All right, there we go. Good morning, everyone. Thank you for joining us. My name is Brian Essex. I'm a Software Analyst at J.P. Morgan, and with me today I have John Granger, Senior Vice President of IBM Consulting. He runs that group. John, thank you for joining me. Maybe a good place to start is to introduce yourself. You know, you've had a lengthy career with IBM, and you're currently leading IBM Consulting. Can you share a bit about your background and the business that you're running today?
Yeah, look, I mean, very quickly, I actually came into IBM through IBM's acquisition of PwC Consulting in 2002. I was a partner in PwC. Actually, like many of the leadership today of IBM Consulting, we've still retained quite a lot of that PwC backbone. I've worked, I've run the business for the U.K. I've worked, I've run IBM Consulting in Europe. I lived in Madrid for a bit. I went and ran our application business for a couple of years in Bangalore. Worked in the U.S., now I'm back based in the U.K. I mean, just to talk a little bit about our business, Brian. I mean, we're gonna come on to talk a lot more about it, I'm sure.
About 160,000 people. I mean, Now, after the spin off Kyndryl, the infrastructure services business, we're about a third of IBM's revenue, but perhaps interestingly, two-thirds of IBM's people. If you talk about an IBMer, then it's like as not you're talking about somebody in IBM Consulting.
Excellent. Thank you for that. There have been, you know, quite a few changes, recently, particularly under, you know, Arvind's leadership. How would you describe the difference that you've seen in management and the way the company is run with the strategic direction now that you have someone that's a career technologist leading the company?
Look, I mean, all of our CEOs have different strengths. I've worked for Sam, I've worked for Ginni, I've worked for Arvind. I mean, I think Arvind's strategy, if you had to sum it up in a sentence, is for IBM to deliver transformation powered by the preeminent technologies of our time, hybrid cloud and AI, leveraging the ecosystem. If you ask me, you know, the difference that he's made, then I think I'd probably point to three things. I mean, the first is that with the sell-off of, or the spin-off of, Kyndryl, and with that strategy, as it were, he has simplified our company, you know, very significantly.
In the way that we are now organized and run ourselves, then I'm accountable on the consulting side for predominantly leading the transformation. My technology colleagues, you know, drive the products, you know, and technologies that support hybrid cloud and AI. We all contribute around the leverage of the ecosystem. I think first of all, it's a much simplified company. I think the second thing I would say, Brian, is that, look, I mean, I talked to you about that, you know, strategy in a sentence powered by the preeminent, you know, technologies of our time, hybrid cloud and AI. Arvind laid that out three years ago. Yeah. You know, particularly, I mean, I think that that shows that he has absolutely positioned us in, I think, what you Americans call the right neighborhoods. Yeah.
I mean, in terms of hybrid cloud, you know, has been a really important focus for enterprise clients. Clearly, you know, with generative AI now coming to the fore, it's great that we've been in this space now for some time. Then the third thing that I think he's done, which is perhaps, you know, a difference in emphasis from previous administrations, as it were, is Arvind is very committed to, as I said, leveraging the ecosystem. Arvind is passionate about no one company can hope to provide, you know, to have a monopoly on all the technology solutions that a client needs. Therefore, what you've got to do is, you know, to ensure that you can orchestrate and integrate those solutions to provide, you know, value to clients.
He's really encouraged a culture at IBM to ensure that we're making that ecosystem work for us. I think it's fair to say that in IBM Consulting, we've led the way in that. I mean, you know, we announced in Q4, I think. I mean, we've now grown our AWS business to over $1 billion. We've grown our Azure business to over $1 billion. We've always had a big SAP business. We've got other partnerships with Salesforce and Adobe that are coming through, you know, strongly as well. I think that's been really important.
The three things I'd highlight then, the simplification of the company, the positioning of ourselves in the hybrid cloud and AI spaces, and then, you know, how we're now encouraged, you know, to really leverage the ecosystem, which I think has been very beneficial for our clients, but also for IBM.
Excellent. Excellent. You know, how have some of the actions that IBM has taken to reposition the consulting business help you serve clients differently than the way that you were positioned before?
Well, I think the first thing that we've done is we've got real clarity about what our offerings are, what we call our growth platforms. You know, we're really clear around three growth platforms. The one is, the journey to cloud, application migration, application modernization, the management of cloud in a hybrid cloud environment. A second growth platform is really around intelligent workflows, Brian, which is, you know, that's where all of our capability lies in terms of our process expertise, talent, finance, supply chain, customer care, and so on and so forth. Our BPO business, as well as our whole data and AI capability. Thirdly, we have a security growth platform. Those are the three areas that we're focused in.
