Dassault Systemes (OTC:DASTY) reported second-quarter financial results on Thursday. The transcript from the company's second-quarter earnings call has been provided below.

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Summary

Dassault Systemes reported a 4% revenue growth and an 8% increase in earnings per share, driven by strong subscription revenue growth, which doubled the overall business growth rate.

The company reaffirmed its full-year guidance and emphasized strategic initiatives focused on customer transformation through the 3DEXPERIENCE platform, expansion into new industries, and continued investment in AI-native solutions.

The acquisition of ArisGlobal was highlighted as a key strategic move to enhance the company's position in life sciences by integrating a unified AI-intelligent platform connecting various stages of the pharmaceutical lifecycle.

The 3DEXPERIENCE platform is becoming an agentic platform with AI-native applications, enhancing industrial innovation across sectors like automotive, aerospace, and consumer products.

Financial performance showed solid growth, with total revenue reaching 1.556 billion, a 4% increase, driven by strong performance in Asia, especially in India, Korea, and Japan.

Management emphasized the importance of digital transformation and AI deployment among customers, noting a shift from questioning AI's role to accelerating its deployment.

The company maintains a strong cash position, supporting the ArisGlobal acquisition, with cash and equivalents reaching 5.66 billion.

Looking ahead, Dassault Systemes aims for 3 to 5% revenue growth ex-FX for the full year 2026, with a continued focus on AI strategy and cloud adoption.

Full Transcript

OPERATOR

Good day and thank you for standing by. Welcome to the Dassault Systemes second quarter and half year 2026 earnings presentation. At this time all participants are in listen-only mode. After the speaker's presentation, there will be the question and answer session. To ask a question during the session, you need to press star 11 on your telephone keypad. You will then hear an automatic message advising your hand is raised. To withdraw a question, please press star 1 and 1 again.

Please be advised that today's conference is being recorded. I would now like to hand the conference over to our first speaker today, Marie Dumas, Investor Relations Director. Please go ahead.

Marie Dumas, Investor Relations Director

Good morning and thank you for joining our second quarter 2026 earnings conference call. I'm with Pascal Dalloz, Chief Executive Officer and Chairman of Dassault Systemes, and Reuben Bergman, Chief Financial Officer. They're both on the line with me to discuss our second quarter 2026 results. Dassault Systemes results are prepared in accordance with IFRS. The financial figures discussed on this conference call are on a non-IFRS basis with revenue growth rates on a constant currency basis.

Unless otherwise noted, some of the comments on this call contain forward-looking statements that could differ materially from actual results. Please refer to today's press release and the risk factors section of our 2025 Universal Registration documentation. All earnings materials are available on our website and these prepared remarks will be available shortly after this call. I would like now to hand over to Pascal Dalloz.

Pascal Daloz, CEO

Good morning, everyone. Thank you, Marie, and thank you all for joining us today. Before Reuben will walk through our financial results, I really would like to spend a few minutes on what I believe is a bigger story. This quarter is about much more than the numbers. It's about execution. It's about the steady progress we are making against the strategy we set at the beginning of the year. As you remember, I said from the start that 2026 will be the foundation year.

Not because we expect less, but because we are building for much more. Transforming industry does not happen in a single quarter. It happens customer at a time, one deployment at a time, and one innovation at a time. And this is exactly what this quarter reflects. This quarter our business performed well. We are reaffirming our full-year guidance. Revenue grew 4%. Subscription revenue grew twice as fast as the overall business, and earnings per share increased 8%.

I think these results reflect the disciplined execution we had. But the numbers, as I was saying, are only a part of the story. The more important story is what we are seeing happening with our customers across every major industry we serve. Companies are accelerating their digital transformation. They are moving to the cloud, they are preparing their data, and increasingly they are investing in industrial AI. The conversation has really changed.

Customers are no longer asking whether AI will transform engineering or manufacturing. They are asking how fast they can deploy it. And this is really an important shift. Why so? Because AI needs context; it needs trusted data; it needs virtual models of products, factories, operations. And this is exactly what the 3DEXPERIENCE platform was built to provide. This is why we believe we are uniquely positioned for the next era of industrial innovation.

Now our strategy remains focused on three priorities for this year. First, helping our existing customer transformation. More of the world’s leading industrial companies are adopting the 3DEXPERIENCE platform on the cloud as their digital foundations. They are connecting engineering, manufacturing, and operations in a single platform. And they are preparing to deploy AI for virtual twin at the enterprise scale. Second, expanding into new industries.

We continue to build momentum in high-tech, new space, and consumer industries. And with the acquisition of ArisGlobal, we are significantly strengthening our position in life sciences. Each of those industries expands our opportunity, and together they make our business stronger and more resilient. Third, we continue to invest in the platform itself. As AI is becoming the new interface to industrial software, our ambition is not simply to add AI features; it’s to build an agentic platform where virtual companions become trusted collaborators for engineers, scientists, and business leaders. In the first quarter we introduced the architecture behind this vision. This quarter we are bringing it to life. We are delivering the first agentic 3DEXPERIENCE platform powering a new generation of AI‑native experiences. And we believe this is the beginning of a profound shift in how industrial innovation will happen over the next decade.

Now let me show you what this strategy looks like in practice. Our customers operate in very different industries. They build cars, aircraft, semiconductors, medicines, consumer products. But today all of them are facing the same reality. Complexity is growing faster than ever. Products are becoming smarter, engineering is becoming more collaborative, supply chains are more connected, regulations are more demanding. And now AI is fundamentally changing how products will be imagined, developed, and produced.

To take advantage of AI, companies need first to trust the digital foundation they are building. And again, this is exactly what the 3DEXPERIENCE platform provides. It connects data, people, and knowledge. And increasingly it also connects AI at every stage of the lifecycle. This is why we are seeing momentum across every industry we serve. In transportation and mobility, manufacturers are accelerating vehicle development while connecting engineering teams across increasingly complex global ecosystems.

