International Business Machines Corporation (NYSE:IBM) Q2 2024 Earnings Call Transcript

International Business Machines Corporation (NYSE:IBM) Q2 2024 Earnings Call Transcript July 24, 2024

International Business Machines Corporation beats earnings expectations. Reported EPS is $2.43, expectations were $2.18.

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 Olympia McNerney, IBM’s Global Head of Investor Relations. Olympia, you may begin.

Olympia McNerney: Thank you. I’d like to welcome you to IBM’s Second Quarter 2024 Earnings Presentation. I’m Olympia McNerney and 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 provided reconciliation charts for these and other non-GAAP financial 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 joining us today to discuss IBM’s Second Quarter Earnings. We delivered a strong quarter, exceeding our expectations, driven by solid revenue growth, profitability, and cash-flow generation. We had strong performance in software and infrastructure above our model as investment in innovation is yielding organic growth, while consulting remained below model. Our results underscore the continued success of our hybrid cloud and AI strategy and the strength of our diversified business. Let me start with a few comments on the macroeconomic environment. Technology spending remains robust as it continues to serve as a key competitive advantage, allowing businesses to scale, drive efficiencies and fuel growth.

As we stated last quarter, factors such as interest rates and inflation impacted timing of decision making and discretionary spend in consulting. Overall, we remain confident in the positive macro outlook for technology spending, but acknowledge this impact. It has been a year since we introduced watsonx and our generative AI strategy to the market. We have infused AI across the business from the tools clients use to manage and optimize their hybrid cloud environments to our platform products across.ai,.data and.gov to infrastructure and consulting, you can find AI innovation in all of our segments. For example, in software, our broad suite of automation products like Apptio and watsonx Orchestrate are leveraging AI and we expect to do the same with HashiCorp once the acquisition is complete.

Red Hat is bringing AI to OpenShift AI and rhel.ai. In transaction processing, we are seeing early momentum in watsonx Code Assistant for Z. In infrastructure, IBM Z is equipped with real-time AI inferencing capabilities. In consulting, our experts are helping clients design and implement AI strategies. Our enterprise AI strategy is resonating as we evolve to meet client needs. Let me start by discussing IBM models. Choosing the right AI model is crucial for success in scaling AI. While large general-purpose models are great for starting on AI use cases, clients are finding that smaller models are essential for cost-effective AI strategies. Smaller models are also much easier to customize and tune. IBM’s Granite models ranging from 3 billion to 34 billion parameters and trained on 116 programming languages consistently achieved top performance for a variety of coding tasks.

To put costs in perspective, these fit-for-purpose models can be approximately 90% less expensive than large models. Hybrid cloud remains a top priority for clients as flexibility of deployment of AI models across multiple environments and data sovereignty remain a key focus. We believe in the power of open innovation and recently announced at IBM Think that we open-sourced IBM’s Granite family of models now available under Apache 2.0 licenses on both Hugging Face and GitHub. We see parallel to Linux becoming dominant in the enterprise server space, thanks to the speed and innovation offered by open-source. We are confident that the same dynamic will play out with AI as we benefit from developer mindshare and community innovation. We also recently launched InstructLab, a tool for more rapid model tuning through synthetic data generation, allowing our clients to more efficiently customize models using their own data and expertise.

The last 12 months of AI pilots has made it clear that sustained value from AI requires truly leveraging enterprise data. In summary, our AI strategy is a comprehensive platform play. Rhel.ai and OpenShift AI are the foundation of our enterprise AI platform. They combine open-source IBM Granite’s LLMs and InstructLab model alignment tools with full stack optimization, enterprise-grade security and support and model indemnification. On top of that, we have an enterprise AI middleware platform with watsonx and an embed strategy with our AI assistance infused through our software portfolio and those of our ecosystem partners. In addition, our consulting services are critical in helping clients build their AI strategies from the ground-up. We also continue to see our infrastructure segment play a larger role as clients leverage their hardware investments in their AI strategies.

Our book of business related to generative AI now stands at greater than $2 billion inception-to-date. The mix is roughly one quarter software and three quarters consulting signings. We believe these strong results highlight our momentum and traction with clients. Our early leadership positions us for long-term success and this transformational technology, which is still in the initial stages of adoption. As clients build our AI strategies, the IT landscape is becoming increasingly complex. Labor demographic shifts further emphasize the importance of optimizing IT spend and automating business processes. We continue to innovate and invest and have created a leading automation portfolio to capture this opportunity, which you can see in our results.

This includes Apptio for cost management, capability for observability and resource management and with announced acquisition of HashiCorp, the automation of cloud infrastructure. The powerful combination of Red Hat Ansible and Terraform will simplify provisioning and configuration of applications across hybrid cloud environments. The latest addition to this portfolio is IBM Concert, also announced at Think, a Gen AI-powered tool, which helped clients get end-to-end visibility across business applications. We also recently completed the acquisition of the StreamSets and webMethods assets from Software AG. This acquisition brings together leading capabilities in integration, API management and data ingestion. Let me now spend a minute on the continued strength we are seeing in infrastructure.