In terms of how we've repositioned IBM Consulting, I think that's really, you know, we have a very intentional framework that we call Transform to Grow, which is about ensuring that we double down, if you will, on the few things that will really make a difference. i.e. focus more and more on less and less. The first of those has been talent. In the last couple of years, we've grown our business now to 160,000, and that's not just, you know, a big influx of practitioners. That's also been a strong influx of, or, you know, building up of go-to-market, you know, senior talent. We've. It's not just been about the quantum of talent, it's also been about the quality.
I mean, a lot of certifications that we've now driven, particularly with our partners, 66,000 cloud service provider certifications, over 50,000 ISV certifications. Second thing we've worked on beyond talent has been brand. Previously, before the spinoff of Kyndryl, we were Global Business Services. Well, when you're trying to recruit kids or, you know, you put Accenture, Deloitte alongside Global Business Services, it's hard to work out what we do. Now we're IBM Consulting, the choice is very clear. I think that's enabled us to not only be successful in recruiting talent, but also to ensure that we've really reintroduced ourselves, you know, to our clients. I think that brand is something that we've stayed on. A third piece has been client segmentation.
As is the way with all good consulting organizations, we've been trying to cut the tail to ensure that we go deeper and deeper with the clients that we do have. We're very focused on, you know, on a very curated set of top accounts. Fourth thing would be big transformational deals. I mean, I think there's a lot of those in the marketplace, and we've maybe not had our fair share of those historically. I think you've seen in our signings that we've started to pick up much more of those big technology-driven transformation deals. The last two things would be partnerships. You know, we talked about the ecosystem. I said that we've led the way on that. I think our partnership revenue is now approaching 40%.
You know, we, as I said, we've built these very big businesses with AWS and Azure. You know, really, you know, made a very deliberate pivot to, you know, to how we work with partners in the market. The last one then is acquisitions. You know, in particular, we've done 14 acquisitions in the last couple of years, which is a lot more than in the last 14 years. Many of those acquisitions have been very specifically geared towards underpinning those strategic partnerships. We bought Nordcloud, for example, in Europe. That brought a lot of competencies in AWS and in Azure. We bought Neudesic, which is the last, you know, Microsoft shop standing in, or sizable Microsoft shop standing in North America. We bought Taos and so on.
We've really deliberately focused these acquisitions on reinforcing those partnerships. Talent, brand, client segmentation, big transformational deals, acquisitions, strategic partnerships. Just those six things. Stayed laser focused on those, and that, I think, has been pretty good for us. I mean, we've had eight quarters now of consecutive growth. You know, so far that, you know, that framework seems to be paying off.
Great. Great. Then, you know, IBM has stated that, you know, demand for technology transformation has been and remains pretty robust. You know, what are you hearing from clients on that front in terms of what's driving their demand?
I think, as I said earlier about, you know, our focus on these big transformational deals, I mean, I think it's very clear that in the marketplace, there is a lot of demand at the moment for technology-driven transformational deals. You can see that in our signings. You know, we had a very strong Q4, we had a strong first quarter actually, where we normally drop off, you know, a fair bit. We didn't drop anywhere near as much. You see it in our competitors' signings. I think it, you know, it's clear that that technology-driven transformation, whereas in previous times of economic uncertainty, you might have said that that was discretionary, and you'd see that fall away. We're not seeing that happening now. You ask about where that comes from. I think that's, you know...
I mean, maybe 4 drivers, a couple of which are still pandemic-related. I mean, I think the whole digital transformation in terms of virtualization of organizations and enterprises' relationships with their clients, with their customers, that still has to work its way through. There's a lot of transformation around that. A lot of work still to do on supply chains. We all experience that every day. The supply chain transformation work, you know, has still, you know, got a lot to do. I think the one that came as a result and as a consequence of the pandemic and some of the wage inflation that followed that is productivity and, you know, the whole AI piece. 'Cause clients have clearly felt that the price of some of the skills that they need to get is prohibitive. How...
That, I think has pushed them to think more about productivity. Then, of course, you've got cybersecurity. Those are the drivers. For us, we see the market, I guess, is probably about, you know, I mean, we think about $800 billion for, you know, for, you know, consulting services growing mid-single digits for the foreseeable future. About half of that is in the cloud and intelligent workflow space. To play back to what I talked about earlier in terms of our growth platforms, you know, we had cloud and intelligent workflows as our growth platform. We think we're pretty well, you know, adjusted for that.