In aerospace and defense, the well‑established leaders are scaling their production, while at the same time the growing new space ecosystem is building its next generation of programs on the 3DEXPERIENCE platform. In high tech, companies are managing unprecedented semiconductor complexity by connecting design, engineering, manufacturing, and lifecycle in one single environment. And across consumer industries, companies are transforming product creation by connecting design, sourcing, manufacturing, and the consumer experience again on one single platform.

In life sciences, organizations are bringing together research, development, manufacturing, and patient outcomes through the virtual twins. And now with the acquisition of ArisGlobal we are taking an important step forward: a unified, AI‑intelligent platform that connects molecules, patients, and real‑world outcomes. In infrastructure and cities, customers are also using virtual environments to design, build, and operate more resilient and more sustainable infrastructure.

And finally, our mainstream innovation business continues to demonstrate the breadth of this opportunity. SOLIDWORKS this quarter delivered broad‑based growth across geographies with a double‑digit unit expansion. Why I took the time to give you this perspective is because this reflects the strength of the portfolio and our ability to attract the next generation of engineers, designers, and innovators. Let me bring this to life with a few examples.

All those customers I was speaking about are operating in completely different industries, but all of them are reaching the same conclusion: to compete in the AI era they need more than software. They really need a platform. So Mahindra & Mahindra expanded its deployments of the 3DEXPERIENCE platform on the cloud to modernize product development across its global engineering organizations, but also to build the digital foundations ready to deploy AI‑powered virtual twins at the enterprise scale.

Their challenge is very simple. They want to reduce the time to market, and the value we bring to them is obvious: it’s connecting all the engineering teams across the ecosystem. We also delivered several important competitive wins this quarter. One of them is the world‑leading memory semiconductor manufacturer in Korea selecting the 3DEXPERIENCE platform to create digital continuity across the entire product lifecycle, from engineering with CATIA, to product information with ENOVIA, to manufacturing with DELMIA.

One platform, one single source of truth, from concept to production. In consumer industries, we have an interesting case. I didn’t know this company; I discovered it. It’s very famous in the U.S., the so‑called Polyconcept North America. They are the leader in personalized goods. And what do they do? They are selecting Centric to connect product design and manufacturing and the consumer experience, while embedding AI in their innovation process to generate automatically these personalizations.

So across every industry we see again the same pattern: customers are no longer investing simply to improve today’s engineering. They are standardizing on the 3DEXPERIENCE platform and the cloud because building the digital foundation for tomorrow’s AI‑powered enterprise is becoming a must. And they are standardizing on the 3DEXPERIENCE platform and the cloud because they understand the competitive advantage will come from the data, the knowledge, and the people.

AI is an accelerator, but the platform is the foundation. This brings me to the next chapter, and today I’m extremely pleased to announce an important milestone in our life science strategy: the acquisition of ArisGlobal. You should look at this as much more than adding another software company within Dassault Systemes. It really completes our vision for life sciences. It closes a very important loop between scientific discovery, clinical development, manufacturing, and real‑world patient outcomes.

And I think this is creating something the industry has never had before: a continuous, intelligent platform powered by AI. So why does this matter? Because life sciences face a remarkable paradox. It’s the industry investing the most in research and development, but yet fewer than 1 in 10 drugs entering development reach patients. So the challenge is definitely not the lack of science; it’s not the lack of data. It’s coming from the fact that the data remains fragmented—scientific data, clinical data, manufacturing and quality data, safety data.

Too often they live in separate systems. And too often the critical decisions still depend on documents rather than connected intelligence. And AI is a game changer in this case because it can only be a powerful tool as soon as the data is there to support it. This is the reason why this entire industry is moving now towards a connected platform that brings together science, operations, and AI in one single environment. This has been our strategy for years—you know it: BIOVIA for discovery, Medidata for clinical development, DELMIA for manufacturing.

And now with ArisGlobal we add the final missing dimension, the real‑world evidence. Why is ArisGlobal so important? Because this company is a leading enterprise platform for pharmacovigilance, regulatory affairs, and safety. And it’s deeply embedded in the operations of the world’s leading pharmaceutical companies and health authorities. To give you an order of magnitude, nearly half of the top 50 pharma companies rely on them. Their software processes approximately 12 million safety cases every year among 25 million worldwide—so half of the safety cases are part of their systems.

And more importantly—and you will see why this is important—80% of those safety cases are not made public; they are private. Which basically means if you do not get access to it, you will never have the research source of the real‑world evidence to train your systems for AI. So this is the reason why this is a very important asset for the entire Dassault Systemes strategy. Now ArisGlobal has already demonstrated how AI can create tangible value with their AI capabilities.

It’s already deployed, delivering productivity gains of more than 30%. They are helping customers to identify safety signals faster to make better informed decisions. And remember, this is not only an automation; it’s intelligent decision support in one of the most highly regulated industries of the world. So what excites us the most is what happens when ArisGlobal becomes part of Dassault Systemes. Because for the first time, life sciences companies will be able to connect every stage of the pharmaceutical lifecycle on a single intelligent platform—discovery, clinical development, manufacturing, regulatory compliance, and real‑world safety.

Every new piece of evidence improves every stage that comes before. For example, the scientific models become smarter because you could anticipate some adverse effects. The clinical trials become much more informed because when you test the drug, if you already know there are adverse effects, you should do this. Manufacturing becomes more adaptive, and patient outcomes continuously improve future innovation. So instead of disconnected systems, customers again have a lot to gain with the continuous learning loop.

And this is what AI needs: not isolated models, but connected knowledge, trusted data, and continuous feedback. Looking ahead, the acquisition is about much more than expanding our footprint in life sciences. I think it demonstrates the strategy we are executing across Dassault Systemes—building an intelligent platform where data continuously becomes knowledge, where AI continuously improves decisions, and where every customer interaction makes the platform stronger.

And ArisGlobal is an important milestone in that journey. But it’s also a preview of where all industries are heading. Because whether our customers design aircraft, develop medicines, or build factories, the future belongs to the platforms that continuously learn. And this is exactly what we are building now. Let me show you how that vision is coming to life through the new AI‑native solutions we are introducing this quarter. If you remember, last quarter we introduced our AI architecture; this quarter we put it to work. The 3DEXPERIENCE platform is becoming an agentic platform, powering virtual companions and a new generation of AI‑native solutions. And this is an important distinction. Why so? Because much of today’s AI has been added on top of existing software.

