A small minority of engineering firms are starting to make serious headway with AI, but the race is far from over and there are still plenty of opportunities for other firms to catch up, writes David Heiny of SimScale
In engineering circles, there are growing rumours of a handful of companies quietly pulling ahead in competitive terms, thanks to their use of AI – but is the fear of missing out (FOMO) justified among those still on the starting blocks?
In SimScale’s State of Engineering AI 2025 survey of 300 senior leaders, 93% of respondents said they expect big productivity gains from AI and 30% are betting on AI having a “very high” impact on their engineering workflows.
However, it’s a far smaller proportion – around 3% – that report actually seeing those gains today.
After countless conversations with teams from organisations ranging from start-ups to global manufacturers, I can confidently say the success stories are real and that their wins come down to practical steps that any firm can take.
Overcoming hurdles
The first hurdle is fractured data. Finding the right simulation file can feel for some like a treasure hunt where the map is missing. When results live on separate desktops, shared drives or old CAE platforms, building reliable AI models is almost impossible.
More than half of those surveyed point to siloed data as their biggest blocker. I’ve seen teams spend weeks just pulling together a single data pipeline before they attempt a proof of concept.
Another pain point are legacy tools. I spoke with a major automaker where engineers still use five different applications to get a full system simulation. They know AI could cut their set-up time significantly, but outdated software won’t cooperate.
Then there’s the enthusiasm gap: 42% of CTOs assume deep resistance to AI within their teams, yet only 29% of engineers recognise this in their peers.
In my experience, engineers are supereager to experiment with AI, but what is holding them back is the thought of needing senior management’s blessing.
Race to the finish
Focusing only on the barriers leaves out the other half of the story. I’ve sat down with the teams already in that small but growing first wave of AI adopters, and here are the lessons they’ve shared.
They treat data as critical infrastructure. One aerospace group I met stores every simulation it runs in a cloud repository where it is tracked, tagged and accessed through simple calls. This organisation’s data scientists can launch training runs in minutes, rather than days.
Successful companies weave AI into the heart of their workflows. A medtech firm showed me how its system suggests optimal boundary conditions the moment that an engineer starts a new model. Tweaks happen on the fly and set-up times shrink dramatically.
Speed is a common theme. These teams start with small, focused experiments and prove value in a matter of weeks. Once an AI model pays off, they push it straight into day-to-day work without waiting for endless approvals.
Version control matters just as much for models as it does for code. A heavy equipment manufacturer explained how it logs every result, every AI model update and every metric in open formats. Engineers can see exactly where a recommendation came from and roll back if needed.
Culture makes a huge difference. AI frontrunners have leaders who celebrate small wins and treat setbacks as lessons
Culture makes a huge difference. The frontrunners have leaders who celebrate small wins and treat setbacks as lessons. Frontrunners also focus on the use cases that matter most. Instead of chasing every AI trend, they pick one or two routines where shaving off days transforms outcomes, whether automating batch simulations or speeding up thermal analysis. Clear goals keep stakeholders engaged and prove ROI fast.
Move fast, learn fast
If you’re feeling the FOMO too, here’s my challenge: gather your core group, pick one painful bottleneck, and sketch a lean prototype with clear measures of success.
Treat your data as the foundation, weave agentic AI and automation into the workflow, and don’t wait for everything to be perfect. Move fast, learn fast. Keep communication open, celebrate every win, and you’ll find yourself joining The 3% Club before long.
About the author:
David Heiny is CEO of SimScale. He holds a Bachelors of Science in Mathematics and a Diploma in Mechanical Engineering from the Technical University of Munich, as well as a Master’s degree in Computational Science and Engineering from the Georgia Institute of Technology
www.simscale.com
