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How AI is reshaping careers in electronics engineering

From accelerating design processes to enhancing quality control and enabling product features, AI is becoming an indispensable tool across a variety of projects. But, Mirko adds: ‘The key lies in applying it to the right tasks. While it’s the future, its potential is still largely untapped today’. It’s clear that with greater efficiency and innovation also comes greater responsibility.

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    Mirko Vermezović

    Principal Electronics Architect

Mirko Vermezović, Principal Electronics Architect, sees AI as not just a trend, but a transformative force.

With over 20 years’ experience in electronics engineering, Mirko explains there’s a big opportunity for AI to reshape the industry – and the careers within it. So what is its true potential in this space?

Here at Zühlke, Mirko is on a mission to find out. In this blog, we talk to Mirko about the impact of AI on electronics development, looking at what’s already possible, and how it will continue to reshape careers in the industry. 

Insights in brief

The impact of AI on electronics engineering careers

The use of AI is accelerating across a range of domains, and electronics is no exception. As the industry becomes more sophisticated and interconnected, the demand for efficient development processes and innovative products has never been higher.

It’s also becoming a key differentiator for those looking to accelerate their careers in electronics engineering. AI gives a competitive edge for developers using these tools, as the impact on projects is already being felt.

It can enhance design, manufacturing, testing, and product innovation, something we’re exploring more and more here at Zühlke.

Mirko has first-hand experience of this. ‘Because we regularly switch between projects, we’re able to work with different teams and technologies’, he says, ‘pushing the boundaries of what’s possible in electronics’.

On a recent client project, Mirko was working as a system architect for several devices for a new system. On this project, he was able to upskill in security and the relevant industry, and a lot of the tests he did for the automated devices were supported by AI.

‘AI helped to analyse information collected in the system and recognise 10 different problems just based on vibrations coming from it’, he explains. ‘The AI had a 95% success rate in identifying when a component is likely to fail, which meant we could use predictive maintenance much more effectively’.

‘Leveraging a video module, the system could detect hazardous situations and assess the number of individuals involved, automatically triggering relevant alerts for a timely response’.

This is just one early use case for AI in electronics, but its practical development is already impacting ways of working. ‘This is just the starting point of what AI can achieve in electronics, but it’s incredibly exciting’, Mirko underlines.

AI upskilling to boost electronics careers

Although artificial intelligence in electronics has huge potential, it’s at a very different maturity level compared with software engineering (check out our related article: ‘Will AI replace software engineers?’).  

Why? ‘Firstly, the data we need for training is not so readily available on the internet’, Mirko says. ‘At Zühlke, the data we use is from existing projects that have been successful. As we experiment and learn more, the data will grow too’.

Mirko also explains that some of the most commonly used applications don’t have a lot of AI plugins. ‘Everything requires electronics knowledge, but it also involves a whole new set of skills that electronics professionals don’t traditionally explore’.

In order to make the most of what’s possible with AI in electronics, people need experience from other disciplines, such as data engineering, AI frameworks, and even programming languages such as Python and C++.

‘It’s a big step to upskill in this field’, he says, ‘but one that is certainly needed. AI automation could lead to job displacement in the electronics sector, but it will also create new opportunities and require a shift in skill sets toward more strategic, decision making, and interdisciplinary approaches. It’s therefore crucial for companies to balance efficiency gains with the social responsibility of retraining and upskilling employees to work alongside AI technologies’.

Without these skills, it’s easy to use AI for shortcuts that come with real challenges, Mirko explains. For example, you don’t want to end up with a solution you don’t understand that’s costly to unpick.

‘That’s why AI should mostly be used for repetitive work, rather than the creative’, he underlines. ‘It can have its place when keeping engineers up to speed on the most creative tasks, but jobs such as finding components, for example, are repetitive. If you have enough data, it’s much easier for AI to find alternatives than searching manually through endless piles of datasheets’.

But anything more creative should have a skilled electronics engineer to oversee architectural decisions and the route towards a solution.

6 more AI use cases in electronics

So, while we take into consideration the challenges with AI, there’s still plenty of scope in this area when it comes to electronics. In his role at Zühlke, Mirko has researched and experimented with a variety of use cases.

Leaving aside the use cases he’s already mentioned, such as component selection and predictive maintenance, here are several others he thinks have untapped potential.

  • Revolutionising design processes

    ‘The design phase is critical in electronics development, often determining the feasibility and performance of a product. Traditional design methods typically involve extensive manual labour and iterative testing, which can be time-consuming and prone to human error. AI can analyse vast datasets from previous designs, identify patterns, and suggest optimal configurations, reducing the time taken to develop new products’.

  • Mastering component placement

    ‘AI can analyse factors such as signal integrity and heat dissipation and suggest the most optimised placement for electronic components on a printed circuit board. It can automate routing, a tedious and error-prone task, to improve design efficiency and reduce board failure’.

  • Faster design cycles and improved design quality

    ‘Designers can save time by using AI to look after repetitive tasks and suggest improvements, so they can focus more on the creative and improve product quality. Designers can achieve more efficient designs with lower power consumption, while focusing more on developing groundbreaking technologies that push the boundaries of electronic design’.

  • Enhancing testing

    ‘Prototyping is a critical stage in electronics development. AI-driven tools are able to automate the testing of prototypes, allowing for faster identification of potential failures and performance issues. By using predictive analytics, these tools can anticipate how a product will perform under various conditions, which not only saves time but also minimises costs associated with physical testing. AI models can also help with simulations, predicting how components will behave in real-world scenarios’.

  • Optimising supply chain management

    ‘AI can play a significant role in streamlining supply chains within the electronics sector. By analysing market trends and demand forecasts, AI systems can optimise inventory management and logistics. This ensures that components are available when needed, reducing delays in production and helping companies to better manage their resources. It can also analyse historical sales data and market trends to forecast demand more accurately, reducing waste and shortages, as well as streamlining logistics and distribution’.

  • Enabling smart manufacturing

    ‘Smart factories leverage interconnected systems, IoT devices, and AI to optimise production processes. AI allows for real-time monitoring of production lines, enabling manufacturers to respond quickly to any disruptions or inefficiencies. For instance, machine learning algorithms can analyse data from sensors embedded in manufacturing equipment, predicting failures before they occur and allowing for proactive maintenance’.

How can we make the most of AI in electronics careers?

There’s a huge amount of potential with AI in electronics, and we’re just beginning to realise it. Some early use cases are already being developed, but there’s still a way to go.

So how do we get there in the best way that supports career development?

‘The best way to incorporate AI into more of what we do is to start early’, Mirko says. ‘It should be baked into our onboarding process. While general knowledge in the sector is essential, it’s also important to work more on creativity, architectural design and to be able to make more complex decisions’.

He explains that this will help lay a better foundation for using AI in the right way. Whether you’re new to electronics, or have been in the field for a long time, upskilling is critical.

‘We should all be able to use analysis tools, and be more capable with programming languages to develop AI algorithms we use or develop in our domains’, Mirko says. ‘AI isn’t there to give you the final answer, but it’ll help with processes to bring you to a better solution, faster’.

Want to find out more about opportunities with Zühlke and how we can support your learning journey?
Check out our careers page for available roles