You know, a kind of chatbot if you want layered over the legacy applications. We took a different approach. We built AI at the core of the platform because industrial AI is fundamentally different. It doesn't just answer the questions. It has to help engineers solve their problems, to understand the products, to understand the physics, to understand the scientific model, and it understands the context in which all the decisions are made. This is what makes AI useful in mission‑critical industry.

Now, at the center of this experience there are the virtual companions. Each is designed for a specific role. You remember Aura helps the business users to navigate enterprise knowledge and execute business processes. And to give you a concrete example, with OHA project management, a business objective can become an executable project plan up to 10 times faster. LEO supports engineers as they design, optimize, and validate complex products. And again an example: LEO Mechanical Engineer can begin with an idea, generate high‑performance manufacturable designs, while maintaining the full engineering traceability.

Marie assists the scientists with the modeling and simulations and scientific decision‑making across the research life cycle. They are not general‑purpose assistants, they are really domain experts. And each companion understands the language, the objectives, and the constraints of the people it works with. Because each one is built on a decade of engineering expertise, scientific knowledge, and industry best practice, this is how we are making a difference.

So now every quarter those companions are becoming more capable. This quarter alone we introduced more than 11 new industrial competencies. And every new competency transcends every customer using the platform. This is the power of the AI‑native architecture. Everything I just said is orchestrated by the 3DEXPERIENCE AgentIQ platform. The platform provides the governance, the security, the traceability, the digital continuity required for an enterprise‑scale AI.

And for some of our customers, you know, running on our sovereign AI infrastructure OUTSCALE, it's also an extremely important topic because it's for them the way to retain the complete control of their intellectual property while they are deploying AI in the most critical environments. This matters because many AI systems can retrieve information. Some can generate content, some can predict the outcomes. But an industrial AI must do something far more demanding.

It must generate results that engineers can trust, results that scientists can validate, results that manufacturers can certify. And you cannot certify an aircraft engine with an AI that understands only the language. You cannot develop a life‑saving therapeutics with an AI that understands text but not biology. Trust comes from understanding how the physical world behaves. And this is why our industry world models are so important. They don't simply learn the patterns from the data; they capture the scientific discipline, the engineering discipline, the industrial knowledge that governs the real world. And at the same time they are protecting the intellectual property of our customers. This is what makes industrial AI trustable. This is what allows our customers to move from experimentations to enterprise‑scale deployment. Now let me bring all of this to life with one example, and I took one I'm sure you will be very interested with: BMW.

BMW Group is a very good illustration on how industrial AI looks like in practice. Not from a CIO view, from a pure engineer view — the one doing the job on a daily basis. You know, BMW is designing increasingly sophisticated vehicles under constant pressure to innovate faster, to reduce the cycle time, and to meet even more demanding performance requirements. Take something as familiar as the car door or the central console of the car. Behind what looks very simple, you have components which have been designed with a lot of constraints: weight, crash performance, stiffness, manufacturability, cost, durability.

And the challenge is not to develop only one door or one central console; it's really to find the best design among thousands of possible alternatives. And this is where our application and AI work together. Firstly, using CATIA, today engineers can generate and analyze around 50 high‑quality design variants from a parametric model. But you know what? Rather than me telling you the story, let's show how BMW engineers are already applying it. Please launch the video.

But the robustness is a big problem for us. So if there are different lines crossing in an absurd way, there's an error, and so on. In this case, you see it here: we have a lot of different combinations, huge changes in the model, but they all work.

Christian, BMW engineer

We had a robustness of 96%. So out of 50 designs, 48 got updated and only two failed. And I also think if we have a closer look, we will find these two and will also find the problem why we had it there.

Pascal Daloz, CEO

As you saw, at the application level CATIA and SIMULIA enable engineers to rapidly explore multiple concepts while preserving the engineering intent and the design quality. This approach gives already a strong accuracy, but far from time‑consuming analysis which limits how many design possibilities their engineers could explore. So the next step is what a better orchestration across design and simulation can accelerate the design space exploration.

With our application powered by the generic frontier model over an IMMCT protocol, every high‑fidelity simulation contributes to build what we call a trusted surrogate model of the design space. Using these surrogates, the engineers can predict the performance of hundreds of new design alternatives in minutes, not hours or maybe days. And they do it by expanding the design space explored by an order of magnitude. Watch how this plays at BMW. But what really matters — we are 3DEXPERIENCE — so we want to know the experience of the design, how does it behave.

And for that we need to get the readings and the post‑processing of the simulation. So here we have now multiple use or load cases. And out of 120 simulation runs being defined, created, simulated, post‑processed, 101 have been successfully completed. So it means more than 84% of all designs have been created. And why is that so important? If you would want to do design exploration and search a certain design space, you want to have a high accuracy in order to train subsequent algorithms for predictions.

Therefore, if a great deal of the design space will not be explored, you might miss good designs and opportunities with it. As you saw, more variants can be explored, but the level of accuracy drops. So ultimately what should we do? I think BMW needs to explore the full design space with high level of accuracy. And this is where our 3DEXPERIENCE AgentIQ platform brings everything together. In the platform, users can interact naturally with LEO, our Mechanical Engineering virtual companion. And while LEO understands engineering objectives, he knows how to orchestrate CATIA and SIMULIA to leverage the industry model to explore the best design alternatives.

And more importantly, keeping every engineering decision fully traceable from the first concept to the final certifications. So here is LEO orchestrating the entire journey at BMW. Please launch the video, extend the length So with this integrated approach, you know, the full design space can be employed with 100% accuracy and the full traceability. So this is really the future of the engineering application: creates AI‑powered simulations, predicts, and the virtual companions, they do the orchestrations. And when it's powered by the AgentIQ 3DEXPERIENCE platform, you know why the engineers can explore more possibilities, make better decisions, and move from concept to certificate faster with a great level of confidence.