The one area, I guess, in all of this demand, though, that we and others have called out is, you know, North America, the US, and I think there's a different market dynamic going on there. It's a paradox in the sense that the appetite for the big transformational, you know, technology-driven deals that I've said earlier, I mean, that's still there and we're seeing that in the U.S. market. I think there's more pressure on fundamentals, you know, that everybody's feeling. I would say that clients in North America have much less contingency. They, if there is work that is not part of this mainstream technology-driven transformation, then they're more inclined to delay it.
For some of the staff augmentation work and some of the enhancements that sort of sit around some of the bigger deals, a bit like pilot fish around a big whale, those things are sort of being, you know, held off. Whilst I would say that there's no evidence, you know, of any cancellation of work, we've seen no backlog reduction. There is a sense of, you know, some of the more discretionary work shifting a bit to the right and the pace of it slowing down. I mean, we'll continue to work through that, but, you know, I mean, that's the sort of picture that a common drive for large, you know, technology-driven transformations, but, you know, a bit more softness in the U.S.
market around some of that, discretionary work.
Is your visibility there better because, you know, perhaps customers experienced some of the benefits of transformation during the pandemic that kind of forced their hand, and now they wanna move faster with you on the transformation side?
Yeah. No, I think that's, you know, I think that's, you know, I mean, that's indeed, you know, how it's happened. I, you know, I think that, I mean, the reason this demand has held up is 'cause clients are now seeing it's a fundamental source of competitive advantage. I mean, it's not something that they can afford to, you know, to put to one side, yeah.
Great. Then how would we think about the way that IBM differentiates its consulting business in the market and how much is the success of the software business tied to consulting?
I mean, in terms of, I mean, as you all know, the consulting system integration market is really crowded. To say that there's a, you know, sort of one, you know, magic bullet of differentiation is quite hard to achieve. I mean, we think about differentiation in sort of three groups really. The one is being differentiated as part by being part of IBM. You know, when I first came into IBM, I wouldn't have pulled that out. I think now, I mean, that's really important. The way it is most important, I think, is if you wanna do really big, complicated end-to-end transformation, possibly with a global footprint, there are really only two players in our marketplace that you would think about, which is Accenture and ourselves.
Whether that's the big, you know, cloud, you know, modernization and migration that we're doing for Delta, whether it's the global SAP implementations that we're doing, in that category of work, Brian, it's really only us and Accenture. Being part of IBM, you know, really helps us in that context because of, I mean, not only IBM's brand, but also the financial buyer power that IBM has, but also the technology debt that IBM has. That's really why clients, you know, are looking to choose us in that space. Elsewhere, I think to your point, you know, we also benefit by being part of IBM, to be able to use and to leverage IBM's technology.
The best example of that is Red Hat, where we've built up a business that is now over $2 billion in terms of revenue, so that's, you know, just about 10% of our business overall. We've had $8 billion of signings in Red Hat since the acquisition. that's an area where we've leveraged, you know, IBM's technology to our advantage. We've got 15 other practices, you know, ranging from Maximo, TRIRIGA, mainframe modernization and so on. I think that being part of IBM is an important differentiation. Second part of our differentiation, you know, particularly against some of the other players in the marketplace, is our industry expertise. We have deep industry expertise, and that's recognized as such across the piece.
That along with, you know, our understanding of clients, enterprise clients, particularly where we've been doing application management for them for many years, means that we have a really good understanding of what their businesses are. The last piece, and the piece of differentiation that I think is probably the closest that we have to unique differentiation, is how our clients experience us. We have an approach to our work called IBM Garage, which is where we bring clients together in either a virtual or a physical environment with some of our technology, and we actually co-create Minimum Viable Products and then co-execute those, scale them up really quickly. We did nearly 7,000 of those last year. They have a very high NPS score.
We had some independent research done by Forrester actually that said that, you know, these, this approach drives 10% more innovative ideas, gets you to market 70% quicker, and it brings 6 times more of those projects into production than otherwise. I think that experience, how you experience working with us is a really important part of that. Being part of IBM, our industry, expertise and how we understand clients, and then Garage and how you experience us, that's what we think about in terms of our differentiation.
Great. Super helpful. Maybe a conversation with IBM couldn't be complete without mentioning AI.
Yeah.
Maybe we'll shift over to AI and generative AI. You know, beginning with the broader view of AI first, how are you helping clients leverage artificial intelligence today?
