SimScale, a cloud-based engineering simulation platform, has published its annual research examining how artificial intelligence is transforming engineering workflows globally. Drawing on responses from 350 engineering decision-makers across the US, UK, and Germany, the study highlights a significant maturation in how organizations are deploying AI — moving from isolated pilots toward deeply embedded, operational use.
One of the report's headline findings is that teams leveraging AI-powered workflows explore nearly four times as many design alternatives compared to those using traditional methods. This isn't simply about doing the same work faster; it fundamentally widens the creative and technical possibilities available to engineers during product development.
The study found that infrastructure readiness is the primary driver of successful AI adoption. Three-quarters of organizations with advanced AI programs point to cloud-native platforms as a critical foundation, while 70% highlight secure data governance as essential for scaling initiatives effectively.
The commercial benefits are just as compelling. AI-enabled teams reported handling simulation requests roughly 2.8 times faster than conventional counterparts, with bid and quote turnaround times approximately three times quicker — a meaningful competitive edge in fast-moving markets.
A rise in autonomous systems was also revealed in the study. AI copilots are now widely embedded across product development stages, with adoption rates between 67% and 76% depending on the phase. Fully autonomous agents, however, remain rare — deployed by only around 10% of respondents — reflecting the high-stakes nature of engineering decisions where safety and compliance still require human judgment.
The overarching message: AI in engineering has crossed from experimentation into measurable, scalable impact.