Dassault Systèmes Highlights The Future Of Engineering Design In The AI Era

The physical infrastructure underpinning AI – primarily data centres – is rapidly emerging as one of the most critical segments of the global economy. Hyperscalers alone are expected to invest approximately $5 trillion in AI technology and data centre infrastructure by 2030, pointing to the sheer scale of demand now facing the architecture, engineering and construction (AEC) and engineering, procurement and construction (EPC) sectors. As AI adoption accelerates, delivering the physical infrastructure that supports compute capacity has become a critical constraint. This is forcing engineers to rethink how they design and deliver increasingly complex facilities.

The central takeaway from Dassault Systèmes’s 2026 AEC Global Summit in Paris is that this is not a short-term surge, but rather a structural shift in the market. Established, project-led approaches are struggling to keep pace with requirements for speed, scale and technical performance, exposing inefficiencies in fragmented workflows, bespoke design practices and late-stage validation. In response, discussions at the event highlighted a transition to more efficient delivery models. From an engineering design perspective, three themes stood out:

• Simulation is moving to the centre of design.

  The Dassault Systèmes MODSIM approach integrates modelling and simulation into a continuous engineering workflow, enabling teams to assess multiple design options using physics-based analysis from the earliest stages of the process. Tools such as CATIA and Dymola support multi-domain modelling, bringing together mechanical, electrical and thermal behaviours within a single environment to reflect real-world conditions. This is particularly important in the design of data centres, where cooling, power and structural elements must be optimized simultaneously under tight constraints. These facilities are increasingly treated as a ‘system of systems’, with close alignment between requirements, design logic and physical outcomes.

• AI is becoming an embedded engineering capability.

  The role of AI in augmenting engineering workflows is growing, particularly in generative design and automation. Dassault Systèmes emphasizes the use of science-based AI tools, grounded in engineering knowledge, in tasks such as extracting requirements from files, automating design generation, running iterative analyses and supporting compliance. One of its ‘virtual companions’, Leo, embeds domain expertise directly into the software environment, helping engineers solve technical challenges and streamline complex processes. Taken together, these developments position AI as a force multiplier in industrial design engineering, accelerating workflows while keeping outputs grounded in validated engineering principles.

• Engineering continuity is being rebuilt on unified data models.
  A persistent challenge in the AEC and EPC spheres is fragmentation between design and construction workflows, which can result in inefficiencies, rework and lost knowledge. A unified data backbone is the clear solution, connecting design, simulation and delivery within a single environment. Built on its 3DEXPERIENCE platform, Dassault Systèmes’s ‘one model, one platform’ approach enables full lifecycle traceability by linking engineering deliverables and downstream processes such as procurement and construction sequencing. It ensures consistency between core deliverables such as P&IDs and 3D models, and connects engineering data directly to construction execution. This allows teams to virtually rehearse installation strategies and improve planning before work begins.

The demand for AI infrastructure is acting as a catalyst for rapid advances in engineering design approaches. Examples from firms such as DPR Construction highlight how prefabrication and offsite manufacturing are becoming viable at scale when supported by engineering simulation models and automation tools, with data centres emerging as a primary use case. Modular construction therefore becomes not just a method of building, but a direct outcome of engineering maturity and data continuity, enabling assets to be manufactured, assembled and deployed with great speed and repeatability.

To read more about how simulation-led design, AI-driven engineering and unified data models are transforming industrial design and engineering software, see Verdantix Smart Innovators: Engineering Design Simulation Software and Verdantix Market Overview: Industrial Engineering, Design And Construction Software.