I do wanna split this into two really, and maybe we come back to generative AI.
Sure.
Because I think it's important to recognize that, you know, as I said earlier, Arvind called, you know, AI as a critical area three years ago, yeah? That's really because, you know, we see for clients this is absolutely essential to their competitive advantage. I mean, being able to do more for less, how you are able to drive that innovation, productivity scale, that's really important, as well as the size of the market. I mean, even before generative AI, you know, analysts like IDC were saying this is gonna be $35 billion growing to $65 billion. It's a really big marketplace. It's really important. We've had a big capability here for a long time.
We've got, 21,000 of our 160,000 odd, you know, consultants are in that data and AI space. We've done 40,000 odd engagements. Really, I think, you know, our focus has been around four areas. One is customer care. A good example would be the Veterans Administration, where their claims processing. How do you speed that up? How do you ensure that they can, you know, analyze and ingest all those documents really quickly and come to a decision, you know, much faster? We help them with some, actually some IBM technology, but running on AWS that's now got a 93% extraction accuracy and has really brought that whole decision-making process down from 20 days to one. That's a really good customer care example.
If you looked at, you know, process operations, TD Ameritrade, 15 processes around how their customers, you know, make margin trades or inquire about their accounts. We've really been able to use a lot of AI assets to reduce the time for processing, you know, really quickly there. In IT operations, J.B. Hunt, a transportation player, you know, we've used automation assets to help them manage their multi-cloud environment. You know, sports tournaments, Wimbledon's coming up. They take over 200 million security events, you know, over the course of a tournament, and we would help them with that. You know, I think we've been in this space for a while, and, you know, we've got a deep understanding of how clients will use that.
Of course, we've got generative AI that I think is gonna tip the scale of how they're gonna use it.
Yeah. maybe getting onto that point in terms of, you know, generative AI. You know, several weeks ago, IBM launched watsonx to assist enterprises with leveraging generative AI in a safe, secure, and private manner. Could you give us an overview of watsonx and what that means for not just IBM Consulting, but IBM overall?
Yeah, look, I mean, what watsonx is it's an enterprise-ready tool set that uses trusted data in order to accelerate the building and deployment of machine learning and foundation models. It comes in sort of three segments, if you will. There's, you know, watsonx.ai, which is the tool set and the studio. There's watsonx.data, which think of it as a lakehouse that actually enables you to access not only trusted data, but also to throw a fabric over the rest of your enterprise data. There's watsonx.governance, which is, you know, the protocols about how you know, bring all this together.
What I think is interesting about it, Brian, is that, as I think about today's IBM, so I'm talking about big IBM now, not just IBM Consulting, I would say the differentiation is it's open, deep technology, and I think we have a brand that is recognized for taking a very principled stance to the introduction of new technology. I think you can see all of those elements coming through in what we're bringing forward in this, you know, watsonx suite. In regard to the first of those, I mean, this is gonna be one set of tooling that you can use anywhere, on-prem, on anyone's cloud, that will actually enable you to, you know, to run anywhere to build those models and to drive that data.
We are very strongly of the view that this has to be multi-model on multi-cloud, and that a platform that we're offering here is only as strong as the ecosystem that it enables. Hugging Face, for example, are gonna be a big, you know, part of this. We'll bring other partners into it. I think this, you know, watsonx suite, you know, this watsonx suite is clearly open. In terms of technology, we're really shifting now from large language models to the really deep foundation models. We're bringing, you know, into, you know, this, you know, capability, the first of those foundation models, or that family are gonna be around geospatial, IT events, and chemistry. Thirdly, around integrity, you know, you've gotta have trust embedded in all of this system.
You know, we're bringing in protocols around how you explain how the data has worked, you know, how you can be confident about the integrity and so on. I think that's very exciting for IBM. In terms of how we're gonna exploit it in IBM Consulting, well, we've announced a 1,000-person COE. We're gonna build a watsonx business. We're gonna do that in the same way that I talked about Red Hat. In the same way that we built a Red Hat business, you know, we're gonna build a watsonx business within IBM Consulting. The critical thing that I would want to say here, however, is that when we built the Red Hat business, at the same time as we built that $2 billion Red Hat business, we also built this $1 billion AWS business.
We also built this $1 billion Microsoft Azure business. This is not gonna be, you know, student body left, you know, total focus on, you know, on watsonx. We will drive a watsonx business at the same time as we in IBM Consulting take advantage of the, of the other technologies that partners may bring to the market.
