Dassault Systèmes is a French technology company that develops virtual twin, 3D design, engineering, and simulation software that helps organizations design, test, and optimize products, processes, and systems across industries ranging from aerospace and automotive to healthcare and infrastructure.
You’ve been with Dassault Systèmes for 13 years. Could you briefly walk us through your career journey and the company’s evolution during that time?
Before joining Dassault Systèmes, I worked as an engineer in the aerospace industry. I have always loved science, innovation, and technology, but I came from the physical world, where you design and build complex machines. What attracted me to Dassault Systèmes was the connection between that physical world and the virtual world.
When I joined, I was responsible for one of our largest aerospace customers and worked on the first virtual twin of the Airbus A350. That was when I saw how virtual worlds could improve real-world products. Later, I led transformation initiatives as the company grew from around 10,000 employees to 25,000. We redefined our operating models and methods, essentially virtualizing our own operations. Today, I sit on the Executive Committee and lead strategy, helping bring our long-term vision to life across manufacturing, life sciences and healthcare, and infrastructure and cities.
You have spoken about repositioning Dassault Systèmes from a software company to an IP generation and management company. What does that mean in practice, and how does AI enable or accelerate this transformation?
For more than 40 years, Dassault Systèmes has been an invisible force behind products ranging from aircraft and cars to consumer goods and therapeutics. When we say we are moving from software to an IP generation and management platform, it is not a branding exercise. It reflects a real shift in where value is being created.
The economy is evolving, and value is increasingly moving away from the physical product itself and toward the intellectual property behind it: knowledge, know-how, data, and design intelligence.
Our platform helps customers generate new IP, not simply store data, while also protecting, tracing, and managing that IP. We now talk about IP Lifecycle Management rather than Product Lifecycle Management. In a world shaped by AI and sovereignty concerns, intellectual property is both a company’s greatest competitive advantage and a potential vulnerability, so mastering it has become critical.
How does AI build upon Dassault Systèmes’ virtual twin technology to accelerate innovation and decision-making?
Everything we do is built on virtual twins, which form the foundation of our approach. Unlike a simple digital replica, a virtual twin represents not only an object but also its behavior. For example, when designing an aircraft, you need to model how every system behaves, how components fit together, and how they perform under different conditions.
On top of these virtual twins, we have introduced AI-powered virtual companions. These companions are rooted in industry knowledge and help users reduce time to knowledge and time to market. We have Aura for business, Leo for engineering, and Marie for science. They help users test thousands of scenarios, recommend materials, account for regulations, and provide knowledge based on prior experience. The human remains in control, but innovation cycles become faster and decision-making becomes more informed.
How does Dassault Systèmes’ industrial AI differ from traditional large language models?
The difference between general-purpose AI and industrial AI is that industrial applications cannot tolerate hallucinations. We need to understand causality, why things happen and how they happen. In industry, AI must account for standards, regulations, materials, behaviors, and operating conditions. Having worked with more than 400,000 customers, we bring that deep industrial knowledge into AI systems, which is where we believe we create real value.
Many organizations struggle with the non-deterministic nature of AI. Is solving that challenge part of what Dassault Systèmes is doing?
Yes, and this becomes even more important in areas such as robotics and physical AI. Unlike text-based AI, physical AI must obey the laws of physics, including gravity, friction, and material constraints. If a robot makes a mistake, it can break equipment or even injure someone.
This is where virtual twins become essential. By creating AI-powered virtual representations, robots can learn from highly accurate synthetic data and train in virtual environments before acting in the real world. This creates a continuous learning loop while avoiding costly mistakes. At the same time, we focus AI on the most critical bottlenecks for customers. Otherwise, the benefits may remain incremental rather than transformational.
How are your customers approaching AI adoption, and what factors are driving successful implementation?
The willingness among our customers is clearly there, provided that AI can address a meaningful challenge at scale. We work closely with customers through co-creation because AI solutions must incorporate both their intellectual property and ours while ensuring that their data and knowledge remain protected.
Adoption itself is not the difficult part. Once people experience trustworthy AI, they generally want to use it again and again. The key requirement is trust. Customers need confidence that their knowledge is secure and that the AI is grounded in reliable models. When those conditions are met, the appetite for adoption is very strong.
What are your key priorities over the next 12 months, and which innovations excite you most?
One of our biggest priorities is our partnership with NVIDIA, which we announced in February. NVIDIA’s computing power sits at the heart of the AI revolution, and they position themselves as an AI factory while we position ourselves as a virtual twin factory.
Together, we are building the platform architecture for industrial AI. This partnership is central to our roadmap because it enables us to address virtually every industry. Over the next year, we will bring more products to market that combine generative experiences and virtual companions with NVIDIA’s capabilities, delivering the most advanced industrial representations possible.
