IBM [IBM] Conference call transcript for 2023 q2
2023-07-19 21:00:20
Fiscal: 2023 q2
Operator: Welcome, and thank you for standing by. At this time, all participants are in a listen-only mode. Today's conference is being recorded. If you have any objections you may disconnect at this time. Now, I will turn the meeting over to Ms. Patricia Murphy, IBM's Vice President, Investor Relations. Ma'am, you may begin.
Patricia Murphy: Thank you. I'd like to welcome you to IBM's Second Quarter 2023 Earnings Presentation. I'm here today with Arvind Krishna, IBM's Chairman and Chief Executive Officer; and Jim Kavanaugh, IBM's Senior Vice President, and Chief Financial Officer. We'll post today's prepared remarks on the IBM Investor website within a couple of hours and a replay will be available by this time tomorrow. To provide additional information to our investors, our presentation includes certain non-GAAP measures. For example, all of our references to revenue and signings growth are at constant currency. We have provided reconciliation charts for these and other non-GAAP measures at the end of the presentation which is posted to our investor website. Finally, some comments made in this presentation may be considered forward-looking under the Private Securities Litigation Reform Act of 1995. These statements involve factors that could cause our actual results to differ materially. Additional information about these factors is included in the company's SEC filings. So with that, I'll turn the call over to Arvind.
Arvind Krishna: Thank you for being here. Our second quarter results reflect continued solid execution of our hybrid cloud and AI strategy. We again had strength in our growth vectors of software and consulting and solid cash generation, consistent with our financial model. Clients and partners continue to view technology as a source of competitive advantage. Clients turn to us to speed up their transformation journeys, modernize applications and optimize their business workflows. At the same time, they continue to prioritize projects that focus on productivity and deliver quick time to value. To seize this opportunity, we are bringing new innovations to market, expanding strategic partnerships, and making investments in targeted growth markets, while unlocking value through our productivity initiatives. All of this gives us confidence in our ability to achieve our full-year expectations for revenue and free cash flow, which remain our two primary areas of focus. We've made progress in our strategy around hybrid cloud and AI, the two key drivers of business innovation. Hybrid cloud is the most widespread form of IT architecture. Red Hat OpenShift, our leading container platform based on open-source innovations plays a crucial role in making this possible along with IBM software and infrastructure. Our consultants use their technical and business knowledge to speed-up clients' digital transformation journeys and help drive adoption of our technology platforms. Our broad ecosystem of partners amplifies our reach and ability to meet client demand. Let me highlight a few collaborations from this past quarter that take advantage of our platform-centric approach. We're helping Air Canada, improve its digital footprint, including their website, mobile application, and loyalty program. Using a hybrid cloud approach helps Air Canada better connect and tap into their commercial, operational, and financial data. With Diageo, IBM Consulting embarked on a large global digital transformation to improve customer satisfaction, optimize business workflows, and enhance its financial performance reporting capabilities. We also forged a strategic partnership with Nokia, where Red Hat OpenShift becomes the preferred platform provider to Nokia's core network applications business. This past quarter, we made strategic moves to bolster our hybrid cloud and AI capabilities with the announcement of our plans to acquire Apptio, which offer the virtual command center for CEOs, CFOs, and CIOs to manage their technology investments. Apptio’s offerings combined with IBM's IT automation software and our AI capabilities, will give clients the most comprehensive approach to optimize their IT environments. AI is a transformative technology that has the potential to unlock tremendous business value. According to a recent McKinsey study, AI could add up to $4.4 trillion annually to the global economy. Our focus is on enterprise AI, designed to address these opportunities and solve business problems. The list of use cases is long and includes IT operations, code generation, improved automation, customer service, augmenting HR, predictive maintenance, financial forecasting, fraud detection, compliance monitoring, security, sales, risk management, and supply chain amongst others. AI is being infused into our software products. We are already building products that address specific enterprise use cases such as digital labor with Watson Orchestrate, customer service with Watson Assistant, and co-generation with Watson Code Assistant. And our Think Conference in May, we announced what's the next, our enterprise-ready AI and data platform to help clients and partners, capitalize on the AI opportunity. Watsonx delivers the value of foundational models to the enterprise, enabling them to be more productive. We began to rollout watsonx, a little over a week ago and we are excited by the client response. To-date, the platform has been shaped by more than 150 businesses across industries from telco to banking. Businesses around the world are excited about tapping foundation models and machine learning in one place, with their own data to accelerate generative AI workloads. For example, Samsung is exploring generative AI to deliver unprecedented innovation for clients. Citi is pursuing the potential use of large language models for connecting controls to internal processes. NatWest is embedding watsonx into its chatbot to improve customer experience and SAP is integrating IBM Watson AI into their solutions. IBM is also working with an expanding ecosystem of partners to co-create and innovate across industries and use cases from space to sports, including work with NASA to build the first foundation models for analyzing geospatial data and Wimbledon, where watsonx was used to produce tennis commentary. Large language models are a step-change in the evolution of AI, with more than 80% of enterprises exploring their use. We believe the opportunity for large language models for enterprises is immense. Given the existing amount of business data, this includes sensor data, chemistry data, material data, geospatial data, code, and of course, speech. Because enterprise AI draws from both public and private data, it is more effectively trained and companies adopt a hybrid cloud approach. Enterprise AI can also be based on multiple models, including public, private, and open-source. Our watsonx platform takes into account this reality and is differentiated in a few important ways. For instance, instead of relying on a single model watsonx enables companies to leverage the best models to meet their needs, whether they are open-source technologies, IBM's models, or those co-created with us. Another fundamental aspect of watsonx is trust, ensuring transparency and bias free models. In addition, beyond offering companies the capability to tap into existing AI models, IBM empowers them to create their own. To help