's hard to be the provider of five or 10 different open source variants of database. We decided to partner for that. We partner with MongoDB, with DataStax, SingleStore, Cloudera, EnterpriseDB for Postgres. It's, it's great for them because they get distribution, we get product integration, so it drives other IBM products, and for clients, they get one place to, you know, one company to work with on their data strategy. Open source doesn't mean we have to be the lead on the project, per se. We also think a lot about partnering around open source.
Probably one of the things I'm most excited about right now with watsonx.data, that is a Presto engine using Iceberg formats, and we see a lot of momentum happening in kind of these new data architectures.
Got it. Got it. On the database side, could you just maybe talk a little bit more about that partnership? Is this, you know, an opportunity for, you know, some of these database vendors like MongoDB to run at some point maybe on the IBM cloud? Or how are you also participating in that, you know, initiative, if it's another third-party database?
We do product integration, because we want somebody that's using MongoDB or Cloudera, just to use those two as an example, to want to use IBM data integration tools.
Mm
... or to use watsonx along with the data that they're storing there. So we view it as a technical integration-
Mm
... and then distribution. We help them get to market, and some of them are at, they're at different levels of scale. Some of them we can help in the U.S., some get more lift from IBM around the world, where they may not have a go-to-market channel.
Yeah.
It's a combination of those two.
Okay, that makes a lot of sense. I guess sticking on the database theme, you know, IBM has been a leader in the database market for a very long time. I think your core offering, Db2, you know, still has very high market share. I guess, how are you just seeing the trends in that space? You talked about open source, and obviously, there's some newer vendors like Mongo or DataStax, that are having a lot of growth. I guess, what type of workloads are you still going after with your own products, and where are you kind of relying on partners with other database vendors? Just kind of frame, you know, the growth opportunity for IBM database.
Database is a very good business, because clients make a choice, they start building applications using databases, and they tend to grow over time because data volumes are growing. So we're really happy with how things like Db2 have done. The thing I'm probably most excited about is I think we're at the start of what I would call the fourth epoch in data warehousing. First one was around OLAP. A lot of people came into the OLAP market. I think IBM and Oracle, Teradata were probably three of the big ones at the time.
Mm.
Next was appliances. We had a very successful play with Netezza. Then you went to the third chapter, which was separated compute and storage. The fourth chapter, I think, is as different from the others as they all were from each other, meaning this is going to be about open architectures. It'll be things like Iceberg format, so easy access. Instead of proprietary data formats and storage, it'll be open data formats, it'll be unified query engine. So we're investing a lot in the Presto project and also Prestissimo, which is a unified query engine. We do work with Facebook around that. I think this is going to dramatically change warehousing. These things take, you know, three to five years to play out. But the economics of the third chapter, separated computer storage, are not great for clients. It's very expensive.
We think coming in with a new architecture, a unified query engine, we can give you 2 or 3 extra performance at half the cost, and we think this will be a growth driver for us.
Yeah. That... And is that kind of the rebranded Netezza offering, or is that a new SKU? Or just kind of talk about the product there?
So this is watsonx.data.
watsonx. Okay.
So that is the Presto engine that we're building.
Got it.
Now, what does that mean for Netezza and Db2? We still have a lot of Netezza clients and a lot of Db2 clients. So part of being a unified query engine is we're enabling clients on Netezza and Db2, they can start to offload into-
Mm
... watsonx.data. For certain applications or certain workloads, we can actually treat that as one query engine. So it's giving them the ability to utilize the investment they have, but then grow into new workloads using watsonx.data.
Got it. Along similar lines of the data warehouse theme, I think you recently announced hybrid cloud Mesh, which supports kind of some data sharing capabilities, data connectivity. It sounded, at least to me, kind of similar to what Snowflake has been talking about in terms of data sharing, which has been a very popular use case for them. Can you just talk about that offering and some of the use cases you're seeing from customers?
