Generative AI is everywhere right now. Engineers are hearing about it in product development, prototyping, even interface design. The big question is simple: does it actually belong in the world of Human–Machine Interfaces (HMIs)?
We’re not here to promote specific tools or name names. Instead, let’s look at the bigger picture. What questions are engineers asking, and where might AI make sense in HMI design?
Why even consider AI?
OEMs are under constant pressure. Design cycles keep shrinking, budgets are tight, and operators want interfaces that are both simple and powerful; after all…HMIs are the control center of machines, vehicles, and devices.
The promise of AI is speed. It can generate design variations, suggest workflows, or even simulate user actions in minutes. The idea is to cut down on repetitive tasks so engineers can spend more time solving problems that matter.
Where could it actually help?
AI has some obvious use cases that are worth exploring:
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Brainstorming different layout ideas or interaction flows.
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Running basic usability checks by simulating user steps.
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Drafting early documentation like flow diagrams or specifications.
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Spotting inconsistencies across product families.
It’s less about replacing the design process and more about getting a head start.
What are the risks?
The appeal is real, but so are the trade-offs:
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Bias: AI tools learn from patterns that don’t always match your operators or environments. Designing for “average” users can miss critical details.
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Compliance: AI doesn’t know the regulations your product must meet. Human review is still required every time.
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Data security: Feeding sensitive system data into AI platforms may create risks around intellectual property.
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Trust: A design that looks polished on screen but fails in the field could be detrimental.
Does this mean engineers are being replaced?
Not at all. If anything, AI makes the role of the engineer even more important. AI might suggest ideas, but it can’t judge safety, compliance, or real-world usability. Engineers remain the ones who set direction and validate every decision.
How to use it responsibly
If engineers want to experiment with AI in HMI projects, a few principles can help keep things grounded:
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Use it for inspiration, not for final designs.
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Always validate against standards and operator testing.
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Protect proprietary data.
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Treat AI outputs as ideas to test, not answers to trust.
AI has potential, but its place in HMI design is as a supporting tool, not a decision-maker. The engineers who approach it with curiosity, caution, and a clear focus on the operator will be the ones who get real value from it.