Dive Brief:
- About 69% of respondents to a new survey by SimScale reported adopting AI-enabled copilots and assistants across their engineering workflows. Some are also starting to use autonomous AI agents, especially for simulation and computer-aided-engineering.
- Organizations that use artificial intelligence-enabled processes said they can evaluate more than three times more design variants per program. This allows engineering teams to test more ideas, be more creative and optimize products faster, the February 2026 survey of 350 senior engineering leaders found.
- Engineers are adopting AI at an increasing rate, with all respondents saying it is extremely important or somewhat important for their teams. By contrast, 14% of respondents in SimScale’s 2025 survey said AI was not important at all.
Dive Insight:
The biggest takeaway from the survey for manufacturers is that AI is improving engineering teams’ ability to serve customers rather than just changing internal processes, SimScale CEO and co-founder David Heiny said in an email.
“While much of the conversation focuses on speed, the real impact is on how many design options teams can explore and how quickly they can respond to customer requirements,” he said.
Heiny added that even though less than 10% of survey respondents said they had implemented mature, scaled AI programs, firms that use AI in some capacity are already starting to see commercial benefits.
For example, companies using AI-enabled workflows are turning around requests for quote and technical bid responses about three times faster than those using conventional workflows, he said. This provides more time to refine designs and strengthen proposals.
“The takeaway is that AI isn’t just about efficiency,” Heiny said. Rather, “It enables manufacturers to explore more design options, reduce late-stage changes, and deliver more competitive products. The organizations that operationalize these workflows earlier are starting to pull ahead.”
In addition, engineering teams that have successfully scaled AI have focused on building out modern engineering infrastructures and implementing effective organizational strategies. Key elements include secure data governance and clear ownership of moving pilots to production, the survey found. In addition, 75% of organizations with mature AI programs said they had the most success using cloud-native platforms.
Looking ahead, Heiny said engineers should start using AI first in areas where it will have an immediate impact.
“For most engineering teams, that means simulation and design exploration, where AI is already enabling faster iteration and broader evaluation of design options,” he said. “The data is clear on this. Teams that have made this shift are pulling ahead, and the gap is widening.”
He added that for manufacturers, “The opportunity is to use AI not just to work faster, but to explore more design options, reduce late-stage changes, and improve how they respond to customer requirements. The organizations that focus on both practical use cases and the underlying infrastructure are the ones most likely to turn early experimentation into a sustained competitive advantage.”
A recent Cisco survey found that although manufacturers are making progress incorporating AI into their operations, driving revenue with AI and even planning to replace workers with it, significant barriers remain to broader adoption. These challenges include network readiness, cybersecurity breaches, and a lack of collaboration between IT and OT.
Cyber attacks also remain a concern for manufacturers as they adopt AI more broadly, although they can take steps to defend themselves.