IBM Z, our mainframe solution is an integral part of our clients’ hybrid cloud environments, driving their most secure and mission-critical workloads. Our latest cycle z16 is uniquely tailored to offer clients security, scalability and resilience, which help clients address both cybersecurity threats and complex regulatory requirements. z16’s Telum processor is a unique differentiator driving real-time, in-line AI inferencing at unprecedented speed and scale for applications like real-time fraud detection. Our storage offerings are also benefiting from generative AI as clients address data readiness and need high-speed access to massive volumes of unstructured data. We continue to invest in innovation and make great progress in emerging technology like quantum computing.

This quarter, we expanded Qiskit, IBM’s quantum computing software into a comprehensive stack aimed at optimizing performance on the utility-scale quantum hardware. These updates aim to enhance the stability, efficiency and usability of Qiskit, supporting advanced quantum algorithm development and fostering broader adoption across various industries. This strong momentum and innovation across the portfolio manifests itself in client adoption. In virtually all industries and geographies, clients leverage IBM solutions to help them transform their operations and create better experiences for end users. Names like Virgin Money, Credit Mutuel and Panasonic all turned to IBM in the quarter. We also continued to strengthen our ecosystem. At our Think event, we announced a series of new AI partnerships with industry leaders like Adobe, AWS, Microsoft, Meta, Mistral, Salesforce and SAP.

In May, IBM and Palo Alto Networks announced a partnership to deliver AI-powered security solutions using What’s the Next. As part of this, Palo Alto is acquiring IBM’s QRadar SaaS assets and we are partnering to offer seamless migration for QRadar customers to XM. IBM will train over 1,000 security consultants on Palo Alto Network products to drive a significant book of business with them. In summary, we are excited to continue delivering strong results. Given our first-half performance, we are raising our expectations for free cash flow to greater than $12 billion for the year. I will now hand over to Jim to walk you through the details of the quarter. Jim, over to you.

Jim Kavanaugh: Thanks, Arvind. In the second quarter, we delivered $15.8 billion in revenue, $2.8 billion of operating pre-tax income, and $2.43 operating diluted earnings per share. Our 4% revenue growth at constant currency combined with greater than 200 basis points of operating pre-tax margin expansion drove 17% operating pre-tax income growth and 11% operating diluted earnings per share growth, highlighting our strong execution. And through the first-half, we generated $4.5 billion of free cash flow. Our free cash flow generation is the strongest first half level we have reported in many years. We are pleased with these results, exceeding our expectations for revenue, profitability, free cash flow, and earnings per share.

Revenue growth was led by software and infrastructure. It is clear that our investments in innovation are yielding results and driving strong organic growth across these segments. Software grew by 8% with solid growth across hybrid platform and solutions and transaction processing and strong transactional performance. Infrastructure had great performance, up 3%, delivering growth across IBM Z and distributed infrastructure. Consulting was up 2% and continued to be impacted by a pullback in discretionary spending. Looking at our profit metrics, we expanded operating gross margin by 190 basis points and operating pre-tax margin by 220 basis points over the last year, inclusive of about a 30 basis-point currency headwind to pre-tax margin. Margin expansion was driven by our operating leverage, product mix and ongoing productivity initiatives.

Driving productivity is core to our operating and financial model. This includes enabling a higher-value workforce through automation and AI, streamlining our supply-chain, aligning our teams by workflow and reducing our real-estate footprint. These actions allow for continued investment in innovation with R&D up 9% in the first-half. This includes investments in both AI and hybrid cloud as well as infrastructure ahead of our Nexi program in 2025, which we expect to accelerate our organic growth profile over time. Our results this quarter reflect broad-based growth and the strength in the fundamentals of our business with revenue up about $300 million, operating pre-tax income up about $400 million, adjusted EBITDA up more than $350 million and free cash flow up about $500 million.

For the first-half, we generated $4.5 billion of free cash flow, up $1.1 billion year-over-year. The largest driver of this first-half growth comes from adjusted EBITDA, up about $550 million year-over-year and timing of CapEx. We are a few points ahead of our two-year average attainment levels through the first-half. In terms of cash uses, we returned $3.1 billion to shareholders in the first half in the form of dividends. From a balance sheet perspective, we have a very strong liquidity position with cash of $16 billion, up $2.5 billion since year-end 2023. Our debt balance at the end of the second-quarter was flat with year-end 2023 at $56.5 billion, including $11.1 billion from our financing business. Putting this all together, our business fundamentals remain solid with continued revenue growth, margin expansion, cash generation, and a strong balance sheet with financial flexibility to support our business.

Turning to the segments. Software revenue growth accelerated to 8% this quarter. Both hybrid platform and solutions and transaction processing grew as clients leverage the capabilities of our AI and hybrid cloud platforms. This performance reflects the investments we’ve been making in software, both organically, which drove more than 6 points of the growth as well as acquisitions. As mentioned in January, the software revenue growth drivers for the year include Red Hat growth, the combination of innovation, recurring revenue, and transaction processing, as well as acquisitions. Let me spend a minute on each of these elements. In Red Hat, annual bookings growth accelerated to over 20% this quarter. Within that performance, OpenShift annual bookings were up over 40% and RHEL and Ansible growth was double digit.

