At the 3DEXPERIENCE World 2026 conference, Dassault Systèmes emphasized artificial intelligence and virtual twin technology as central elements of future engineering and manufacturing workflows. The company is advancing a strategy to embed AI deeply into its 3DEXPERIENCE platform so that AI becomes not an add-on but an intrinsic part of design, simulation, and lifecycle processes. This approach layers physics-based intelligence and industrial context into digital models, enabling engineers to predict real-world behavior early in the design cycle, says Digital Engineering 24/7.
A highlight of the event was the expanded partnership between Dassault Systèmes and Nvidia, aimed at creating a shared industrial architecture that fuses virtual twin capabilities with accelerated computing and validated “industry world models.” These models merge virtual twin technology with AI that understands physical laws, materials, and systems, giving designers and manufacturers tools to explore complex scenarios before physical prototypes are built. The collaboration is intended to support a wide range of sectors, including engineering, materials science, and even biology.
AI companions, that is, specialized intelligent agents trained on industry-specific data and on a company’s own design context, also featured prominently in discussions. These companions serve as interactive assistants within engineering workflows, helping users manage projects, validate manufacturability, interpret performance trade-offs, and even generate initial geometry from simple inputs. By embedding expertise directly into the platform, the aim is to reduce repetitive tasks and enable engineers to focus on higher-level decision-making.
Virtual twins, defined as digital counterparts of physical products and systems, are poised to evolve from static models into dynamic, high-fidelity simulations that inform design, production, and operations. When paired with AI companions, virtual twins create an environment where simulations and evaluations can be conducted rapidly and iteratively, lowering barriers to simulation adoption and speeding up innovation cycles.
Taken together, the announcements pointed to a future where digital knowledge and AI-driven insight become as important as traditional CAD data, shifting the engineering landscape toward more predictive, collaborative, and intelligent systems.