clients on this journey, we have over 20,000 data and AI consultants and recently launched our new Center of Excellence for generative AI, already staffed with more than a 1,000 consultants with specialized generative AI expertise. The investments we're making in products and skills will help us to seize the AI opportunity. Our path is clear, in the same way we have built a consulting practice around Red Hat's hybrid cloud platform, that is now measured in the billions of dollars, we will do the same with AI. And just like OpenShift is the technology platform at the heart of our hybrid cloud capabilities, watsonx will be the core technology platform for our AI capabilities. Watsonx is just one of many new technology innovations. Shortly after previewing watsonx at our Think Conference at the Red Hat Summit, we introduced OpenShift AI, which is a unified solution to train, serve, monitor, and manage the lifecycle of AI models and applications. We also unveiled IBM hybrid cloud mesh, a SaaS solution that streamlines application-centric connectivity for edge, hybrid, and multi-cloud environments. To help clients with their sustainability agendas, we launched our AI-powered cloud-based tool that helps clients track their greenhouse gas emissions for cloud workloads. And as an example of how we continue to push the boundaries of innovation, IBM recently demonstrated using error mitigating techniques, quantum computers can produce results at a scale of 100-plus cubits. This is a significant breakthrough that firmly puts us on a path towards building practical quantum computers that can solve hard problems in areas such as risk, finance, and materials. Let me conclude by reiterating our confidence in our strategy and execution. It is clear that the work we have done to better align IBM to the needs of our clients is paying off. The momentum in our business and continued focus on productivity, position us to achieve our full-year expectations and deliver sustainable revenue and free cash flow growth. With that, I would like to hand it over to Jim who will delve deeper into our performance and expectations.
Jim Kavanaugh: Thanks, Arvind. As always, I'll start with the key financial highlights of the second quarter. We delivered $15.5 billion in revenue; $2.4 billion of operating pretax income; $2.18 of operating earnings per share and through the first-half nearly $3.5 billion of free cash flow. In the second quarter, we had modest revenue growth at constant currency, and that includes over 1 point of impact from the businesses we divested last year. Currency rates continue to be a headwind to growth with dollar strengthening over the last 90-days; currency impacted our reported revenue growth by 80 basis points, which is about a 0.5 point worse than what spot rates suggested in April. As is typical, I'll focus my comments on constant currency. Revenue performance was again led by software and consulting. These are growth factors that together represent about three quarters of IBM's revenue and contribute to a solid base of recurring revenue and profit. Software revenue was up 8% with good growth across both, hybrid platform and solutions, led by Red Hat and Data & AI and Transaction Processing. IBM Consulting revenue growth of 6% was also broad-based, with growth across all three lines of business and geographies. Our infrastructure revenue in any quarter reflects product cycle dynamics. Infrastructure revenue was down 14%. This, as expected, had a disproportional impact to IBM's overall revenue growth this quarter, given the very successful launch of z16 in the second quarter last year. Looking at the two-year compounded growth rate, infrastructure revenue was up. Turning to our profit metrics, operating gross margin expanded 140 basis points, driven by our portfolio mix and productivity. We had good performance this quarter with gross margin improvements in every reportable segment. Our operating pre-tax margin was down 70 basis points. Last year we had a gain of about $230 million from the sale of our healthcare software assets. Without the year-to-year impact of the divestiture gains, our operating pre-tax margin was up 70 basis points. This is a better indication of our ongoing operational performance. Let me comment on a couple of items within our expense profile that impacted our pre-tax income performance. As we discussed in the last couple of earnings calls, we address the remaining stranded costs from our portfolio actions, resulting in a higher level of workforce rebalancing activity this year, about $115 million in the quarter. Workforce rebalancing impacted our year-to-year pre-tax margin expansion by another 60 basis points. And then currency remained a year-to-year headwind, not only to revenue, but also to our expense and pre-tax profit. The combination of translation and hedging impacted operating pre-tax profit growth by about $150 million and operating PTI margin by about 80 basis points year to year. As I've discussed in the past, this disproportionately impacts our product-based businesses. We have good momentum in our underlying operational profit performance. I mentioned a strong business mix, but we're also making progress on our productivity initiatives. We're digitally transforming IBM as Client Zero simplifying workflows, and deploying AI across our processes. From IT operations to HR to source-to-pay. The productivity benefits free-up spend for reinvestment and contribute to margin expansion. Turning to free cash flow, we generated $2.1 billion in the quarter and nearly $3.5 billion in the first-half. This first-half performance is up over $100 million year-to-year and keeps us on track to our full-year expectation. Growth is driven by the cash from our profit performance, working capital efficiencies, and lower payments for structural actions. This was mitigated by higher performance-based compensation payments, given last year's strong results and higher cash taxes. In terms of cash uses through the first-half, we returned $3 billion to shareholders in the form of dividends and spent about $350 million to acquire six companies. Later this year, we expect to close the acquisition of Apptio, which complements and advances our IT automation capabilities. From a balance sheet perspective, we continue to have very strong liquidity position with over $16 billion of cash that's down over $1 billion since March, and up $7.5 billion since December. Our debt balance at the end of the second quarter was over $57 billion, which is up $6.5 billion from year-end. You'll recall earlier in the year, we were opportunistic in accessing the debt market and issued debt to prudently get ahead of 2023 and 2024 maturities, as well as capital allocation priorities. Turning to the segments, software revenue growth accelerated to 8% this quarter. Both Hybrid Platform & Solutions and Transaction Processing grew, as clients leverage our hybrid cloud and AI platform capabilities. This performance again reflects growth across both our recurring revenue base, which is about 80% of annual software revenue, as well as transactional revenue. In Hybrid Platform & Solutions revenue was up 7%, fueled by growth in Red Hat, Data & AI, and automation. Our Hybrid Platform & Solutions ARR is now over $13.6 billion and up 7%, reflecting the importance of our strategic offerings with our clients. Red Hat revenue grew 11%. OpenShift, our leading hybrid cloud platform grew more