The strength reflects the demand for our hybrid cloud solutions, including app modernization, management automation, generative AI and virtualization. In a subscription-based business, the majority of revenue is under contract for the next two quarters. Think of it as our CRPO for the next six months. This metric is growing in the mid-teens and accelerating more than 5 points versus the first-half of the year. We continue to bring new innovation to our portfolio and it’s contributing nicely to our software performance. Our new innovation includes generative AI offerings like watsonx, our AI middleware, watsonx Assistants, the recently-announced IBM Concert and others, which contributed about $0.5 billion to our AI book of business inception to-date.

And we delivered good growth across our recurring revenue base, which is about 80% of the annual software revenue. This is evident in hybrid platform and solutions, where our ARR is now $14.1 billion and up 9% since last year. Transaction processing delivered 13% revenue growth. This performance demonstrates the innovation and value of our mission-critical hardware stack across IBM Z, power and storage. The combination of growing demand for capacity, good client renewals, and strong large deal performance fueled our results. And notably, our new generative AI portfolio innovation, watsonx Code Assistant for Z is resonating well with clients. Together, these dynamics contributed to both recurring and transactional software revenue growth again this quarter.

Revenue performance this quarter also benefited from our focused M&A strategy, including synergies realized across the portfolio. This included the recent Apptio acquisition. Less than 12 months since closing, we have accelerated annual bookings and are seeing an uptick in ARR growth already in the mid-teens. The synergy between Apptio’s FinOps offerings and our broader automation portfolio helps clients manage, optimize and automate technology spending decisions. Earlier this month, we completed the acquisition of StreamSets and webMethods from Software AG and expect the HashiCorp acquisition to close by year end. Looking at software profit, gross profit margin expanded and segment profit was up over 350 basis points year-to-year, with the latter reflecting operating leverage driven by our revenue scale and mix this quarter.

Our consulting revenue was up 2%, consistent with last quarter and largely reflecting organic growth. In April, we discussed that we were seeing solid demand for our large transformational offerings as clients continue to prioritize driving productivity with AI and analytics. At the same time, we saw a pullback on discretionary projects as clients prioritize their spending. The second quarter buying behavior played out much in the same way. Signings for the quarter were $5.7 billion, driven by solid demand for large engagements across finance and supply-chain transformation, cloud modernization, and application development. This contributed to backlog growth of 5% year-over-year and our trailing 12-month book-to-bill remaining over 1.15. Meanwhile, continued discretionary spending constraints impacted our small engagement performance and backlog realization in the quarter.

As Arvind mentioned, our book of business in generative AI inception-to-date is greater than $2 billion and about three quarters of it represents consulting signings with strong quarter-over-quarter momentum. Our extensive industry and domain expertise has placed us in an early leadership role, which is crucial at the onset of a technology shift. IBM has both technology and consulting, which is a unique and powerful combination to help clients navigate this technology transition. Similar to previous technology shifts such as the advent of the Internet, globalization, and cloud computing, generative AI is driving the next wave of growth. In a human capital-based business, signings represents clients reprioritizing spend on this technology transition, while there is some potential for lift as the total addressable market expands.

We are delivering value in two ways. First, partnering with our clients to design and scale AI solutions, whether that be leveraging AI capabilities of IBM, our partners or a combination. Second, we are developing new ways of working, driving productivity and improving delivery, all with our Consulting Advantage platform. In summary, GenAI is acting as a catalyst for companies to grow revenues, cut costs and change the ways they work, creating a significant opportunity for us. We are seeing this already as IBM is the strategic partner of choice for clients using this technology, including WPP, Elevance Health, and the UK’s Department of Work and Pensions. Turning to our lines of business. Business transformation revenue grew 6%, led by finance and supply-chain transformations.

Data transformation also contributed to growth. In Technology Consulting, revenue was up 1%. Growth was driven by application modernization services. Application operations revenue declined, reflecting weakness in on-prem custom application management, partially offset by strength in cloud-based application management offerings. Looking at consulting profit, we expanded gross profit margins by 40 basis points, driven by productivity and pricing actions we have taken. Segment profit margin was modestly down, reflecting continued labor inflation and currency. Moving to infrastructure, revenue was up 3%. We’re capitalizing on the strong and broad-based demand for our hardware platforms, especially IBM Z. Within hybrid infrastructure, IBM Z revenue was up 8% this quarter.

We’re now more than two years into the z16 cycle and the revenue performance continues to outperform prior cycles. Our clients are facing increasing demands for workloads given rapid business expansion, the complex regulatory environment and increasing cybersecurity threats and attacks. IBM Z addresses these needs with a combination of cloud-native development for hybrid cloud, embedded AI at scale, quantum-safe security, energy efficiency, and strong reliability and scalability. Increasing workloads translates to more Z capacity or MIPS, which are up about threefold over the last few cycles. IBM Z remains an enduring platform for mission-critical workloads, driving both hardware and related software, storage and services adoption. In distributed infrastructure, revenue grew 5%, driven by strength in both power and storage.

