Engineering simulation (ES) has long been a powerful catalyst for better, faster, and more cost-effective product development. Its benefits are well established: Virtual testing reduces the need for physical prototypes and accelerates time-to-market. It enables teams to explore designs more thoroughly and resolve issues earlier in the development cycle. In industries characterized by rising product complexity and intensifying performance expectations, simulation has become an indispensable part of the modern engineering toolkit.
Over the past decade, artificial intelligence (AI), specifically engineering AI (including gen AI) have begun reshaping industrial systems more broadly. Automotive manufacturers already deploy AI-based predictive maintenance to extend service intervals and optimize repair interventions based on vehicle sensor data. Aerospace players are using engineering AI to accelerate the design of lightweight components. These examples highlight a broader shift: AI is not just automating discrete tasks; it is also transforming engineering activities at the systems level.
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