I'd say it's a little different than that. So let's go back to kind of how we got here. As we were thinking through our strategy around hybrid cloud and AI, and I talked about the focus on the business, we started looking at, what are the places that we don't participate in that are highly complementary to our strategy? The obvious one, to me, was software-defined networking.
Mm-hmm.
I think we're at the very early stage of networking, going from being hardware-centric to more driven by software. And when you think about a client implementing a hybrid cloud strategy, it's really hard to do that without application connectivity.
Mm-hmm.
And so hybrid cloud Mesh is organic development that we've done on, I'd call it application-centric networking-
Mm.
which is you can run the same application on multiple clouds. How will it communicate and talk to each other? You could do that between on-premises and cloud, and I think there's a real opportunity here on networking that has largely been untapped, and it's highly complementary to somebody that's thinking about hybrid cloud or modernizing applications, and those are two places that we want to be a significant player.
Okay. Okay, got it. I guess going back to the watsonx, you know, on the generative AI theme, could you just talk maybe more broadly across IBM, how you're thinking about generative AI, both from, you know, the software perspective, but also as you think about, you know, consulting and services?
I would describe kind of a, a stack for how we think about it. At the top layer, we deliver what we call assistance. This is packaging up generative AI models targeted at a use case. So I mentioned watsonx Orchestrate, which is an assistant for automating repetitive tasks, watsonx Assistant for customer service, watsonx Code Assistant. These are all literally what they sound like. They're assistants-
Mm
... for a non-technical user to use generative AI. Next, you have what I'd call a software development kit. We want to work with other software companies around the world that want generative AI to be part of their products, but may not be able to invest at the level that we've been investing. Like I said, we've been at this for three years. If that's not your core business, it's hard to invest for three years before you have a product. So I think probably the best example of that is SAP, who announced that they've adopted watsonx as their generative AI platform.
Yeah.
They can pick up pieces from the SDK that give them different experiences when they're working with clients.
Okay.
Next, you've got the platform, that's the studio, which we call watsonx.ai, building models, training models, tuning models. We've integrated Hugging Face, so you can use open-source models. We announced that we've integrated Llama 2 from Meta. We've got IBM models, which are models that we've trained based on our data. Then we've got watsonx.data we talked about, and watsonx.governance, which we will release later this year. I think when that comes out, we'll be the only person that has a governance product for generative AI.
Yeah.
Governance means fairness, transparency, model explainability, lifecycle management of models, data lineage. So as we think about generative AI, we want to deliver that complete stack, from assistance to the software development kit, to the platform itself.
Yeah. And that's a... The governance is a huge topic of importance. I guess, as you think about the core differentiation of IBM, I mean, sounds like it's kind of the complete stack, but what do you see as maybe the number one or two biggest differentiators compared to, you know, AWS or Azure or Google's approach?
I think one of the advantages to IBM's model is the fact that we have consulting and technology.
Mm-hmm.
'Cause it's pretty clear to me, the early years of this is going to be about clients wanting assistance to get something into production and get an ROI, which is why I think you'll see this monetized and consulting for us first and fastest, because clients want help. You think about the use cases I talked about, automating tasks, customer care, they're gonna want a consulting partner for that. So I think that's one of the advantages that we've had. We've also made watsonx available to all the global systems integrators that we work with. So we're launching centers of excellence with the likes of HCL, Accenture, Deloitte. And so I think in the early days there's a big services opportunity here, but we're also gonna monetize through the software because we love the economics of the software.
Yeah. I guess, as you look at the portfolio today, obviously, it's evolved a lot since you've joined IBM, but from an M&A perspective, like, what are the biggest areas that are most attractive to IBM? Obviously, you have a lot of opportunities, but whether it's open source, generative AI, but what kind of makes the most sense just from a, you know, category perspective?