Power growth was fueled by demand for data-intensive workloads on Power10 led by SAP HANA. Storage delivered growth again this quarter, including growth in high-end storage tied to the z16 cycle and solutions tailored to protect, manage, and access data for scaling generative AI. Looking at infrastructure profit, we delivered solid gross profit margin expansion and segment profit accelerated quarter-to-quarter to the high-teens. Segment profit margin was down 230 basis points in the quarter, reflecting key investments we’re making in the business across areas like AI, hybrid cloud and quantum, and almost a point of impact due to currency. Now, let me bring it back to the IBM level to wrap up. We feel good about our performance in the first half with revenue growth reflecting the investments we’ve been making both organically as well as acquisitions.

Our focus on execution and the strength in the fundamentals of our business resulted in strong performance in the quarter across revenue, margin expansion, and growth in profitability and earnings. Looking to the full-year 2024, we are holding our view on revenue. We see full-year constant-currency revenue growth in line with our mid-single-digit model, still prudently at the low end. For free cash flow, given the strength in our performance in the first half, we feel confident in raising our expectations to greater than $12 billion, driven primarily by growth in adjusted EBITDA. This also includes a modest contribution resulting from the Palo Alto QRadar transaction, largely offset by related structural actions to address stranded costs. We continue to expect the QRadar transaction to close by the end of the third quarter.

On the segments, in Software, we had solid first-half performance, up more than 7%. This performance reflects strength in our recurring revenue base and early traction in GenAI. With this performance, we are raising our view of growth in software to high-single-digits for the year. And given ongoing productivity initiatives and operating leverage, we now expect software segment profit margin to expand by over a point. In Consulting, given the continued pressure we have seen on spending related to discretionary projects, we now expect low-single-digit growth for the year and segment profit margin to expand by about half a point. And given the strength in infrastructure in the first-half, we now expect it to be about neutral for the year with segment profit margin in the mid-teens to high-teens.

With these segment dynamics, we are raising our expectations of operating pre-tax margin expansion to over a half a point year to year. And we are maintaining our view of operating tax rate in the mid-teens range, consistent with last year. On currency, given the strengthening of the dollar, we now expect a 100 basis-point to 200 basis-point impact to revenue growth for the year. For the third quarter, we see revenue growth consistent with the full-year. For profit, we expect our net income SKU through the third quarter to remain a couple of points ahead of the prior year, driven by the strength of our business. And again, we expect the gain of the Palo Alto QRadar transaction will be offset by related structural actions to address stranded costs.

In closing, we are pleased with our performance this quarter and for the first-half, driving confidence in our updated expectations. We are positioned to grow revenue, expand operating profit and grow free cash flow for the year. Arvind and I are now happy to take your questions. Olympia, let’s get started.

Olympia McNerney: 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 multi-part questions. Operator, let’s please open it up for questions.

Q&A Session

Operator: Thank you. At this time, we’ll begin the question-and-answer session of the conference. [Operator Instructions] And our first question comes from Wamsi Mohan with Bank of America. Please state your question.

Wamsi Mohan: Yes, thank you so much. Your long-term model on transaction processing is low-single-digit and you just posted a very strong quarter with 13% growth in the quarter. How should we think about the trajectory of that in 2024 and maybe in 2025? I know, Jim, you noted a few different things, including solid client renewals and some strong large deal performance. Was there anything very episodic or unusually large within that mix as well? Thank you so much.

Jim Kavanaugh: Thanks, Wamsi. I appreciate the question overall. Very important. You know, if you take a step back, you know, we continue to be very pleased with our transaction processing performance overall. You know, if you dial back to when we laid out our mid-term model, we said we converted this to a growth vector, low-single-digit overall. And if you look at the last couple of years, we’ve been averaging mid-single-digit or better overall. We shifted this now to a growth contributor. And why is that important? One, high source of profit and cash, the fund investment flexibility; and two, it provides a very solid incumbency base for the IBM or multiplier effect. But if you take a look at it, we are capitalizing on the strength that we’ve seen over the last three programs of our mainframe cycle.

It’s really instantiating the enduring value of that platform. Our MIPS over the last few programs are up three times from an installed perspective and over 80% of our clients are growing MIPS on the mainframe. I think that was a very different picture when you dial back five, seven years ago already. So, we’ve taken that portfolio. We’ve invested now significantly, which I’ll come to around watsonx Code Assistant for Z, but we’ve taken that from a down mid-single-digit portfolio to now capitalizing on the stack economics of our mainframe, execution and move that to low-single-digit. Now for the year, as you heard, we are taking up our guidance just given the strength of first half to mid-single-digit. You know, when you get into 2025, we’ll talk about our guidance going forward, but we feel very confident that we can continue growing this and that’s why we’re investing in bringing out new capabilities like watsonx Code Assistant for Z, which is resonating extremely well.

Olympia McNerney: Operator, let’s take the next question.

Operator: Our next question comes from Toni Sacconaghi with Bernstein.