And this is what I'm calling industrial AI in action. It's not a vision. All those capabilities are already delivering value to our customers today. Now let me summarize before transitioning to Reuven. This quarter reflects a continued execution against our strategy. We delivered solid results in line with our objectives. Customers are deepening their commitment to the 3DEXPERIENCE platform and it is visible through the adoption of the cloud which continues to accelerate.

Third, industrial AI is moving from visions to deployments, and with the acquisition of Aris Global we are taking a major step forward in Life Sciences. I think now Reuven will lead and go through all the financial performance in detail and explain why Aris Global's financial opportunity is as compelling as the strategic one. Reuven, the floor is yours.

Rouven Bergmann, CFO

Thank you, Pascal, and good morning everyone, and thank you for joining us for our Q2 earnings call. Solid Q2 performance keeps us firmly on track for the full year. As you heard from Pascal, we are not just executing, we are transforming our company, launching new AI product categories, all while improving cash flow and the margins. This is growth and discipline together. Now let me look at the details of the financials for the quarter. Total revenue reached 1,556,000,000, up 4%, with subscription growing twice as fast at 8%.

Service revenue was up 6%. Our recurring revenue continues to perform well, rising 5% ex‑FX, and thanks to the very healthy subscription growth, subscriptions now represent 50% of our recurring revenue. This is driven by good dynamics, particularly in our Industrial and Mainstream Innovation business. Top‑line leverage and operating discipline translated to a nice uplift of 7% in operating profit and the operating margin of 30%, which is up 90 basis points ex‑FX.

EPS was 31 cents, growing at 8% year to date. That brings us to 3,065,000,000 in total revenue, growing 3%, underpinned by solid expansion, and operating profit of 5%, driving the operating margin improvement to 40 basis points to 30.1%. EPS was 61 cents, up a healthy 6% year to date. So in summary, revenue and profit are well placed versus our Q2 objectives. Let me look more closely at our recurring business growth in the quarter. We added 73 million in annualized contract value when compared to Q1. This brings total ARR to 4,443,000,000. And this includes, as you know, all active subscriptions and maintenance contracts as well as the annualized value of multiyear subscriptions. So what drove our ARR growth this quarter? We continue to grow the share of cloud bookings and the contribution for multiyear subscription deals with higher total contract values.

This broad-based momentum translated into double-digit subscription growth. In fact, over 70% of the net increase was driven by strong SaaS growth in our core industrial business, with Centric and Medidata all generating sequential growth. Turning now to our growth drivers, both 3DEXPERIENCE and Cloud were up 14% in the second quarter, driven by strong 3DEXPERIENCE Cloud growth of 60%. We saw good traction with clients adopting and expanding on the 3DEXPERIENCE platform as they look to transform their operations to capture AI-powered virtual twin opportunities in the future.

In this quarter, clients such as Mahindra & Mahindra, Orano, Venus Aerospace and Xpeng, just to name a few, highlight our momentum and competitive edge across many industries. All of the above creates a solid foundation for our future AI deployments. Adopting 3DEXPERIENCE and Cloud is a critical step to fully embrace the power of our Generation 7 portfolio. From a geographic standpoint, growth was particularly strong in Asia at 8%, complemented by solid performance in the Americas with 5% growth and flat growth in Europe.

The excellent quarter in Asia was driven by India as well as Korea and Japan, with strong momentum in transportation, mobility and high tech, specifically in Korea. While China was down in H1, we expect improvement in H2 driven by industrial opportunities. Americas showed the anticipated growth pickup over Q1, driven by very solid growth in the manufacturing industries as well as home and lifestyle and high tech. Europe had a softer quarter after strong Q1.

While the automotive sector was challenging, we saw healthy growth across key segments such as energy, industrial equipment and aerospace and defense. Moving to our performance by product lines, Industrial Innovation delivered solid growth of 5%, ensuring the anticipated uptick over Q1. This growth was led by strong performance in 3DEXPERIENCE and Cloud, with CATIA, ENOVIA and DELMIA driving the momentum overall. Key competitive wins across automotive — I mentioned the example of Mahindra — high tech, space and defense demonstrate that our platform adoption continues to gain traction, continuing from the strong first quarter.

Mainstream Innovation delivered an excellent second quarter, up 8%. SOLIDWORKS continues its broad-based momentum across geos with unit growth up double digits. It underscores our strong value proposition in the mainstream market where shorter sales cycles and time to value are essential. Centric delivered excellent performance in the second quarter, highlighted by several significant competitive wins including a global leader in retail and the global leader in sports merchandising and licensing.

Both are US companies, and this reinforces a key point: Q1 was not an outlier. Centric sits at the center of consumer-driven transformation across food and beverage, retail and sports apparel. Powered by an integrated platform and AI, revenue performance was in the high-teens growth, which we expect to further normalize in H2. Now to Life Sciences, and here, as anticipated, Q2 revenue growth was impacted as a result of low booking volumes across 2025 and the Moderna impact, driving Medidata to minus 3%.

This was factored into our model for H1. An important point to highlight is the shift in the partner business model in light of the deal we signed with WCT (Worldwide Clinical Trials) in Q1 — so last quarter — but what it highlights is that we are stabilizing the growth trend for CROs, and overall it supports our growth in the volume market. The momentum in our mid-market remains healthy, and as discussed last quarter, for 2026 we expect H2 to improve over H1 as we are building the annual run rate momentum to support sustainable recovery.

And as you heard from Pascal, now a few words to ArisGlobal. As I'm discussing the life sciences sector, with the acquisition of ArisGlobal we are entering the next phase to transform the life sciences industry, and let me provide a few additional points that help to better connect the strategic rationale as presented by Pascal with a financial profile and value creation. This acquisition is a game changer. Today ArisGlobal is the primary AI-enabled life sciences safety and regulatory platform, providing a mission-critical system of record.