Great. I think you touched on this a little bit, but I wanna kinda emphasize that, you know, one of the things we look at in a software space is platform versus product. I thought your platform approach to Watson was really interesting, or watsonx, was really interesting. I guess on that, you know, what's your perspective of the importance of building a platform more focused on foundation models with cleaner data rather than a large master LLM model with greater volumes of data? You know, perhaps, I don't know if your customers are addressing some of the shortfalls around, I know there's a governance segment of the-
Yeah, look, I mean, I think, I mean, you know, the choice here at the moment is between, you know, models that have trillions of, or 1 trillion, you know, data elements that are less curated than models that, you know, foundation models that, I think this is where IBM is placing its emphasis, that may only have 100 billion of data elements, but which are much more curated. I think what's critical here for business is confidence around the quality of the data, the amount of bias and so on and so forth. That is... I mean, that is the fundamental issue, I think. We in IBM have always been super focused on enterprise.
What I would say is that at the moment, to your point about what clients are seeing, I'd say at the moment, clients are experimenting with both types, the broader models and the more you know, narrow. They're only experimenting with the broader models where they're really confident of that their data is gonna be protected, but they are experimenting with both. What we see at the moment though, is that they, when they are starting to think about how they might go into production and scale, then they're shifting much more towards the narrower foundation models.
Mm.
I'll give you an example. I mean, where it is more complex for an enterprise, they need to rely more on these narrow foundation models. Think of three or four use cases. Where you're gonna use AI to support employee productivity, for example. You wanna put somebody alongside an HR professional. That's gonna be a more a deeper foundation model. Where you wanna create a new experience, you know, like we did at the Masters, where we generated AI commentary for all of those, you know, golf shots. That sort of new experience, you're gonna want a more narrow, focused, curated foundation model. Where you as a legal business, for example, might want to not only change how your own organization operates, but disrupt the industry, you're gonna want a narrower foundation model.
Where you're in co-creation, perhaps, then a broader model may be more appropriate. I think enterprise focus is gonna be more on those narrower foundation models. That's what we're seeing. That's where IBM is putting its emphasis. We're putting our emphasis there not only because of our focus on value and our focus on value for enterprise, but also for innovation. 'Cause when you look at what the open source community's doing and where all the innovation is at the moment, it's at the moment on those narrower foundation models. We're into that space because of where we think enterprise is gonna go, but also because where we think the innovation's gonna come from.
Excellent. Thank you for that. I guess next, you know, IBM built its strategy around, you know, as you mentioned, hybrid cloud and AI, and we just spent some time on AI, so maybe to pivot to hybrid cloud. What are some of the main challenges clients are facing as they evaluate moving applications and processes to the cloud, and how is IBM supporting clients' cloud strategies?
Look, I mean, I think, you know, in cloud, our experience, and if you think about how you would, you know, characterize IBM's clients, our enterprise clients, you'd say that what actually holds them together is the fact that they all drive mission-critical operations. Whether that's in financial services, telco, government, healthcare, that's the characteristic I would say that, you know, that, you know, that our client base has in common. What we have found with those enterprise clients is that for them, a simple hop to the public cloud is just not an option, for reasons of data security, for reasons of the complexity of the, you know, the large, you know, application engines that they run. The cost of actually, you know, starting to split those out and to move them over.
Let alone the Frankenstein's monster of starting to see different skill groups and tribes building up within your operating model serving different clouds. For all of those reasons, we see those clients thinking that a hybrid cloud architecture, and by that I mean a single fabric that sort of runs across an on-prem environment, private cloud, and multiple public clouds, that is the architecture that our clients are increasingly focused on. We in IBM think that we're really well placed, you know, to serve that because we have that architecture in the, in the Red Hat stack. I mean, that combination of Kubernetes and Linux and containers that Red Hat offers.
That can provide that hybrid cloud architecture and fabric that allows you to build your applications once, deploy them anywhere, to skill your people once in that fabric, and then use them anywhere. Most importantly, perhaps to innovate anywhere with anyone's technology. That's what IBM is focused on in this space. What we in, you know, IBM Consulting are focused on, is actually helping clients to take advantage of, you know, of cloud in that sense. A really good example would be Delta, you know, where we are, you know, migrating and modernizing their applications to move to an AWS cloud platform. It actually uses Red Hat OpenShift on AWS ROSA. Domain by domain, moving, you know, those, you know, those applications to the cloud.