Toni Sacconaghi: Yes, thank you for taking the question. I’m wondering maybe you can discuss how you think about AI signings and whether you believe they’re really incremental or just a shift in client spending? And part of the reason I asked the question is, if I — you know, it looks like your AI book of business was up about $1 billion sequentially. You’re saying three quarters of that is Consulting, so it’s $700-plus million in Consulting signings in the quarter. If I take that out, your book-to-bill and the rest of your business is actually down. And despite the strong signings, you’re lowering your Consulting expectations for the year. So, I’m just wondering, do you think AI investments in Consulting are a shift in spending? Or do you think they’re accretive? Or do you actually think they could even be cannibalistic to Consulting spend and more broadly IT spend?

Arvind Krishna: Yes. So Toni, let me start and then Jim will add more color on this topic. First, it’s a great question and you laid out some of the dynamics that were going on in there. If we just step back and just look at our comments on the macroeconomic environment, we kind of stated that there is discretionary spend pressure in Consulting. When you do have that pressure, but there is a demand for AI, I would look you in the eye and say, probably the bulk of that demand, not all but the bulk is indeed a shift from other areas of Consulting. We don’t actually believe it’s cannibalistic to the point you’re pointing out. Now, as time goes on and as people move from early experimentation and proving out the value to wanting to scale and really get the full benefits of generative AI, we do actually believe at that point, even for consulting, these will turn into accretive and additive, but we are still some time away from when that will happen.

So, that is just to give you some color and acknowledging that the bulk, but not all is a shift. Jim?

Jim Kavanaugh: Yes. Thanks Toni for the question. Just building on what Arvind said. I mean, first of all, we’re very pleased with the early momentum that we’ve gotten with our book of business around GenAI, both on the technology side with our watsonx platform and now with our open innovation strategy around RHEL AI, OpenShift Granite model’s InstructLab, etc. But let’s just deep — dive a little deeper into your question about Consulting, because I think when you look at Consulting, first of all, why is it so important right now in a early part of a cycle? It’s important because it’s got to establish IBM Consulting as the strategic provider of choice for enterprises as they’re going through what we’d like to call digital transformation 2.0 with GenAI.

Everyone is looking for who is going to be their strategic provider and partner. And I think $1.5 billion over $1.5 billion book of business in the first 12 months, which by the way is in excess of the ramp we saw play out with hybrid cloud and Red Hat, we’re off to a pretty good start. Now, to Arvind’s point, you know, in every technology shift, very different dynamics between a Human Capital based business and a product IP business. Human Capital based business, we do see and we expected clients will shift and reprioritize spending. They’re doing that now as they’re driving large enterprise transformation projects, which is what our portfolio has been able to capture, and that’s why you see nice acceleration in growth in our backlog up healthy at 5%.

But to Arvind’s point, we do think once you get through the early cycle, this is an incremental expansion of TAM that drives a long-tail growth vector over time that has multiplier opportunities for us. So when you look at our consulting book of business, let’s dive into the sub-segments, you see business transformation services, which a lot of the GenAI plays out too early right now. That is how do you transform the way you operate HR, finance, supply-chain. We’ve doubled and accelerated our growth quarter-to-quarter. What you’re seeing is a reprioritization and dynamic spending decisions by clients because our AO, where we have a lot of short-term discretionary staff augmentation work, there’s a lot of trade-offs between those two. So, it’s important for us strategically with our client base, but I think you see how it plays out.

Now, just to wrap up the full picture, Software, I think is fundamentally different. Our software book of business now $0.5 billion through the first 12 months. I think inception-to-date right now, we’re about two-thirds of subscription, SaaS, one-third perpetual. I think that’s contributing nicely about a point of growth. And by the way, that’s one of the two components of why we took our software up for the year. So, I think that’s predominantly all lift.

Olympia McNerney: Operator, let’s take the next question.

Operator: Our next question comes from Amit Daryanani with Evercore ISI.

Amit Daryanani: Thanks for taking my question. I guess, you know, my question is really on the Consulting side. And when I think about this business growing low-single-digits for ’24, if I take out some of the M&A contribution, also some of the revenues from the AI book of bill — book of business that you have at $1.5 billion, is it fair to think that maybe the non-AI Consulting piece actually gets worse in H2 versus H1 for you? If you just talk about the puts and takes on the back half consulting expectations versus front half, that would be really helpful. And then, you know, I’m curious, if you talk to your customers, what is your sense on the duration of this weakness in Consulting and when do you think it has to come back? Thank you.

Arvind Krishna: Hi. So Amit, let me just start and maybe address the second part of your question first and then. I actually do not believe there’s any secular macro trend around weakness. I think that this is temporal based on a number of factors we have. The geopolitical uncertainty has gone longer than most people expected and that weighs into people’s heads about what that might happen. And specifically, the war in Europe as well as the war in the Middle-East. Second, inflation has gone longer than people expected, which has the unfortunate consequence of higher interest rates and that begins to bear on people. If I look at those two altogether and that then at the moment you have higher interest rates and inflation, you have wage inflation, which does impact the bottom-line of our clients.