The market is projected to reach 7.5 billion by 2030, growing at a double-digit rate where, importantly, software and AI capture a larger share of spend every year, and it represents less than 40% of the TAM. Today ArisGlobal brings an outstanding financial profile, $175 million in estimated 2026 revenue, a highly recurring SaaS model, and an operating margin profile which is consistent with Dassault Systemes. In doing this transaction we are establishing the industry's first continuous real-world evidence loop spanning the entire therapeutic lifecycle, and by uniting ArisGlobal's compliance data with our molecular design, clinical trial and manufacturing domains, we transform the life sciences industry from fragmented, document-heavy workflows to a unified, model-based intelligence platform. Now coming to the transaction terms, we structured this acquisition with disciplined terms. We will pay $1.8 billion in cash at closing, with up to $200 million in additional consideration tied strictly to AI-related revenue milestones over the next three years. We will fund this transaction with balance sheet cash and we are at the same point in time preserving our robust financial flexibility.

It's a compelling investment case. ArisGlobal brings an attractive financial profile with good standalone revenue growth and margins and, in addition, revenue synergy opportunities are mainly driven by cross-selling to the mid-market and leveraging the AI platform to expand our reach to capture the entire drug lifecycle. Consequently, we expect the transaction to be both revenue and EPS accretive in the first year post close. We aim to close the transaction by late Q3, early Q4 of 2026, of course subject to customary closing conditions and regulatory approvals.

We look forward to welcoming ArisGlobal's exceptional leadership team and 1,300 global employees to the Dassault Systemes family. Upon closing, they are committed to joining us and together pioneering the next chapter of life sciences innovation. Welcome, guys. Now let me turn back to our Q2 results, specifically to cash flow performance. We generated strong operating cash flow in H1, 1,237,000,000, up 8% year over year and 11% ex-FX. This was driven by strong operating performance and working capital which was up slightly on higher billing activities.

A brief comment on Q2: operating cash flow was mainly impacted by two factors. First, collections that shifted to July, which have all been secured in the first two weeks of Q3 — so it's only a temporary effect — and second, we had lower accrued compensation. Free cash flow was up 13% ex-FX in H1, driven by strong operating cash flow which was mainly used for dividend payouts and the repayment of commercial paper. Overall, this first half performance demonstrates the strength of our cash generation.

As a result, cash conversion for H1 reached 134%, an improvement versus 123% last year, and important to note we remain on target for a full-year 2026 cash conversion. This consistent transition of our business towards subscription and cloud creates an opportunity for us for continued improvement in cash conversion. To complete the picture, cash and cash equivalents reached 5,660,000,000 at June 26th, reflecting a half-year increase of 1,535,000,000.

It was 785,000,000 in Q2. This was positively impacted by the successful placement of the new 1 billion senior bond which we did in June, the proceeds of which we will be using to refinance the upcoming maturity of 900 million due in September 26th. The net cash position strengthened to 2.3 billion, plus 750 million during the first six months, and you can see that this has also put us in a solid cash position to fund the ArisGlobal transaction from our own strong balance sheet.

Now let me turn to our objectives for 2026. We enter the second half of the year with a solid foundation, and we confirm our full-year outlook: total revenue of 6,296,000,000 to 6,416,000,000 representing 3 to 5% growth ex-FX; operating margin in the range of 32.2 to 32.6%; and EPS of 1.30 to 1.34, representing 3 to 6% growth ex-FX. Now for Q3, we expect total revenue in the range of 1,497,000,000 to 1,537,000,000, up 3% to 5% ex-FX, with software revenue growing 3 to 5% and services up 4 to 8.

We target an operating margin between 31% and 31.1% and EPS of $0.30 to $0.31, and it's growing between 4 to 7% ex-FX. These targets are based on FX assumptions that are consistent compared to the beginning of the year: 1.18 for dollar to euro and 170 yen to euro, and the tax rate assumption of 17% for Q3. Finally, to note, we will reflect the impact of the ArisGlobal acquisition following the close of the deal, which as mentioned is expected in late Q3 or early Q4.

However, the financial impact on 2026 should not be significant given the timing of revenue contribution and also the timing of cash payment of this acquisition. Now, in summary, we delivered a solid first half in line with our objectives and we confirmed full-year guidance objectives. Our growth drivers show the strategy is working: subscription growing twice as fast as total revenue, and 3DEXPERIENCE and Cloud are accelerating. We remain squarely focused on execution as we enter H2, with operating discipline to drive solid margins and strong cash conversion.

This gives us the foundation to invest in long-term growth, accelerate our AI strategy and create tangible value for clients, employees and shareholders. Now thank you for listening, and now Pascal and I look forward to take your questions.

OPERATOR

Thank you. Dear participants, as a reminder, if you wish to ask a question, please press star-1-1 on your telephone keypad and wait for your name to be announced. To withdraw a question, please press star-1 and 1 again. Please stand by while we compile the Q&A queue. It will take a few moments, and now we're going to take our first question. The first question comes from Laurent d'Heure from Kepler Cheuvreux. Your line is open. Please ask your question.

Laurent d'Heure, Analyst at Kepler Cheuvreux

Yes, good morning, gentlemen. Thank you for taking the question. I have two. The first one is, if we look for, I would say, the next three to five years for ArisGlobal, would be interesting to share your view on the growth potential of this acquisition and where you will focus on, what are the most promising segments that Aris is targeting in terms of sales outlook. And my second question is on the transport and mobility segment. You keep winning deals, but at the same time the news flow in the space is really depressing.

So, Pascal, it would be nice if you could share with us your view for the next, I would say, three to four quarters about this transport and mobility unit, whether it's going to be a drag to your revenue or not. Thank you.

Pascal Daloz, CEO

Thank you, Laurent. And thank you for putting me on the spot. So let me start with your first question, which is a very important one. Obviously, you know the regulatory and safety market, as I was saying, is anyway growing at double digit. And the proof of what I'm seeing, if you look at the number of adverse events which have been traced and investigated, in fact, is increasing. I mean the volume is increasing at double digit every year. So that's the reason why at least there is no reason for the company to do as a standalone below the growth of the market.

Where are the levers coming from? There are three levers. You remember in my introduction speech I said Aris Global is covering only half of the top 50 pharmas; Dassault Systemes has a presence in most of them. So there is a way, thanks to the unified intelligence platform, to displace some of the competitors which are already in place. And you know them, some of them are challengers, some of them are well established for a long time, and they have old architecture, old product lines.