than 30% in the quarter and now has $1.1 billion in annual recurring revenue. Ansible also delivered double-digit growth and gained market share this quarter. In automation, revenue was up 2%, reflecting growth across integration, application servers, and business automation. As clients drive enhance business value through productivity and performance optimization. Data & AI revenue was up 11%. The broad-based growth included areas like data management and business analytics, giving enterprise needs for data visualization, organization, analysis, and insights as the underpinnings for AI workloads. Security revenue declined 1%. We delivered growth in security software, driven by data security with Guardium Insights. This was more than offset by declines in security services this quarter. In Transaction Processing, revenue grew 10% off of an easier compare last year. The increase in zSystems installed capacity over the last couple of cycles and strong software renewal rates reflect the importance of zSystems platform in a hybrid cloud environment. These dynamics contributed to both recurring and transactional software revenue opportunity again this quarter. Putting this together with price increases, we had strong performance in transaction processing. Moving to profit for the software segment, our pre-tax margin was up by 0.5 point, while absorbing over 1 point of impact from currency. We delivered operating leverage, given both the revenue scale and mix this quarter. Consulting revenue was up 6%. In April, we discussed that we were seeing sustained demand for larger transformations that delivered meaningful ROI. At the same time, other projects considered to be more discretionary predominantly in the United States. The second quarter client buying behavior played out much in the same way. Our signings were solid, up over 20% with double-digit growth in both large and small engagements. This takes our book-to-bill ratio up to 1.1 over the last 12 months. We address continued demand for technology-driven transformations as clients prioritize projects that drive cost savings and increase productivity. Turning to our lines of business and consulting, growth across our service offerings was broad-based. Business transformation grew 5%, driven by data and technology transformations, including AI and analytics-focused projects. Digital transformations continue to be underpinned by clients embracing a hybrid cloud strategy. Technology consulting grew 5% and application operations grew 8%, as we again saw strength in cloud-based application services across development, modernization, and management. Contributing to growth across the business, our strategic partnerships grew signings and revenue double-digits with solid performance from partnerships with AWS and Azure. Our Red Hat practice also grew signings and revenue double-digits. We have an annualized revenue run rate in excess of $2 billion. Moving to consulting profit, we expanded both gross and pre-tax margins a 180 basis points. Our margin expansion is a reflection of the pricing and productivity actions we've taken, more than offsetting the increased labor costs and investments. Turning to the Infrastructure segment, revenue was down 14%, reflecting product cycle dynamics. This impacted both hybrid infrastructure and infrastructure support. Within hybrid infrastructure, the zSystems revenue declined 30%. We've wrapped on strong revenue performance last year, up 77%, when z16 launched in the seasonally strong quarter. Through the first five quarters of availability, revenue is well ahead of prior cycles. The z16 brings the power of embedded AI at scale, cyber resilience security, and cloud-native development for hybrid cloud to our clients. For example, clients are adopting IBM's z16 and the Telum processor as the foundation for real-time AI insights across significant volumes of data. Distributed infrastructure revenue was down 6%. Let me remind you, we are wrapping on strong growth last year, up 17% driven by strength in Storage and Power10 high-end systems. Moving to infrastructure profit, we expanded gross margins 200 basis points, while pre-tax margin was down 40 basis points, including about 1 point of impact from currency. Now that I've gone through the segment results, let me bring it back up to the IBM level to wrap up. We feel good about our first-half performance, with momentum in our growth vectors of software and consulting and a solid recurring revenue base driven by our high-value software. We're delivering strong gross margin performance, with growth across our segments driven by portfolio mix and productivity. Our overall year-to-year profit dynamics as expected reflect the impact of last year's divestiture. As we look to the full-year of 2023, we're holding our view of the year on our two primary metrics: revenue growth and free cash flow. We see constant-currency revenue growth of 3% to 5% and we expect free cash flow of about $10.5 billion, which I'll remind you is up over $1 billion year-to-year. Let me comment on a few items within these full-year expectations. We expect IBM's operating pre-tax margin to expand by about 0.5 point year-to-year, driven by a combination of product mix and progress on our productivity initiatives. That's consistent with our view 90-days ago and in line with our model. We're also maintaining our view of our tax rate for the year, which is in the mid-to-high teens range. And then finally, while there has been some volatility in currency rates over the last couple of weeks, at current spot rates, currency translation is still expected to be fairly neutral to our revenue growth for the year. I'll remind you that our profit and cash dynamics this year are impacted by the rap on last year's hedging gains, which is about 1 point of headwind to our pre-tax margin expansion. In terms of segment dynamics, in software, we had a good first half and now expect revenue growth at the high end of software's mid-single-digit model. This is all-in including acquisitions. Our revenue growth drives operating leverage with software pre-tax margin expected to expand 1.5 points to 2 points year-to-year. In consulting, we’ve reposition our business to address today's clients' needs. What we saw in the second quarter didn't change our view of the year. We continue to expect consulting revenue growth in the range of 6% to 8%. And to expand consulting pre-tax margin by at least 1 point. And then for infrastructure, as I described in the past, revenue is roughly flat over the mid-term model horizon, with performance in any year reflecting product cycle dynamics. In the second quarter, we have wrapped on the z16 introduction in a seasonally strong quarter. For the year as you expect 2023 infrastructure revenue will decline, impacting IBM's overall revenue growth by over 1 point. We continue to expect pre-tax margin in the low-teens. Our expectations for 2023 reflect a higher-growth, higher-value business with strong cash generation, what we have referred to as today's IBM. The analysts' estimates also reflect these dynamics. And as we look at the third quarter, the average of analysts' estimates looks reasonable. In closing, we are pleased with our first-half performance and it keeps us on track to deliver revenue growth, expand margin and grow free cash flow for the year. I'm happy to provide more color on the quarter and our expectations in the Q&A. Patricia, let's get started.
