"AI is meant to enhance our expertise, not replace it."

Artificial intelligence is transforming the way engineering work is done. But where does it actually add value? And how can it be used responsibly? CTE is taking a close look at these questions. COO Andreas Langer explains the opportunities that are emerging, why expertise remains crucial, and where AI is already being used today.

Noemi Wannenmacher

Published Nov. 9, 26

The internal AI project team—comprising Andy Langer (standing) and Paul Wischnewski, Haris Alic, and Joël Haag (from left)—is overseeing the implementation of AI tools and supporting the development of expertise at CTE.

AI has become part of everyday work life. How does CTE, as an engineering firm, deal with this?

Andreas Langer: It was clear to us early on: AI is here to stay. Regardless of one’s personal stance on the matter, as an engineering company, we must proactively address its opportunities and challenges.

That’s why, three years ago, we made AI a separate focus area, brought in employees with relevant expertise, and sought dialogue with external experts, including the Lucerne University of Applied Sciences and Arts.

Development is happening at an incredibly rapid pace. That’s why it’s important to continuously monitor, test, and critically evaluate new technologies. Not every innovation automatically adds value. Our goal is to identify opportunities early on and pursue them where they actually improve our engineering or our customers’ processes.

How can AI specifically support your engineering and your processes?

Andreas Langer: One key area is access to knowledge. Over many years, we have built up extensive experience, methods, and standard concepts. AI can help us make this knowledge available in a more targeted way and align it with new requirements. For example, we can compare customer requirements or ideas with existing CTE concepts and determine where additions are necessary.

In software development as well, AI helps us turn ideas into initial functional prototypes more quickly and test potential solutions at an early stage. Its use in quality assurance is also interesting: One thing AI is undeniably very good at is checking extensive documentation for completeness and verifying whether traceability—that is, the consistency of all customer requirements throughout our specifications, implementation, and their validation in engineering—has been taken into account.

What is particularly important to us, however, is that AI complements—rather than replaces—the personal exchange of knowledge. As a family-run company deeply rooted in technical expertise, we thrive on the exchange of ideas among our employees. Discussions with experienced colleagues remain central to our work. We are committed to actively fostering this exchange.

At the same time, CTE makes AI tools available to all employees through a centralized platform. What does that mean?

Andreas Langer: We want to provide our colleagues with more than just a chatbot. Our goal is an AI toolkit tailored to our engineering tasks and our own expertise. Our employees contribute their experience and methods. This allows us to ensure that the results are based on our own expertise and not on the general knowledge of a language model.

However, we are explicitly not interested in producing as much output as possible as quickly as possible or in cutting staff. We want to automate repetitive tasks and free up more time for challenging engineering tasks, so that we can be not only more efficient but also even more effective.

What does this mean for your customers?

Andreas Langer: If we can use our knowledge more efficiently and automate recurring tasks, our customers will benefit as well. We see potential for offering services more cost-effectively, especially in projects with a high proportion of manual or repetitive tasks.

One distinction is important to us: We don’t want AI to simply generate engineering results without verification. Rather, we use AI to develop tools that automate defined work steps and deliver reproducible results. This is particularly important in regulated industries.

At the same time, we can share our experience and help customers integrate AI effectively into their own engineering processes.

"AI can make our knowledge more accessible. However, it cannot replace the personal interaction and experience of our employees."

Andreas Langer, COO

What role do partnerships play in developing these skills?

Andreas Langer: AI is a very broad and complex field. It would be presumptuous to believe that we could quickly build the same level of expertise in all areas as companies that have been specializing in this field for years.

That is why we deliberately focus on collaboration. We exchange knowledge with universities such as the FHNW and other companies, which helps us better understand new developments. For specific client projects, we bring in additional specialists as needed.

One example is the AI experts at Learning Machines, with whom we have been collaborating for about three years and in whom we have since acquired a stake (see page 5). With their expertise in data science and machine learning, they specifically expand our capabilities in these areas.

Where is AI already being used in customer projects today?

Andreas Langer: One example is our Data Science Framework. With this framework, we first create a suitable data foundation that enables us to analyze and optimize industrial processes using machine learning. In a successful pilot project at Syngenta, we were able to achieve energy savings within a short period of time.

We are currently working on a customer project focused on predictive maintenance. Data-driven models are used to identify maintenance needs early on and plan maintenance efforts more effectively.

We also see potential in analyzing large volumes of text-based information, such as log files or alarm messages. AI can help identify correlations, classify messages, and verify extensive system configurations.

Reliability and information security are particularly crucial in the industrial sector. How do you ensure these when using AI?

Andreas Langer: We adhere to a clear principle: People remain in charge. In a regulated environment, this is referred to as “human-in-the-loop.” Before software, documentation, or other deliverables are handed over to customers, they must be technically reviewed and verifiable.

This requires clear guidelines, training, and deliberately set technical limits. Our new ISO/IEC 27001 certification provides an important foundation for this. It strengthens our systematic approach to information security and helps us consistently implement both technical and organizational requirements, even when using AI.

Where should this development lead in the coming years?

Andreas Langer: We want to use AI where it actually improves our work and our clients’ processes. The key will be to combine technical capabilities with in-depth subject matter expertise. After all, AI alone cannot complete projects. Only once we understand the requirements and processes and have defined clear goals can we deploy AI in a targeted manner and thereby create real added value.

Picture of Andreas Langer, COO at ControlTech Engineering AG.

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