If you look at what we've done year to date, I think it's illustrative for how we work through our M&A process. We've done some smaller deals, which was acquiring largely technology that would accelerate organic products that we were building. Like, for example, we acquired Ahana, which is a great team that has committers to the Presto project to accelerate the delivery that we were doing on watsonx.data. That's in the smaller category. We acquired Polar Security because we have a great data security product called Guardium, but we wanted to take Guardium and make that available for multi-cloud and hybrid cloud, so you could look at data across all clouds, and Polar Security was a great, I'd call it a technology tuck-in-
Mm
... that gave us that capability to get to market faster. Then you go to bigger ones. We acquired Apptio, which to me was, I'd say, rounding out our vision around IT automation, which is you need capabilities around IT observability, resource management, but having financial operations with Apptio ... It kind of makes us, I'd say, the only provider in software that can deliver everything you need for IT automation. So that's about being, you know, a bigger acquisition that's highly complementary to a segment that we'd already made big investments in. So we continue to look at deals of all sizes. Size is not a strategy per se, but we're thinking about how do we accelerate the areas in software that are important to us. We also do a decent bit of acquisitions and consulting as well.
Mm-hmm.
But for software, we've had a very good year in M&A.
Okay. Okay, makes sense. Wanted to shift a little bit to automation, and maybe it'd be helpful just to kind of frame how you see the portfolio of IBM, you know, automation products. Where is the opportunity? Where are you investing? And just kind of how that might change with generative AI.
I would break automation into three categories, and all three are important to us. Firstly, what I would call business automation or RPA.
Mm-hmm.
How are you automating different tasks? I talked about watsonx Orchestrate. What's interesting about watsonx Orchestrate, I think it's a good example of today's IBM, in that the first customer of watsonx Orchestrate was IBM. And we've talked publicly about the use case around HR that we've implemented, where we took an HR service center, and in a period of a year, we were able to automate 90% of the tasks.
Mm-hmm.
So massive labor savings and massive increase in clock speed in terms of how we execute. And we learned a lot about what worked and what didn't work in the product by going through that. And so by the time we got to the point of launching watsonx Orchestrate, we were really confident that this would be a great product for the clients that we're working with. So I'd say that's one of the main focuses in what I call business automation.
Mm-hmm.
Next, you have IT automation. We started with an organic product called AIOps that we built. We acquired Turbonomic for resource management and Instana for IT observability, and we can now give you basically full stack observability and action for IT automation with the combination of M&A and products that we've built. And then the third category, what I was alluding to on financial operations or FinOps. So automation, to me, is business automation, IT automation, FinOps. Maybe there's another category that develops over time, but those are the areas that we're gonna be focused on.
Okay. On the transaction processing side, I think that the performance there is, has been better. It's flipped to a growth driver. Could you just talk about what's underpinning that, and are you expecting that to continue?
It's really interesting. The timing for this is highly linked, I believe, to the timing where I talked about when clients shifted from, "We're gonna be public cloud only," to multi-cloud.
Mm-hmm.
Because when there's a top-down mandate of, "Hey, everything is going to one cloud," something like the mainframe, by definition, would get less attention. The minute that clients kind of flipped in their mindset and said, "Wait, hybrid cloud is actually gonna be our strategy," suddenly the mainframe became critical again, and they started putting more workload on the mainframe. Actually, your company-
Yeah
... Citi, spoke at a conference earlier this year, where the MongoDB implementation that you all have, you started running that on zLinux.
Yeah.
Because it was like: Why do we need, like, 300 servers to do this when we could run it on a single zLinux partition? Massive floor space savings, massive energy savings. It's kind of like a no-brainer. But that probably wouldn't have happened if, if you hadn't embraced mainframe as part of the, the IT strategy again. So I think there's been a big shift where mainframe is now a key part of the strategy. That's different. Second is, we've started to do more innovation around the software stack in mainframe. I talked about watsonx Code Assistant for Z that we just announced. Before that, products like Data Gate, which gives you a read-only version of your data on the mainframe, so you can do warehousing-style workloads. So we've been innovating in that stack.