Patricia Murphy: Thank you, Jim. Before we begin the Q&A, I'd like to mention a couple of items. First, supplemental information is provided at the end of the presentation. And then second, as always, I'd ask you to refrain from multipart questions. Operator, let's please open it up for questions.
Operator: Thank you. At this time we'll begin the question-and-answer session of the conference. [Operator Instructions] Our first question is from Wamsi Mohan with Bank of America. You may go ahead.
Wamsi Mohan: Yes, thank you so much. Arvind, you noted some initial traction around AI and I was wondering, you guys have made a lot of major announcements around AI. I'm wondering if you can share some thoughts on AI monetization in the short to medium term. And any quantification if possible, either in terms of dollars or growth rates over ‘23 and ‘24, would be helpful? And if I could, Jim, you saw very strong transaction processing growth, you noted a few different items there. I was wondering if you could talk about how much of that is structural versus cyclical. And if transaction processing is growing this fast, does that drive upside to software revenue for the year? Or are there other areas that are offsetting? And if you could just reiterate, if Red Hat, you still expect that to grow 11% to 13%? Thank you so much.
Arvind Krishna: Wamsi, so thank you for the question. And as you noted, I'm very excited by our progress on AI, and what is going to do for our clients most importantly and then return of course for us as we monetize it. Our monetization is largely going to be through consulting and software and I'll explain that. Infrastructure will benefit, but I would not call that a direct monetization route. So let me start with consulting. If you noticed, I talked about and Jim talked about what we have done with hybrid cloud aka OpenShift in consulting, where we began with this journey in 2019, our book of business was to be precise and to round it out zero. In the first year, we signed about $1 billion of business. And at this point, we have inception to-date signed $9 billion with an annual run rate of $2 billion in consulting. I would tell you and expect that we'll play out AI in a similar way. I hesitate to call it anything else until we get six months or so down the road, in which case then we'll have more knowledge. Now on the software side, we are very, very excited by the initial reaction to the watsonx platform. the number of projects we have going on, the client interest, it really is something which we are very, very pleased by. So what's the model to think of it on? As I think about how OpenShift, which was a Red Hat product came in, in 2019, it grew literally doubled each year for the first four years. And at this point, the revenue is about 10 times of what it was and it came in. And right now we have quantified it at $1.1 billion on our annualized run rate basis. So that gives you a sense of the excitement we have around these projects, these technologies, and what it could do for us as you begin to go forward. Now third and most important, but I don't want to quantify it is the fact that AI will infuse in models every single product we have, whether it's sustainability, whether it's our database products, whether it's our consulting projects, whether it's inside the mainframe of the Telum. But I'm not including those in those first two categories. So with that, let me give it to Jim for the TPs question.
Jim Kavanaugh: Thanks, Arvind. And thanks, Wamsi, for the question. We're obviously very pleased with our overall software performance here in the second quarter accelerating to 8% at constant currency and was pretty pervasive, both acceleration in the hybrid platform and solution. And to your question, transaction processing. But you get underneath the performance double-digit in Red Hat, double-digit in Data & AI, and double-digit in our high value transaction processing business overall, which by the way gives us the confidence exiting first-half to raise our guidance and software overall to the high-end of our mid-single-digit model. Now to your question about transaction processing. We constantly talk about on these calls, the value of TP in our business model. It's a value vector 30% of software, the tremendous source of profit and cash that gives us financial flexibility to reinvest for growth overall. It also provides a tremendous incumbency position for our IBM multiplier effect. We entered the year, Arvind and I talked about we saw the inflection shift in TP in ’23. And that was predicated on the successful mainframe programs that we've had over the last two. By the way, the last program were up 2 times our installed MIPS capacity. So we have a much more extended opportunity base to go get those strong renewal rates overall. But we said from a model perspective, we saw the inflection shift versus being down mid-single-digit, which is a tremendous drain on us, we saw low-single-digit growth. Now on top of that, just given the highly inflationary environment, we talked about we were going to get disproportional price in ‘23. Call that, I don't know, 2, 3, 4 points somewhere in that ballpark. So when you look at our first-half performance, our first half were up 8%. By the way, our first-half last year was relatively flat. It's our easier compare. So we have to acknowledge it's easier compare. We're going to enter a different -- more difficult compare in the second-half. But that 8 points of growth overall, I would say, once you normalize for the easier compare, we can grow low-single-digit on a sustainable basis. This year, just given the differentiated price position, we said we'd grow mid-single-digit. We feel very confident exiting first-half.