As importantly, Brian, not just the, you know, the technical part of it, but also reskilling and reschooling, you know, their IT operations team into how they will work in Agile squads going forward and how they will now work in a new cloud environment. I could give loads more examples, but that's the sort of thing that, you know, that we, you know, that we do within the cloud space.
Right. Excellent. Maybe just, you know, a macro-related question? Given the changing macro environment and the demand environment that you cited, from a productivity perspective, what is IBM doing to drive better productivity within the consulting business?
I mean, I guess there's a couple of, you know, things in there. I mean, the one is, you know, what we're doing to improve, you know, our margins, frankly. Yeah. I mean, I'd cite three things there. The one is price. so you know, we're doing, you know, we've done a lot of work to ensure that we're taking advantage of all of the, you know, cost of living and other provisions within our existing contracts. Also leveraging the, you know, what I call the balance, you know, between the value that we create for our clients and the reward that we get. We run a lot of Net Promoter Score surveys.
Mm-hmm.
Really therefore saying, if we're getting a high Net Promoter Score, and you're really valuing what we're doing, but the reward is not, you know, what it's like, how are we gonna balance that out? Those conversations, I think, have been very productive for us in the last 18 months. We're doing a lot on pricing. From a labor point of view, in a consulting business, it's really about ensuring that you've got a really strong pyramid that you've got, 'cause most of your money's made by utilizing your more junior people for as much time as you can. We've been working to ensure that our pyramids are in line. Thirdly, just the heavy lifting around utilization.
The last thing I'd say is that, you know, we're very focused on how we deliver to our price cases, which is how we make sure that the quality of the work that we do actually, you know, and the price case that we set out with actually gets delivered with our clients. Those are the things that we do from a margin point of view. In terms of how we, you know, if you will, is it cobbler's children? I can't remember, you know. How we actually apply AI to ourselves, then we're doing quite a lot of that, particularly in the HR space, where, for example, you know, we run our whole promotion process largely, you know, through watsonx Orchestrate.
Which means that all of the data, all of the preparation work is automated, and it's really only the final decision as to whether to promote or not that stays with the manager. That's been, you know, very helpful. Also a retention tool that has 95% accuracy, 'cause, I mean, we're a people business.
Mm-hmm
... you know, people's skills, where they're sitting, you know, you know, what's happened to them recently and so on. Then to be able to decide whether we want to intervene to keep them or not. Those are the sorts of productivity tools that we're using to, you know, to ensure that, you know, that we're, you know, always, you know, as efficient as we can make ourselves. Yeah.
Got it. maybe to shift real quick to M&A. I mean, Arvind's mentioned the significant amount of firepower that IBM has. you know, I think they cited, the management team cited, you know, kind of a 2/3 software, 1/3 services target model for M&A. What do you think the most likely target profile would be of companies that you might acquire?
In terms of target profile, I mean, to go back to what we talked about earlier, and those growth platforms. I think the first thing is, you know, are they capabilities that are gonna fall into those growth platforms? Cloud, intelligent workflow, security. Will they help us with particularly with our strategic partnerships? Then also, you know, you put, you know, across that, you put a market lens. For example, we've identified federal as a market that we want to invest in, and we recently bought Okta.
Mm-hmm
... you know, which is a technology and services company in federal, which really helped to, you know, to build our capability there. That's how we look at it from a consulting point of view. Across all of our acquisitions in IBM, there are really three questions. I mean, does it fit with strategy? Is it gonna generate synergy across all of IBM? Whether this is a technology acquisition or a consulting acquisition, we expect it to reinforce, you know, either side. Then, you know, is it gonna be cash accretive in a reasonable amount of time? That's how we've, you know, thought through that.
Great. Maybe last question for you, maybe just to wrap it up. What are you the most focused on that is key to the continued success of IBM Consulting?
Well, I think, you know, in terms of what, you know, we've talked about earlier, come as no surprise to say ecosystem and maintaining this open-
Mm-hmm
... you know, approach and therefore ensuring that we can, you know, leverage, you know, partnerships. I think taking advantage of, you know, technology disruption in the market, of which the, you know, the present cause célèbre is generative AI. I mean, we've gotta carry on executing. The last thing, you know, I think it's really important to remember in a consulting business, it's all about people. One of the things that we are trying to stay very focused on is engagement. Because hanging on to your talent is really, really important, you know, if you're gonna progress as a business.
Right. Excellent. With that, I think we're out of time. John, thank you very much for joining me.
No problem.
Appreciate it.
Yeah.
Thank you everyone in the audience as well.