Third is, we have taken some pricing action that we've talked about, and it's proven that, clients see value in the platform and will continue on it.
Yeah. Okay, great. Let's talk a little bit more about go-to-market and specifically around partnerships. You, I know you addressed some of these partnerships on the database side, but given that, you know, you're now leading a much more product and software-focused business, just how has kind of the breadth of partners that you're engaging changed?
As we thought through our partnering strategy and what we want to do in the ecosystem, I would say it came down to a few categories. First was, we said: We need to pick some big strategic partners that we develop a technology strategy with and a go-to-market motion. And in that category, I would put AWS, Microsoft Azure, Salesforce, Adobe, SAP, more recently, Palo Alto. These are companies where we can build a big consulting practice, but we also have a level of technology synergy. We've put a lot of our software onto AWS. We've put software onto Azure. We have technical partnerships with SAP around watsonx that I described. Same with Adobe. And so these are big partnerships for IBM that I would say are equally important to those companies, 'cause it's, it's opportunity for both of us.
So that was one category, was being very thoughtful and selective about big strategic partners. Three years ago, we had no relationship with AWS or Azure... for consulting or technology. So this is a major change in direction that's resulting in, in revenue growth. Next category, global systems integrators. Now that the majority of the company revenue is product, you have to work with all global systems integrators. So we've gone out of our way to embrace working with the likes of Deloitte, Accenture, EY, HCL, TCS, Wipro, all of them, on helping them build skills, helping them get more familiar with IBM technology. In many cases, our consulting team also works with them, 'cause a lot of projects, certainly in the government space, become multi-vendor or multi-bid, and so we've built partnerships out with them. Thirdly, is we redesigned our resell program. It's called Partner Plus now.
The problem to solve there was pretty simple. We had to make it way easier for partners to work with IBM.
Yeah.
Way easier to use software, use our hardware, make it really easy to understand how partners would make money, so we redesigned that program. Those have been the three main focus areas, and I think we've made a lot of progress on ecosystem. I, I think partners sense that this is a bit of a different IBM that they can work with-
Mm-hmm.
and we just want to build on that momentum.
Yeah. Oh, that's great. And I guess, do you have, you know, rough targets or, you know, frameworks in terms of the percentage of source deals that you're looking to engage partners with? Or, how do you kinda think about where we are in that journey?
I think we're still early in it. Our goal is to be a platform company for hybrid cloud and AI. You can't be a platform company unless you're getting 50%+ of your revenue from the ecosystem.
Mm.
We want to be as aggressive as we can at getting partners onboarded to watsonx, partners working with Red Hat, and so I think we're still very early on this, but we've made more progress in three years probably than even I thought we could.
Yeah. And as you look internally at your own direct sales force, what are some of the big changes that you've made? And, you know, certainly you're in a lot of really exciting developer kinda markets. How are you thinking about, you know, introducing more self-service or, you know, product-led growth initiatives as some of the high-growth areas?
Three big changes in go-to-market. One was compensation. Sounds basic, but salespeople are motivated by the right incentives.
Mm.
We changed them to make them much more lucrative. That's had a positive impact. Second piece was building a much more technical sales force. We've built two new teams. One's called Client Engineering, which is a pre-sales team. It's literally what it sounds like. It's engineers who go to work for a client even before we've signed a deal.
Mm.
So they're trying to help the client explore technology, build MVPs, build pilots, get familiar. That's had a big impact. And then the second team is a customer success team, which is post-sale. Client's bought a product, how do we get them quickly up and running, consuming the product, showing them new features, showing them the new version? That's all about driving consumption and ARR growth.
Mm-hmm.