Patricia Murphy: Thanks, Wamsi. Let's go to the next question, please.
Operator: Thank you. Next question is from Amit Daryanani with Evercore. You may go ahead.
Amit Daryanani: Yes, thanks for taking my question. Yes, I guess, I was hoping you could spend a bit of time on the consulting side and the growth did decelerate there a little bit from 8% in Q1 to 6%. I'd love to understand how does that 6% growth in consolidated Q2 stack up versus your internal expectations? And then given the deceleration we saw in June, maybe just talk about what gives you confidence that the growth rate holds up, and that's 6% to 8% range for the back half of the year when some of your peers have actually talked about that market decelerating a bit? Thank you.
Jim Kavanaugh: Thanks, Amit. I'll take this one. We're actually pleased with our consulting performance. You remember you dial back 90-days ago and we saw a real change in buying behavior, particularly in the United States around discretionary project-based activity that slowed down in the month of March and that impacted our backlog -- realization in the quarter. But we've actually posted relatively strong growth, 8% in the first quarter, we had mid-teens, if I remember correctly signings growth. When we look at second quarter, we have not seen any substantive change in client buying behavior at all. So I think that's actually a positive indicator. We didn't see it, permeate across other markets around the world. Clients like us, internally I'm focused every single day, I'm getting productivity cost, quick payback ROI and our clients are looking at that. But on top of that 6% growth here in the second quarter, I think it should be noted, we delivered very strong signings growth that was pervasive both large deal, small deal. So we see continued momentum where client demand is there, where there is a value to clients, overall. And how we differentiated ourselves and I would argue we're gaining share. We grew 24% in signings in the second quarter. And that was driven by areas that you would quite expect around digital transformation, application, modernization, data and technology, AI by the way, grew 50% signings in the first quarter. So to Arvind's opening valley about AI and how we're going to monetize, this is early green shoots on some of these things. So we exited the quarter with about 1.1 book-to-bill, by the way, that's the strongest book-to-bill we've had in quite some time. Now that positions us well for the second half. We got very good strategic partnership velocity, we got very good Red Hat book of business growing strong double-digit. But we're going to continue to monitor this client buying behavior on backlog realization. That's the critical piece. And by the way, our erosion we have not seen any change or inflection shift in erosion. So we're positioned well for the second-half and that gave us confidence in our 6% to 8%, maintaining guidance for the year.
Patricia Murphy: Thanks, Amit. Let's take the next question, please.
Operator: Thank you. Next is Toni Sacconaghi with Bernstein. You may go ahead.
Toni Sacconaghi: Yes. Thank you. I just wanted to clarify, when you talked about feeling comfortable with Q3 estimates was that both the revenue and an EPS statement? And then my question is on software, I think you were looking for 200 basis point margin improvement for the year and now you're saying 150 to 200. Can you speak to that? And also when we look at the improved software revenue growth, is that just improvement in transaction processing because you're way above your forecast in Apptio or is there something beyond that? And related to that, are you modeling any substantive revenue from AI and consulting or in software this year? And why would that not impact your outlook if you were? Thank you.
Jim Kavanaugh: Hey, Toni, thank you. I'll take the first two or three or four of your questions and then I think Arvind can talk about the AI piece overall. But when you look at our software margin overall, first of all, we're taking our full-year guidance up on revenue to the high-end of our model. So that's about 1 point raise year-over-year and by the way that's all-in, as we stated in prepared remarks, including how we're very excited about the Apptio acquisition, overall. But that raise in guidance I think is a reflection of the pervasive performance we've seen in the first-half that we feel pretty confident in. We enter let's dial back, we entered the year, we said, mid-single-digit, we were coming off of PKLA, we said, we get 5 to 6 points of growth out of annuity, and we would have about a 1 point headwind on transactional. We had a pretty solid first quarter delivering above our model. We continued and accelerated that in the second quarter. And by the way, it's both transaction processing, hybrid platform and solution overall. So when you look at it, we see one, yes, Apptio, very excited. It's a high-growth company, high recurring revenue, and a highly profitable company. And we expect just given normal customary regulations of closing, we probably assume sometime early fourth quarter. So that's about 0.5 point of that raise. The remaining 0.5 point is going to be solid mid-single-digit growth on TP to my answer to Amit. And then third is we actually exited our first-half with very solid transactional growth, albeit we do understand we're going to wrap in fourth quarter on a very strong ELA cycle. But the first-half, we're seeing very strong clothing upsell that's in the mid-20% year-over-year on those expiring ELAs through the first-half. So I think it's all three pieces overall. I think, I covered both the revenue piece on the margin, Toni. That is really just the dilution effect in the first quarter of Apptio. So we called about 200 basis points for the year. Now we're putting Apptio in. We're somewhere between 150 basis points and 200 basis points. But I'll remind you, we expect a very quick accretive business as we go forward just given their profitable overall. So I'll turn it over to Arvind on the AI.
Arvind Krishna: Yes. Thanks, Jim. So Toni, I'll comment quickly on the color on revenue from AI, both in software and consulting. So as I said, in consulting, we are expecting a number of projects to get signed. By the way, as Jim mentioned, some of that is getting baked in. And you're seeing that in the strong signings that we have in consulting in the second quarter with the over 20% growth in signings, and a lot of that was indeed data and AI consulting projects. Ditto in software, I'd just note that we had double-digit growth in the data and AI subsegment of software, and no doubt that some of that is colored by clients doing more around AI with us than they have historically. So we expect to see it. But I do want us to be sort of all in, all in with 2023, including the AI color. We see software at the high end of our model, and we see consulting as in the range that Jim just laid out. So while we are very excited about it and we see a lot of traction on AI, it is included in the estimates that we just gave.