You put all of that into perspective and is this going to go on for another six months? Likely. Is it going to go on for another year? I’m not so sure, but we got to get through the second half to be able to go there. So, that is why we are optimistic about the medium-term and long-term vector on Consulting. And as Jim answered in the prior question, we do see that this is going to become a tailwind over time, at least for us. Now, in the short-term for the next six months, we do think it holds up a little bit. In terms of answering the specifics and sort of decomposing some of the numbers that you laid out in the first part of your question, I’m going to turn that over to Jim.

Jim Kavanaugh: Yes. Thanks Arvind and thanks Amit for the question overall. You know, let’s put this in perspective, right? You go back 90 days ago, how did we see the year kind of playing out with Consulting? We said at that point in time, we had backlog growing nicely mid-single-digit, albeit we did talk about durations going up because large scale transformations were really where the spend was moving to. But we had a solid book-to-bill trailing 12 months over 1.15. We had GenAI momentum that was going to continue throughout the year early in the cycle. We had strategic partnerships, Red Hat growth profile, and we had future acquisitions as we’re going to continue to be opportunistic around our M&A criteria and the synergistic value of how consulting plays to our portfolio.

If you look right now, 90 days later, as we look to the second-half, many of those are still playing out. You got GenAI, which arguably were above our own expectations, right now doubling, by the way, in Consulting, our GenAI book of business quarter-to-quarter, strategic partnerships, especially hyperscalers, Red Hat still growing nicely. What you’re seeing, you know, at the end of the day, those are large scale transformations, lower yield, that’s why Arvind and I are saying these are longer-term growth vectors and tails that will play out into ’25, ’26 and beyond as we get that strategic provider of choice. But in the interim, what you’re seeing is that spending reprioritization around short-term discretionary that I think, you know, everyone in the industry is talking about.

We’re all dealing with this. The key is we have to win that strategic provider of choice in GenAI. And I would argue we’re off to a great start. You look at competitor numbers overall, we got $1.5 billion over $1.5 billion book of business doubling quarter-to-quarter right now. I think we’re in pretty good shape. That’s what we’re focused on because that will provide the future revenue multiplier effect as we move forward.

Olympia McNerney: Operator, let’s take the next question.

Operator: Our next question comes from Jim Schneider with Goldman Sachs.

Jim Schneider: Thanks for taking my question. Maybe if I could just ask on different topic for a second. Can you maybe talk about the environment you see right now for M&A and your intention to continue to drive through acquisitions? And do you believe you have sufficient scale in open-source and DevOps software in particular? And can you maybe comment on the attractiveness of multiples in the public market today relative to the private market?

Arvind Krishna: Hey, Jim, great question and thank you for asking this. Look, on overall M&A, I just want to begin with that our strategy has not changed. We are — we are disciplined and we are focused. By focused, I mean we stick to the areas that we are investing in hybrid cloud and artificial intelligence. And by discipline, I mean it has to be not just aligned to our strategy, but we expect synergy from the acquisition, especially the multiples are higher as you pointed out and it has to be accretive to free cash flow if it’s larger, definitely within two years at the outer end of the range. So having said that, if I look at it right now, we have HashiCorp out there. So, we got to get through that. We expect that to happen in the second-half of this year. We just finished StreamSets and webMethods and we’ve done a couple of smaller ones in the Consulting space and in other technology tuck-ins.

Jim Schneider: All right.

Arvind Krishna: What do we see going into this space? Our valuations rich, they’re reasonably rich. They’re not outrageous, I would say, like they had become in parts of late 2020 and 2021. So, I would say that they are more reasonable than then, but they’re richer than they were about 18 months ago. There are different dynamics in both the public and the private markets. Public markets are quite variable. I mean, as we can see, some of the multiples and if you look at multiple to revenue, which is not a great metric, let me just acknowledge that, but it is one that’s out there. If you look at six, seven, eight, maybe nine or 10 times, we can see our way there for a large deal as long as we have sufficient synergy. Now, for very small deals, that’s not even a fair multiple.

Very small deals are all about technology and people. In the private markets, we were very pleased with what we got done on StreamSets and webMethods. I would call that a private market deal, not a public market deal. And there, I think it all depends upon what’s the property, what is its growth profile, what is the attractiveness of it to the seller versus the buyer, in this case us, all of that play into those multiples. I do expect that on the private side, valuations will be slightly less, but then the risk of going public or some other exit is also taken away. And in some sense, you get a discount for taking that risk off the table. For people who are venture-backed, that’s different. They are looking at IPO versus a strategic exit and those are different multiples.

But putting all of that together, we remain in the market and M&A is an important part of our growth methodology. We maintain a strong balance sheet for that purpose and we’ve kind of been clear of that. All that said, this year, we got a big one coming. So, we want to wait and get that done because part of the discipline is also making sure that we kind of digest them at the right rate and pace and put them into our global go-to-market distribution engine.

Olympia McNerney: Operator, let’s take the next question.

Operator: Our next question comes from Ben Reitzes with Melius Research. Please state your question.