And I think we have definitively an opportunity on this. The second point, which is more important, is the mid-market. Aris Global is extremely well positioned for the large pharma and biotech and med devices. However, the footprint they have established on the market is quite limited for the mid-market. And you remember Aris Global is having 200 customers; we have 4,000 customers. And the difference is coming from the fact that we are addressing extremely well this segment of the market.

And this is where I think the go-to-market is already in place. There is no additional investment we should do except basically enabling this salesforce to do the promotions. So we have a significant lever on this. And this is an important point because for the regulatory and safety decision process, you know, it's not the clinical ops guy or the head of engineering, head of development who are making the choice. It's usually the public affairs or the medical officers.

Aris knows how to speak to those guys. Why is this important? Because usually the selection of the tools happens when you do not have yet your molecule on the market. And this is exactly where the synergy with Medidata is so important, because with Medidata we are already used for several years before the decision should be made. And this is again the lever we can bring. Another lever is obviously the product side and mainly the AI side. You remember in my speech I emphasized the fact that in Aris’ system of record, you have almost half of the worldwide safety cases.

And this is extremely important because it's a unique base to do the learning for the AI engine. And if you combine this with the Medidata assets, which is more than 20 years of clinical data we have collected across many different therapeutic domains, at a point where by now more than 70% of the drugs being approved every year rely on our platform, we have access to this data to train the systems. So if you combine the two, it's a unique asset we can leverage to accelerate the AI strategy and to build the world model of the life sciences industry.

So this is really where the growth will come from. But I will let Rouven, you know, quarter after quarter, guide you on how much you could expect on a quarterly basis. But I'm very confident on the trajectory of the growth, as you could feel, I guess. The second topic related to transportation and mobility. Let me share something with you. We grew 6% this quarter. I repeat, we grew 6%. So you can argue that this industry is suffering. It's the reality.

And you can argue that probably we are impacted in Europe. This is also a reality. But we are capturing market share in the rest of the world. We spoke about Mahindra, Mahindra, Rouven was speaking about XPeng. So all the newcomers, all the ones having basically the good momentum, they are our customers and that's basically what we do. We are in fact with them accelerating our deployments. And they have exactly the same issues. And the others, at some point they need to integrate their suppliers, they need to trace and to do the lifecycle, they need to accelerate the simulation using AI capabilities.

And this is again where we are relevant. So I will not basically conclude that transportation and mobility is a dead sector for the ecosystem. It's not. We still have a lot of opportunity to expand and not only because you have newcomers or new spaces, but also with the incumbents. They need to transform themselves. You remember me telling you that to develop a car on average in Europe takes 52 months, whereas the best, especially the Chinese, they do it in 18 months.

The only way to reduce the cycle is to have the digital continuity across the entire lifecycle. So it's not becoming an option, it's a must, including for the large incumbents you are referring to. That's it for the two questions. Great, thank you.

OPERATOR

Thank you. Now we're going to take our next question. And the question comes from the line of George Webb from Morgan Stanley. Your line, please. Ask the question.

George Webb, Analyst at Morgan Stanley

Hi. Morning, Pascal, Rouven. Congratulations on the deal, and I've got a couple of questions, please. Firstly, just on the core business performance, you obviously delivered towards the upper end of your guidance for the second quarter. But if you could just talk a little bit about what you see around deal closures in Q2 within that performance, perhaps China was an area where you saw some of that. I mean, outside of China and Asia, the growth was still very strong.

So also kind of curious how you think Asia performed versus your initial expectations in Q2. Secondly, on Aris Global, can you just scope out a little bit what the revenue mix is of that business between software and services? And also from your discussions with Nordic Capital, could you talk a bit about what they've been focused on in recent years? It looks like they've probably done a subscription transition or accelerated that. And to what extent is that giving you an additional layer of visibility over Aris Global's growth over the coming years?

Thank you.

Rouven Bergmann, CFO

If I can start. Pascal?

Pascal Daloz, CEO

Yeah, please.

Rouven Bergmann, CFO

So, on the business mix and the business performance and deal closure activity, we had good line of sight in the second quarter and we came in as we had planned, so we didn't see any risk of slippage that would impact our performance for the quarter. Of course, you always have some puts and takes, how we say, but they have to be managed and we did well in Asia. You are right, we had an excellent performance with 8% thanks from growth in Korea, but most notably India, solid performance in Japan and AP South; however, China was down. That was also not a surprise to us. H1 we knew was a tougher period. We are entering now into H2 where we have a good pipeline to support returning to growth. And in China, sometimes the visibility and predictability can be challenging, but we also have to make sure that when we operate there, we are operating with a strong line of sight and are closing deals on our terms and not trying to be under pressure. And so this flexibility is important and we apply that.

So we are confident about our growth in China for the second half of the year. And overall, you mentioned Europe. I mentioned that as well, with a tough auto sector. But nevertheless, the teams performed well in closing deals in the last two weeks of the quarter. So what was expected was done, so we didn't face any volatility from that. This I think was well executed. And now in Q3 we are also expecting Europe to return to growth. Americas had very solid performance, improving visibility essentially week to week over the quarter.

And there also I think good line of sight and good management of pipeline. So well done by the team in America as well. So overall things are under control. Now to the revenue mix of Aris Global, and your question regarding what did Nordic do and focus on in the last two, three years. The revenue mix is 85% recurring, so a high share of subscription SaaS revenue. So there's only 15%-ish which is services. So it has a high recurring share and it's clear the business model transition has been done and it's implemented.

Nordic was, together with the Aris management team, very much focused on driving that recurring business growth, building the AI roadmap with tangible outcomes in their industry. Today they are the leaders in AI in safety and compliance. This is done, they're generating revenue, they're seeing real productivity gains from clients. So these are the two things I would highlight. Other than that, I think the company is well run across three main locations: US East Coast, mainly Boston area; London; as well as in India, where there's a strong footprint in terms of service and operations. That's as much as I can say. Pascal, do you have things to add?

Pascal Daloz, CEO

No. And maybe one additional comment. From a product architecture standpoint, it has been completely re-architected, so it's really a full cloud and SaaS model with multiple instances. So there is no technical debt, if you want, we have to take care of for the future. So this is also an important point to move forward and to accomplish the synergy we want to do.