Patricia Murphy: Thanks, Toni. Let’s go to the next question, please.
Operator: Thank you. Next question is from Shannon Cross with Credit Suisse. You may go ahead.
Shannon Cross: Thank you very much. Arvind, I'm wondering, can you talk -- and I know you haven't launched it globally, but I'm sure everybody is having conversations right now. What is the interest level and understanding of AI by geography? And how do you think that sort of plays out and rolls through? And then just as a follow-up to the commentary on Apptio. I wondered if you could talk a bit more about what were sort of the key drivers of that acquisition, what KPIs we should watch for. And then I'm also curious as to how the $450 billion of anonymized data that you're gaining with that. How do you think you'll leverage that within your foundational model? Thank you.
Arvind Krishna: Thanks. Shannon, great questions. So when I look at AI by geography, at one thought of simple level, I would tell you that over the last six months, the interest in AI spans across all markets, all industries. So it is a international phenomenon, not confined to the U.S. Now we've got to dig under it. Then if I look at the maturity of clients to actually have their enterprise ready to embrace AI to be able to interact with their clients, their employees, that does vary. I have to acknowledge it. The North American market is probably the most further ahead on this. I think Western Europe comes second, likely together with some of the more advanced and developed markets in South America. Following that then is Asia and all of what would we call the Global South. Japan has a strong interest, but they tend to be cautious on adopting technology, not necessarily in experimenting. In experimenting, they'll be pretty quick. And then it will go into South Asia, where always, I think technology adoption tends to lag by a year or two behind the West. So that gives you some sense of that. But that said, every government, every enterprise, every CEO, every CIO that I talk to wants to talk about AI, what it can do to their company, what should it be in their country. And all of the questions around sovereignty of models and data and privacy and not depending only on a few international players come into the conversation, and that's why we talk a lot about private models and models that can be left behind with the client, because that is coming up more and more. And so that, I hope, gives you some color on how this is going to play out. Coming to the next part of your question on Apptio. Look, the key drivers of this acquisition are pretty straightforward. When we look at and talk to CIOs, CFOs, CEOs, they're all getting worried about their spend across the hybrid landscape. What do I spend on my first public cloud? What is it on my second? What is it on a SaaS property? What am I spending on my own data centers? So to give people a virtual cockpit that really lets them span across this, not just in terms of the third-party spend, but also the people and the process spend, is something they're all deeply, deeply interested in. And more than a few CEOs I've talked to said it really gives them a handle on what's going on and where the money is being spent. That, I think, is going to play in right away. And you went right to the second value prop. With that spend data coming in across enterprises, the aggregate anonymized across the asset is the $450 billion. Now helping people benchmark, who does this better than you? Who does this process better? Who can do this with fewer total spend on a public or a private resource? It's interesting to people because benchmarks is a great way to guide oneself to better performance. We expect that over time, we'll be able to monetize that into a large language or a foundation model and be able to give people even better predictors or where they can take their spend, too. That's why we are so excited about it. And I think the last part of your question was KPIs. Look, as we look to get Apptio much more international, while our footprint is, I'll call it, maybe two-third, one-third outside the U.S. and in the U.S., they're almost inverse. So as we can put it into our distribution channel, that will be one big expansion as we go over the next year or so. The second one is we believe we have a great chance to also increase the penetration in our larger clients. So those are two big metrics while we continue the success in the growth rate they've had using their own channels.
Patricia Murphy: Thank you, Shannon. Let’s go to the next question, please.
Operator: Thank you. Next is Erik Woodring with Morgan Stanley. You may go ahead.
Erik Woodring: Good afternoon, guys. Thanks for taking my question. Arvind, I'd love to dig into how you guys are thinking about M&A today. Obviously, you announced the Apptio deal a few weeks ago. That largely probably takes transformational M&A off the table, but you obviously still have some additional dry powder to make other acquisitions. So maybe if you could talk about what your appetite is for further M&A. Are you thinking about any other end markets or solutions you target now? Is valuation becoming more restrictive for you? Maybe said differently, just what's your message on M&A today post Apptio? Thanks so much.
Arvind Krishna: Erik, so I might sound somewhat repetitive to those of you who have heard me over the past two years on this topic. So if I just sort of maybe just step back and say, taking unusual actions off the table for a moment, we had talked about a total Finflex let's call it, circa $20 billion over a three-year period. That includes the ability to raise additional debt if we so desired. We've been spending circa about $3 billion a year for the last couple. So that tells you what's the capability and the flexibility that we have. You asked about valuations, and I hope my answer that tells you that we are always on the lookout, and I'll get to which categories because you asked that also. On valuations, I wouldn't call it so much that today is restrictive. What I could say is that while some of at least the reports I was reading, we're talking about valuations perhaps coming down in multiples over this year. It doesn't seem that that's the case. They've not gone up in any, kind of, tremendous way, but they have not come down. But the market is what the market is. So if we find properties that meet our criteria, and my criteria are pretty straightforward. Doesn't align with our strategy, and I'll call those areas out in a moment. Doesn't actually give us synergy, meaning can we the combined entity grow faster than the individuals could before, right, just about it in very financial terms. And if it is larger, it has to be accretive. And by larger, I mean it's not a tuck-in, meaning it's not a few hundred million. It's larger than that, then it's got to get accretive, let's say, within two years at the latest. So if it meets those criteria, it's certainly an attractive proposition. The areas we are in, we don't want to open up more strategic lane, so to speak. Our areas are hybrid cloud, data and AI, automation, cyber and those consulting properties, which in turn help these. So that's kind of the lanes we're in. And if I look at the latest one, Apptio, I'd say it kind of hits three out of my four. It hits hybrid cloud because it helps you deploy those. It is a big data and AI property because that's what they use. And it is automation because it takes out human labor cost from many of those processes. So it was actually a very, very good fit. And if any of you have suggestions for similar things, we are all ears, and you can certainly write to me.