Ben Reitzes: Yes. Hey, thank you. Appreciate it. Jim, I wanted to — and Arvind, I wanted to see, you know, if the — it sounds like the margin progress is sustainable for the year. So while I appreciate that you guide to free cash flow and you’ve raised it a little bit, do you anticipate us being able to flow through the $0.25 of upside on the EPS line? And you know, can — does that mean earnings is sustainable in the back half? And then I was just wondering if you have any more info on HashiCorp, yes, in terms of the revenue contribution, Street was looking for about $750 million in revenue next year. And on the dilution, there’s — there should be a loss of around $0.30 in interest income. So, just wondering if you have any further views on the net effect to 2025 on that deal. Thanks so much, guys.

Jim Kavanaugh: Hey, Ben, thank you. Appreciate it. Very good question overall. But let’s take a step back on your first part of the question around free cash flow. Yes, we’re very pleased with the start of the year. Free cash flow of $4.5 billion, up $1.1 billion year-to-year, 4 points above historical attainment. It’s our largest first half free cash flow generation as far back as I can go and count. So, we’re off to a pretty good start and that gives us the confidence overall of how we’re positioning second-half. But the second half and why we took the guidance up is entirely driven by the strength of the fundamentals of our business and flowing through the adjusted EBITDA overachievement. So, read that, although we don’t guide on EPS, the strong overachievement of the $0.25 of EPS, we’re flowing that through to adjusted EBITDA and that flows through to our guide take-up on free cash flow.

The rest of the free cash flow dynamics we’ve been talking about all year long around, yes, we got benefits of change in retirement plans and cash tax that’s going to be a headwind and other balance sheet items, none of that changes. One thing I will bring up and we said in the prepared remarks, but just so there’s absolute clarity, we do expect to close the Palo Alto transaction here in the third quarter around certain assets of our QRadar business that will obviously generate a gain. We’re excited about the new strategic relationship between our two great companies overall, but we will take structural actions to offset that gain to address stranded cost. And oh, by the way, to your second part of your question, to accelerate our productivity initiatives in 2025, so you get the HashiCorp.

First of all, the strategic transaction stands on its — on its own. Arvind went through our M&A criteria. I think there’s a very compelling strategic fit around an end-to-end leadership hybrid cloud platform. There’s a lot of synergistic value both on product technology and go-to-market, but there’s a very attractive financial profile that we talked about 90 days ago, higher revenue growth profile, adjusted EBITDA accretive in 12 months, free cash flow accretive to Arvind’s point by two years. And we do see potential significant near-term cost in operating synergies that lead to about a 30% to 40% free cash flow margin business over a handful of years. Now, when you look at dilution, we understand dilution. I mean, M&A has been an integral part of our financial model for decades.

So, underneath that, we understand the purchase growth of those transactions, the synergies of those transactions, the balance sheet capital structure implications of those. And with all that said, our model is to grow mid-single-digit revenue and grow operating leverage so we grow free cash flow quicker than revenue. We don’t see that changing in 2025. We see growth profiles around revenue, around operating leverage and around free cash flow overall. And that speaks to the diversity or diversification, I should say, of our business model around productivity. We entered the year, raised it to $3 billion. We’re getting out ahead of that again and you see that play out in our margins through the first-half, what, up 180 basis points on pre-tax.

So, we’ve got many levers to deal with this overall. We know how to handle it.

Olympia McNerney: Operator, let’s take the next question.

Operator: The next question comes from Erik Woodring with Morgan Stanley.

Erik Woodring: Hey guys, thanks so much for taking my question. Arvind or Jim, I’d love if you could just dig into the Red Hat business a bit more. You know, over the last few quarters, you’ve talked about some very healthy bookings growth numbers ranging anywhere between, call it, 15% and 20%. But we did see growth obviously decelerate by about a point this quarter despite, you know, expectations that it would be flat to maybe increasing for the rest of the year. So, can you just kind of double click on exactly what you’re seeing with the Red Hat business today? What’s kind of the offset to the strong bookings numbers? And how should we think about Red Hat growth now in constant currency for 2024? Thanks so much.

Arvind Krishna: Great question, Erik. So, let’s just look at the Red Hat business in terms of how the dynamics function between our clients and ourselves. So, clients come in and create demand, we fulfill that. That shows up as bookings, not as revenue because the Red Hat business model is a pure consumption business model. Clients pay for what they’re consuming and so the bookings then play out. Now, those bookings are a signal of further demand and typically they’re anywhere from one-year to three-year worth of revenue that the client is pre-committing to. So, when we enter a year, about half the revenue, we can look at the bookings of the previous year and say that that gives us. The other half has to come over the quarter.

Now that we have a year, not longer, but a year of the double-digit demand that you’re talking about, if I remember right, it was 14%, 17%, 14%, 20% in terms of those demands. Now that full-year is there, that points to that for the portion that we can see, and as we get into a quarter, it climbs up from that 50% to 60% to 70% to 80% and Jim mentioned in his prepared remarks, what he called CRPO or the revenue performance obligations, we see those sitting around mid-teens for the second half of the year to answer your question. Now, if that’s about 80% and that will translate into low double digit is what we can look at and feel quite comfortable on. By the way, we see these early signs of the demand continue into this quarter and likely the half, which means that we expect to continue now in the low double digits going forward.