So that was the second big thing, was just changing the complexion of the go-to-market. Then third, as you say, is product-led growth. We need to acquire thousands of new customers. That's the next ambition-
Mm
... which is typically gonna be done through a digital sales motion, handed off to the ecosystem, so to connect it back to the ecosystem piece, which means products have to be discoverable on the web. There has to be trials for the products. I would encourage you all to go look at them. I think we've got a lot out there-
Mm-hmm
... that are pretty good, but every day is A/B testing and figure out, how do we make it better? But that is the third dimension, and that's the earliest, of the three strategies.
Got it. Got it. I guess, are there specific products, maybe the watsonx series, that you expect to see the most success with those product-led growth initiatives, or are they still too early, or?
For product-led growth, the best products to acquire new clients tend to be SaaS products. It's probably obvious.
Mm-hmm.
But also the ones that are more, I'd say, familiar to an end user. So I think about things like Planning Analytics for financial planning. It's a great product. Most CFOs don't really wanna talk to a salesperson. So if you can give the finance staff a way to experience that product online, you can get a lot of momentum. Maximo is another good example. And to your point, watsonx will be a big part of our focus for product-led growth.
Yeah. Great. Well, in the closing last few minutes here, I did wanna ask you a couple bigger-picture questions. Just as you look out into the technology industry, what do you think is our, you know, one or two big driving forces that may be under-talked about? Obviously, generative AI, which probably has enough press time, but, like, what do you think people aren't paying enough attention about, that could have, you know, more dramatic impacts over the coming years?
I would say first is quantum computing. If you look at... There's a recent IDC report that said the market was $1 billion or so in 2022, going to $8 billion in 2027, so there's a real market forming here.
Yeah.
Granted, it's early. But we, last year we released a 400-qubit system. This year, we'll go over 1,000 qubits. We have 20 quantum computers, so more than anybody else in the world. We developed Qiskit, which is a developer toolkit for building applications for quantum. We think we'll get to 4,000 or so qubits in 2025. So we have a significant technical lead here.
Mm-hmm.
But it's an early market. But we're really excited about it, because we think there will be significant change in technology based on quantum computing, and we think we're in a good position as that plays out. But again, we're investing for the future here.
Mm-hmm.
And so I think that's probably number one. Two is probably something you don't think as much about for IBM today, but core semiconductor process technology. You may be familiar with Rapidus in Japan, which is the company behind the Japanese government initiative on bringing semiconductors onshore. We're the technology provider underneath that. So this is work that we do at the Albany Center here in New York. And for everything that you all see about what's happening in the world of semiconductors, including geopolitics-
Mm-hmm
... we think having a strong technology development of semiconductor technology is really important.
Okay. Those are very interesting. And I think on the quantum side, my colleague Rob over there is hosting a session later this conference on it, so definitely tune into that. I guess in the closing couple minutes here, Rob, it'd be great if you could just end with what are your top two or three biggest priorities for the company, and then feel free to address anything we didn't hit on.
Number one is keep our momentum and go to market. I think we've really changed the perception of IBM in terms of how we're showing up with clients, but that job is never done.
Mm-hmm.
So it's what do we have to do next? We're doing a lot of thinking about expansion globally. I mentioned I've been to Indonesia this year. I'll be going to the Middle East. We're investing in markets that have large GDP, that are putting technology at the forefront of, of how they're driving the, the transformation in the country. So that's really about evolving everything that we've been doing in the go-to-market. That's number one. Two is organic innovation. How do we get more capacity of engineers, more innovation in IBM happening? Really pleased with watsonx and how it came to market, but also thinking about what are the next three or four things that will have a big impact on enterprise technology. Third is M&A, which is complements what we do organically, but spend a lot of time thinking through M&A, what we should be doing next.
We'll continue to be opportunistic there as, as those pop up. Lastly is we just want to be a great partner with other partners. Everything I talked about in ecosystem, how do we bring in more partners to be a part of this journey, help them be successful with clients? I'd say those are the big focus areas.
Awesome. Well, thank you, Rob. This is a great discussion. Thanks, everyone, for joining in the room, and appreciate everyone coming.
Thank you.
Thank you.