George Webb, Analyst at Morgan Stanley

That's great, thank you. Maybe, Pascal, I'd ask you one follow-up to that. When you think about the integration of Aris Global into Dassault, will you run it as a standalone business within Life Sciences for the foreseeable future, or would you look to integrate it into Medidata? Sorry, I lose my voice.

Pascal Daloz, CEO

It's okay. So, in fact, it's a mix of both. Let me tell you why. And again we have time to come back to you with the details between the signing, which was yesterday, and the closing, as you say, Rouven, will be probably somewhere October timeframe. But to make it simple, again, we have a lot of synergy. From a go-to-market standpoint, we have already the go-to-market; it's independent from Medidata, from BIOVIA, from all the brands. So I think it's relatively easy to push Aris’ product line as part of this go-to-market.

From a development standpoint, you remember the slide I presented? You have three stages, you have the system of record. So it's a system of record by itself and it will basically coexist along with Medidata, with BIOVIA and DELMIA. So this is in a way a standalone approach, except that at some point we need to have common development processes, common maintenance and support systems. And then after you have the AI story, and this is really where we probably need to bring the team together in order to have a unified AI platform crossing all the different systems of record. And that's what I'm planning to do. And last but not least, probably an important point for you guys: I am creating an executive position at the Dassault Systemes Executive Committee level to oversee the entire life science domain. Why so? Because it was done by Rouven and myself for the last few years and I think we have many things to do now and it's important to have someone dedicated not only to drive the integrations, but also to drive the development, the positioning, to entertain the executive-level relationships. And this is something I am currently doing.

George Webb, Analyst at Morgan Stanley

That's great. Thank you very much and good luck for the second half.

Pascal Daloz, CEO

Thank you.

Rouven Bergmann, CFO

Thank you.

OPERATOR

Thank you. Now we're going to take our next question. And the question comes line of Michael Briest from UBS. Your line is open. Please ask your question.

Michael Briest, Analyst

Thank you. Good morning. Just in terms of the Nordic—sorry, Aris Global—I think Nordic Capital have it on their website with revenues of 150 million euros last year, which is just shy of $170 million. I appreciate it's not a euro business or 100% dollar business, but can you talk about that implied growth rate of sort of mid single digits? It doesn't seem to accord, or is some definition of revenues which is different. And then in terms of the average customer spend, I know not everyone's going to be the same, but it's less than a million dollars each if you've got 200 customers.

Can you talk about the span there and maybe what the largest customers are? Because I know Medidata is in the tens of millions, but then the revenue opportunity within those customers—customers that you have today—is that fully maxed out or could you get more from them? And then good performance on margins on headcount for the second half—will that start to grow again? Or are you sort of leveraging AI and other efficiency measures to sort of keep that flattish from here on, and how do you think about headcount?

Thank you.

Pascal Daloz, CEO

You take it.

Rouven Bergmann, CFO

Yes, Michael, I'll take some of the questions. I guess we'll go back and forth, Pascal, but I'll start. So on your revenue question, Michael—yes, FX of course is a factor. The revenue outlook of $175 million that are provided is based on the visibility as of at the end of Q2. So we are not giving forecasts that go beyond, because we don't run the business, we do not control it. I can only say what we see today in the books, which is pretty much actualized cost for 2026.

And I cannot... We have analyzed and reviewed there of course the schedule and growth over the last five years and it's solid double digit. So we are... that's what we are planning for and that's why the business, as we integrate it into our financials, is revenue growth accretive. On the revenue opportunities within clients—I think Pascal, you alluded to that—we have the opportunities to expand with our large pharma clients. The AI expansion opportunity is real.

We are connecting not only to safety, regulatory, but also quality and connecting it to clinical trial.

Pascal Daloz, CEO

And I think the question from Michael was, if you do an average, you divide the revenue by the number of customers, it's a million in average. You're right, Michael, but at the same time, you know, there is a distribution. So the question probably behind your question is, do we already have customers spending 10 million-plus? Not yet the case, yes. Do we have—with Aris Global, I mean on the Aris Global scope—do we have customers spending more than 5 million?

The answer is yes. So just for you to have this in mind. Now, where are the levers? Reuven made a very important statement when he said the TAM is 3.5 billion, of which only a fraction is captured by the technology today. So the vast majority of the spending for the safety cases and quality management is still manual, and you have specialized companies doing business process management, and also you have a lot of large pharma doing it in-house. This is again where AI is coming at stake.

And the Navax products, which are the ones Aris has developed, have been already on the market. And we already have some feedback on the market that this is extremely helpful because they have developed agents who are capable to do not the full manual process, but most of it. So it's a way for customers to re-insource some of the job they were subcontracting to services companies, and we take obviously a share of it. And there is a way also, as you say, to do more with less.

And this is also the second lever we have. And this is really only, if you want, on the scope of Aris Global—we could expand the share of wallet. And last but not least, you have all the synergy I was explaining upfront, which is again a way to continue to nurture the developments and to size the deal up. So pretty confident about this. And again, that's probably one of the values of the combination of the two companies. And then the third question on the margin and headcount—coming back to that.

You're right, headcount is slightly down year over year. And also for the first six months we are leveraging, of course, AI. We are not replacing one for one. I repeat what you say: we are doing more with less or the same. Certainly we have been building a very good track record in research and development, but also in customer support and in supporting functions in G&A. And we will continue to do that because this gives us the flexibility to invest into future growth, which we are doing.

And I think that's what is expected. We're confident about the margin outlook.

Michael Briest, Analyst

Yeah, thank you. Maybe just to follow up on the midterm targets. I mean the revenue side is pretty challenging, I think we would all agree, but the margin ambition was fairly sort of gradual. Do you feel there's opportunities with AI that maybe you didn't appreciate a year or more, whenever you did the last CMD, that give you greater confidence on that profit progression?

Pascal Daloz, CEO

Yes, yes, absolutely. We have that opportunity. But also we have the opportunity to re-accelerate the top line. And as you're re-accelerating the top line, we will have a bigger lever on margin expansion because the cost or the OPEX growth should be contained.