Patricia Murphy: Hey, thank, Eric. Let’s go to the next question, please.
Operator: Thank you. Next is David Grossman with Stifel. You may go ahead.
David Grossman: Thank you. Arvind, you spoke extensively about the favorable impact of pricing on the transaction processing portfolio. What have you learned from repricing that portfolio? And what other segments of your business could potentially benefit from similar actions? And sorry to violate the one-question rule. But Jim, I just want a clarification. My recollection is that you had about $500 million of working capital tailwind factored into the free cash flow guide. I just want to make sure I got that right and that's the same. Thanks.
Arvind Krishna: So David, let me address the first part of your question on pricing. Look, I'd like to be careful. TP certainly benefited this year, but the biggest part of the benefit has been the mainframe cycle and the capacity and value that our clients see. Yes. Was there a price increase? Given the labor inflation of 2022 and some ongoing in ’23, given the strong dollar, effectively, there was pricing increase, because of those factors, and that got taken well by the market, because of the value they see on that. Would I expect to see similar pricing on TP and then I'll come to other parts of both consulting and software? I doubt, David, that it will be on the same range because, definitely, I think we would all agree, ‘22 had a high inflation. And because our costs go together with the labor and the dollar, I don't think it will be as strong as that, but I would expect maybe moderate increases based on just the pricing in TP. Now consulting has also got both labor and inflation built in. And when we are seeing 6%, 8%, 10% increases in labor cost, it is, I think, appropriate to be able to pass some of that on, albeit with a lag. And you heard Jim talk in his prepared remarks about that, that is some of what is coming through in consulting. If there remains underlying labor inflation, I fully expect to be able to pass that on, again, with a bit of a lag to clients in consulting because, otherwise, that's not a healthy business to go on. I think on the rest of software, except TP, I would expect that as labor inflation is there, those elements do come in effectively on pricing, renewal rates and so on. But I'd also say it's a competitive market, and you have to remain competitively priced to where the others are. So I would say it's in those two: TP, consulting and then in other elements of the portfolio that pricing can play a role. By the way, our renewal rates are a very strong indication that these are portfolios that provide tremendous value to our clients, but we remain competitive on price.
Jim Kavanaugh: Yes. I mean our strategy overall has always been around pricing for value, right? But, David, just to put it in perspective, last year, we all dealt with a very -- and we're still dealing with a very highly inflationary environment that was somewhere anywhere, what, 3, 4, 5 points above history overall. That's kind of what we've been talking about is a disproportional price in ‘23. You're not going to get that every single year, to Arvind’s point, but I've always said pricing optimization is a direct correlation to the value and differentiation you offer to clients. You got to bring value to clients, or they're not going to accept the pricing. And we've been seeing good take-up with our mission-critical transaction processing. Arvind talked about the human capital-based business, the consulting, et cetera. But just quickly to wrap on your second question, David. We said entering the year, remember, we came off of December, where we had a shortfall leaving much more on the balance sheet and collected in working capital. Working capital for the year is probably somewhere around $400 million to $500 million, like you said, and that's a tailwind coming off of last year. The remaining piece of the $1.2 billion of free cash flow growth year-over-year is the fundamental improvement in the operating discipline of our revenue and operating margin and cash from profit.
Patricia Murphy: Hey, thanks, David. Let’s see if we squeeze two more in. Let’s go to the next question.
Operator: Thank you. The next question is from Keith Bachman with BMO. You may go ahead.
Keith Bachman: Hui, many thanks for the question. Arvind, I wanted to direct this to you, if I could. You've talked about the success you've had, even at these early stages of signing new AI offerings in the consulting side of the business? How are you thinking about the supply side of the business? And what I mean by that is, as you look at over time, the software development process, as you talked about that in Orlando, is going to become much more efficient. And so if your consulting business is really a seat-based model that drives revenue and if those developers are increasing productivity by, I don't know, 30%, 40% because it's gen AI, presumably, clients will want that back. So how do you think about the disinflationary forces associated with gen AI on delivery side of the model, which is, I think, separate and distinct from the opportunities associated with new demand sources? And Jim, if I just sneak one in to you, to if you could talk about the total MIPS growth, not just the cycle growth, but the total MIPS growth that you've recently experienced as we look out over the next couple of years. Just trying to understand what the pricing increase, how that may -- how you may be able to use pricing on TP to leverage that MIPS? That's it for me. Many thanks.