So, I hope that that gives you a sense. But I’m also excited by the underlying product capabilities. We see OpenShift, which is extremely important. It plays into containerization, it plays into virtualization. It’s an important element of how our clients exercise hybrid. It has been growing and the demand there grew again at about 40% this past quarter. But we also saw acceleration in Linux and enhanceable where both of those demand vectors grown to the low double-digits. That given the size of the Linux business is very good news for us going forward. So, I hope that that gives you some color on those pieces. And a vector that we have not talked about that will play, but probably into ’25 and ’26, we are very excited by our two open-source AI projects inside the Red Ad business, our RHEL AI as well as OpenShift AI.

And as people begin to deploy at scale, but not only on public cloud, but also on-premise, leveraging their hybrid environment, we expect that both of those will also contribute into the Red Hat business, but that will take more time.

Olympia McNerney: Operator, let’s take one last question.

Operator: Thank you. Our next question comes from Matt Swanson with RBC Capital Markets.

Matt Swanson: Thank you. Yes. Arvind, if we could pick up right where you left off there. Can you just give us a little more color on the decision to open up the Granite models and the code base? And then really kind of what you’re seeing in the market that makes you feel like taking maybe a more developer-focused approach to those? I think as you put it, fit-for-purpose models, is the right long-term strategy?

Arvind Krishna: So Matt, thank you for asking that question. And there was actually a question on developers before also. So, I’m sorry we didn’t get to it fully. We’ll get to it now in this question. Look, the whole question comes down to, there was a thesis out there about a year and a half ago that maybe one, maybe two extremely large models are going to run away with the bulk of the market share. We always felt that was both technically and economically infeasible. And I’ll describe why. If you run an extremely large model on public clouds, the model by its nature is going to be expensive because a very large model needs a lot more compute, a lot more network, a lot more storage, a lot more memory, and we can see some of those dynamics play out.

If you can drop the model size, you can drop all of that by 90%. I would actually tell you 99% reduction in the compute and memory and network costs, but let’s call it 90% just for the sake of argument. So if you are running a — like one of our clients was describing to me, they run a couple of billion transactions through their internal systems each day. If they had to go service those out to a large public cloud, the bill per day would have come back to be a couple of $100 million. You multiply that by 250, that’s kind of an infeasible cost. If you can drop it by 90%, you’re now bringing it down to the $10 million to $20 million a day. If you can actually run it using some of our Red Hat technologies on-premise, you can drop it by another 50%.

You’re not talking 5% to 10%. For what it can do, that is a very attractive proposition. So, now getting back to the models. If you have no idea what you’re going to do, if you have no idea what you might be looking for, you go to a very large model because it contains all the possible elements. If you have a sense of what you need to do, I need to summarize emails. You need an English-language model if you’re sitting here in the United States. If you are going to go change your Java or C++ or Python programmers to be more productive, you don’t need a model that can write poetry and draw images. You need a model that understands programming languages. So, we are very, very proud of what our team has done. We can produce models that can do these things.

So, these are two distinct models, one for programming, one for business language. They are one-tenth or less than that of the size of the extremely large models. But you can look on the leader boards, they perform quite as well as the largest models. So, that is kind of what our strategy is. However, if our clients want other models, we are also happy to work with other models and we have had that perspective. So, why open-source since that is part of your question? Why open-source is because often we find that clients want to increase the model’s efficacy by adding their own unique language. People might want to write emails in a certain way. They might want to program in a certain way. They like comments in a certain style. I call that refining the model.

We have a technique called InstructLab, but then clients get concerned. Wait, if I add my data, I don’t want to give that away and back into a more public format. Can I keep that to myself? So, open sourcing our models under the Apache license gives our clients the freedom that what they add onto our underlying open model, they can keep to themselves. Now, to the developer point, putting all of that machinery into Red Hat Linux now gives us an avenue to open it up to developers as they can go experiment and play. By the way, I will turn around and tell you that for a developer who’s not running production, who’s just playing with things like all people do it. On a MacBook, you can begin to play around with models that are in the low tens of billions of parameters.

That’s a massive market that opens up. They get the freedom and flexibility that they don’t have to give it back to us unless they want to. I am not actually concerned about this gives away the IP, as we have found through whether it’s Red Hat Linux or whether other people have found through Mongo or other people have found through Hadoop, enterprises do look for and the last few days have certainly shown us, people look for patching, people look for security, people look for backward compatibility. There’s a lot of enterprise reasons why people will still do business with us. But the open-source nature of what you asked, I’m so glad you did, allows us to expand that market into the millions of developers who do run Linux on their own machines or their corporate machines or their laptops and they can go experiment, add their innovation and either give it back to the community or actually reserve it for their enterprise.

So, that’s how we kind of tap into the whole developer ecosystem. So, let me now wrap up the call. In the second quarter of 2024, we executed on our strategy to deliver revenue growth and cash generation. We saw strong performance across our portfolio. We are excited about our early traction in generative AI. We look forward to sharing our progress with you as we move through the rest of the year. Thank you all.

Olympia McNerney: Thank you, Arvind. Operator, let me turn it back to you to close out the call.

Operator: Thank you for participating on today’s call. The conference has now ended. You may disconnect at this time.