Michael Briest, Analyst

Okay, thank you.

Pascal Daloz, CEO

So we do not want to cut. Right. We want to invest and grow, and we want to expand this profitable growth. That is the formula. Thank you. Thank you, Michael.

OPERATOR

Yeah, thank you. And now we're going to take our final question for today, and it comes from the line of Balaji Tirupati from CT. Your line is open. Please ask your question.

Balaji Tirupati, Analyst

Hi, good morning. Thank you for taking my questions—two from my side as well. If I may. Firstly, on life sciences and Medidata, could you share color on the return to positive ARR growth? How was the ARR growth adjusting out the Moderna contract? And secondly, with positive ARR growth, should we expect Medidata revenue to return back to positive growth in second half? And the second question: if you could please share your view on how you expect to see some of your leading customers partnering with AI labs like Mistral.

And in that context, how is your own relationship with AI labs evolving when they are also coming out with AI-CAD tools? Thank you. You take the first one.

Rouven Bergmann, CFO

Yes, thank you for your question. Some color on the positive ARR momentum related to the life science and Medidata. Yes, ARR is back to growth for Medidata, so we have positive contribution in net ARR. The momentum is coming from the mid market, and we also see that the partners' activity is increasing. So we do not have that headwind any longer that we had the last two years. So this market is stabilizing—it's important. But mid market is very consistent.

We had also, as you rightfully point out, the headwind of Moderna in the large enterprise, which is now more behind us after H1; there's only marginal impacts in the second half of the year. So the ARR growth for Medidata has turned positive, and in H2 we expect another step up in terms of ARR contribution from Medidata. From a sequential standpoint, it's not yet at the level of course of the subscription ARR for the company, because the subscription ARR for the company is called double digit, as I mentioned in my prepared remarks, while the total ARR 6%—subscription ARR is in the low teens of growth, which is by the way very aligned with our growth in cloud revenue, which is also in the low teens this quarter. And so you see that our growth drivers are lining up, and we are driving the momentum shift and the business model shift very consistently. And we are now reaching a point where subscription revenue as a share is starting to exceed the support revenue, and that will support our ARR growth overall.

Pascal Daloz, CEO

Okay, coming back to the second part of your questions—are we a competitor or partner with the providers of the frontier model? It's both. Why so? Because on one hand, you know, we are vertically integrated but horizontally open, and you have seen this in the architecture slides, which means I do not intend to redevelop an LLM. There is no value, because what we are focusing on is really on the world model. So we are by design multi-LLMs. And this is important because for sovereignty reasons, you know, Mistral is the sovereign solution for Europe.

But in China it's another one, and you could be sure that in the US and the rest of the world it would be the same. That's point number one. Point number two—that was exactly the purpose of my speech for using BMW as an example, because BMW was using Mistral. And if you remember the case number two whereby you use a frontier model with an MCP protocol to pilot the applications, there is a value, which is that you can automate certain workflows. But I hope you have understood—and it's not me saying it, it's the people doing the job, the real ones, not the CEOs, the people who on a daily basis need to produce and design the car—they are saying it's not enough, because having the ability to orchestrate the workflow automatically is helping to investigate much more design alternatives, but the accuracy is low. So what does it mean? It means it costs you a fortune to run the frontier model with the tokens, and you are creating an extra value in terms of number of alternatives which are really fitting the requirements.

This is not the way to go. And again, if you have listened carefully to what I said, the last approach is using the 3DEXPERIENCE Agentic platform, leveraging LLMs for what they are good at, including Mistral, but using the vertical integration with the world model, with our companions, with our applications, to deliver the best of both worlds. So believe me, I have spent enough time with many of the customers you are referring to, and what I'm telling you is extremely valid.

It has been, by the way, validated by the specialists. And last but not least, everything you do, you have to certify it and you need to trace it. And this is what it means if you want to put AI at scale within an industrial company. So if you do not have an equivalent to the 3DEXPERIENCE platform, you cannot do that. You simply cannot. Because there is no way that if your system is working like a black box you will be able to be certified. You need to prove—by basically following the steps which have been defined by the regulations—you need at each step to provide the end result that someone else could understand, recreate the reasoning, and basically find the same results. Otherwise you are not considered for the purpose of the job. So in summary, the LLMs—they are good to read text, to generate contents, whatever the content is: a text, an image, a code. But they are not good to generate physics, biology. They are not good to produce physics and biology. And this is where I think we are making a big difference. So it's a little bit of both.

Balaji Tirupati, Analyst

Very clear. Pascal, and thanks a lot. Pascal and Reuven, thank you.

Pascal Daloz, CEO

Thanks for your questions. Okay, so thank you, all of you, for your questions. I think what you have heard today is our strategy is progressing on multiple fronts. I think first we are, as you say, Rouven, we are executing with discipline; the results are solid. Our customers are expanding the use of the 3DEXPERIENCE platform, and cloud adoption continues to accelerate. And this is giving us confidence not only in the pace but also in the consistency across geography, across industry, and across companies of all different sizes.

I think second, we are advancing our life sciences ambition and strategy. Our vision, which has always been since the beginning to virtualize the entire lifecycle to help to improve patient outcomes, is making a step forward with Aris Global. Now we are creating this unified AI intelligence platform called Connecting molecules, patients, and real-world outcomes. This is unique on the market. This is really game-changing. And by doing this we are closing the loop between discovery, development, manufacturing, and evidence.

And third, I think we are turning industrial AI to real value for the customer. I mean the 3DEXPERIENCE platform is becoming an agentic platform. We deliver it to the market. This agentic platform is powering AI-native applications. The Companion is a category of them. They are on the market and we continue on a quarterly basis to enrich them with competency, with new skills. And this is how we are building the competitive advantage. And last but not least, I see we are capturing how the industrial world works, and we make AI knowledge much more accessible with an industrial platform.

So thank you very much. Hope to see you on the road. If not me, it will be Rouven and Marie. And if I do not have a chance to see you in person, enjoy the summer break. Thank you so much.

OPERATOR

This concludes today's conference call. Thank you for participating, and we'll now disconnect. Have a nice day.

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