Arvind Krishna: So Keith, let me address the first part of your question. So if I look at it in the short-term, let's just walk through. What does the consulting team actually do? They spend a lot of time upfront with the business side going through business processes, worrying about how to optimize business processes, cutting across silos, coming up with data architectures, which could help the business, helping the business decide how they're going to roll forward. All of that, to be candid, holds even in a world of gen AI, assuming it gets to perfection. Now let's get to the next level. A lot of what our teams do, and it is perhaps unique to us, we tend to work on much more mission-critical systems. We tend to work much more on things which are fundamental to the business around financials, supply chain, cyber resilience and so on. Will gen AI and large language models have an impact? Absolutely. I would tell you that if I look over a five to 10-year horizon, I would agree with you that for that second part of consulting, not the first, I would agree and expect to see a 30% productivity. Now I would tell you that in that time frame, I would believe that for IBM, that's an advantage, not a disadvantage. Why? Absolutely, it's disinflationary. But if we share that with the client, that means we can win more work. And the total labor pool we need to drive an amount of revenue is lower because there is obviously value in the technology that we are using, be it for test automation or code writing. And maybe I can be a little bit boastful. I'll use that word, Keith, and talk about one example that we have. So we wrote a code assistant for Ansible, and it is part of our watsonx family. That code assistant for Ansible can help our Ansible developers, which is used as a -- I think it's the most widely adopted language for IT deployment, gets up to 60% more productive. Now that's one piece of it. IT deployment overall, I would then say, gets probably somewhere between 10% and 30% overall productivity. So that's why I think that 30% number is a good one to keep in mind. But to go across all the environments, KOBOL, Java, icon, AI models, that's going to take a few years before our clients get the full confidence around that topic.
Jim Kavanaugh: Yes. Keith, thanks for the question. On mainframe overall, pretty pleased given where we're at, GA plus four quarters in. So we wrapped on last year. Remember, we talked a lot last year. We came out with, unlike the prior programs. We came out with a second quarter launch in a highly seasonal transactional quarter, and we grew 77% last year overall, and we wrapped on that this year. I think we printed down 30% here in the second quarter. But a two-year CGR, so far, our five quarters in its most successful program and mainframe that we've had. Now why is it important? Yes, definitely, the value we deliver to clients, whether it's embedded AI, it's scale, cyber resilient security, cloud native development, but it's important internally to us, because it's a platform that drives a multiplier effect, to your question, around transaction processing. And we've been talking about this 2 times installed MIPS shift -- MIPS capacity over the last program. That was actually the z15 program over z14 because we're only 5 quarters into z16. But if you fast forward right now into z16, five quarters in, we're 120% to 130% up on an installed MIPS capacity already. And you know the tail of that usually happens in the outer path of the next three or four quarters before we come out with the new one. So we feel pretty good, and that's why we had the confidence entering this year, Arvind, and I, to take up the transaction processing model to actually low single-digit growth from being down mid-singles. So we see that continuing. Thanks for your question.
Patricia Murphy: Okay, we’re at the top of the hour. But let’s squeeze in one more question, please.
Operator: Thank you. Our final question comes from Ben Reitzes with Melius Research. You may go ahead.
Ben Reitzes: Hey, thanks a lot. Thanks for sneaking me in there. I wanted to ask you, Arvind, in layman's terms with regard to AI, I find a lot of investors want to understand IBM's place better. And in terms of AI, where you have your consulting and then hand it off to software, are you finding that IBM is well positioned to help people pick the right models to train, to lower their cost? What is it about IBM with the consulting and software that has your unique place set for growth and some of the optimism that you sound like you have heading into next year?
Arvind Krishna: Ben, thank you for the question, and I deeply appreciate your asking it in that form. Look, when we look at -- let me start with our extreme advantage when clients have data that they like to train models on and they absolutely want to preserve the intellectual property in that data, they do not want the learnings, I mean, I can go through three forms. Almost everyone will say, look, we're not going to take our data and give it to anybody in direct form. Okay. Next, how about learnings in the model itself from the data? Do you use that implicitly or explicitly or not at all? Three, the very fact that you're asking a certain kind of question can in turn reveal information. I'll use the word from my college training of site channel information. I'm sure that all of you also understand what that word could imply. So for people who are worried about all that, which we estimate to be at least 30% of the overall AI opportunity. Think about a bank dealing with regulatory compliance. Think about a pharma company dealing with reports to the FDA. Think about a health care company worried about some, kind of, side effect on something. Think about a chemicals company worrying about their proprietary formulations, not just watson, the literature. So as you go through all of these, there are lots and lots of examples where people want to train models. Maybe it's a refinement of a larger known model. So to your point on other models, and I'll come to that. So we found that there's a lot of opportunity, and those are the questions that people are asking us. Then next, a number of people are, critically, they have great models. They're great for big public consumption. They are great because everybody kind of has the same need for productivity. But there is also a world right now from the partners we work with, there's already over 100,000 open source models in addition to the models that we IBM provide. How do you pick from those models? Which one is appropriate? And we have taken a conscious strategy that we are not going to constrain the model that our clients want. So on our consulting teams, we will work with all the models, our own open source and other models so we can help our clients decide on which is the best one for them. Look, 30-years of being here has shown us that trying to help the clients navigate through the extreme complexity of this world is helpful to us, and we can become much better advisers and gain revenue in the process. So hopefully, that gives you a sense of how we are going to win here and get our fair share of this market. So given that we just passed the top of the hour, let me wrap up the call. We are in a really good position as we enter the second half of the year. Solutions meet today's client needs, new innovation we are bringing to market, and there is momentum and productivity in our underlying operations. As always, we need to execute to capture the opportunity in front of us, and I look forward to sharing our progress with you as we move through the rest of the year.
Patricia Murphy: Thank you. Sue, let me turn it back to you to close out the call.
Operator: Thank you. Thank you for participating on today's call. The conference has now ended. You may disconnect at this time.
