“Companies lack the courage to innovate,” says Přemysl Šůcha, the new head of Industrial Informatics at CIIRC

25.08.2026

At the end of February 2026, the results of the TAČR SIGMA competition were announced, in which only four projects out of a total of nineteen were successful. Among the funded projects is the National Center for Artificial Intelligence (NCUI), whose principal investigator is Doc. Ing. Přemysl Šůcha, Ph.D. Since March 1, 2026, he has also headed the department Industrial Informatics, where he succeeded Prof. Dr. Ing. Zdeněk Hanzálek, who is now leading the Optimization team and the OP JAK ROBOPROX project, which is a similarly significant project focused more on basic research.

The Department of Industrial Informatics has long distinguished itself as a unit with significant practical applications—it carries out projects with a direct impact on industry, wins prestigious awards, and achieves above-average results in national evaluations of research organizations.& “For example, in the 17+ Methodology, our department has better results in the evaluation of applied outcomes than some entire faculties,” notes Přemysl Šůcha.

Read the interview with Přemysl Šůcha, who points out that these successes are not solely due to cutting-edge algorithms, but above all on a focus on real-world needs—from the operation of hybrid power plants through healthcare to the defense industry—and offers not only a behind-the-scenes look at cutting-edge research but also an open reflection on why innovation in the Czech Republic is gaining traction more slowly than it could. He also stresses the need to further strengthen the department’s role as a bridge between research and industry, both at the national and international levels.

Přemysl Šůcha considers connecting the academic world with companies to be key:  “There is a lack of effective cooperation between the academic and industrial sectors in the Czech Republic. I see shortcomings on the part of both companies and universities, but we must find ways forward.”

Your field of interest falls within the realm of industrial informatics.  How would someone outside the field understand what that means?

We develop specialized algorithms for non-trivial problems. Very often, these are algorithms for optimizing complex processes, decision-support methods, simulations of complex systems, autonomous vehicle control, and the like. Our scope is diverse, ranging from industrial manufacturing, through the automotive industry and energy, to healthcare, business processes, and defense systems.

What trends are currently having the greatest impact on industrial informatics—and which of them do you consider truly fundamental, rather than just short-term hype?

From our perspective, a key trend is the much-discussed digitization. If the problem we’re solving isn’t digitized, it’s difficult to come up with any optimization or innovation, because every algorithm needs data. Today’s society is heavily focused on machine learning and artificial intelligence, which are discussed in nearly every field; however, these methods absolutely require digital data that contains the necessary information. If digital data is lacking, it is difficult to apply any machine learning or artificial intelligence methods. Unfortunately, our experience shows that digitization very often lags behind. This is evident, for example, in the healthcare sector. I have collaborated with a number of doctors—for instance, on scheduling surgical procedures—and it is surprising how poor the quality of the related data is or how often it is completely missing.

What is your team currently focusing on the most? What types of projects are you working on?

Our department works across various fields. Currently, new opportunities in the energy sector, healthcare, and the defense industry are taking center stage. To give a few examples, we recently completed an algorithm for controlling the Energy Nest hybrid power plant, which has been operating successfully for over a year in Vranény in the Mělník region. The power plant’s control algorithm won a Siemens award, and the power plant project itself has also received other accolades. We are currently involved in developing algorithms to improve the efficiency of passive radars and are developing algorithms to streamline the digitization of business processes, such as in banks. In both cases, we are nearing integration into the final product. In addition, we are exploring other opportunities related to processes in healthcare and manufacturing. Since March, we have been involved in the National Center for Artificial Intelligence project, for which I am the principal investigator. I am very pleased that my deputy in managing this project is Doc. Tomáš Kroupa from the Faculty of Electrical Engineering (FEL) at the Czech Technical University in Prague (ČVUT).

Could you briefly introduce the National Center for Artificial Intelligence project?

This project brings together six academic institutions, more than thirty industrial partners, and government agencies. Its goal is to develop innovative artificial intelligence methods with practical applications. The project is overseen by a project council comprising figures such as Prof. Vladimír Mařík, Prof. Michal Pěchouček, Ing. Jan Kavalírek, and Mgr. Lukáš Kačena. We place great emphasis on sharing knowledge across disciplines, ranging from computer science and energy to security and healthcare, and even robotics and autonomous systems. I am delighted that we have succeeded in involving leading experts in the field in the project, and I am very much looking forward to the project’s results. We have six years of intensive work ahead of us.

What does the typical journey of a project look like, from the initial idea to practical implementation?

Our experience shows that every successful project relies on people who have the courage to make a change. In every collaboration, we emphasize analyzing the problem at hand. We need to analyze how the process works, assess where improvements, speed-ups, and cost savings are possible, but most importantly, what the user actually needs. We then proceed to specify what is to be created. We begin the project itself with a brief problem study, which serves to assess the difficulty of the problem at hand and evaluate the economic return on investment. We then carry out the project under a standard contract for work, or we seek out a suitable grant opportunity that would help finance the project. We work on the project in close collaboration with a partner company until the solution has been tested. The commercialization and subsequent maintenance of the solution are then handled by the industry partner.

You collaborate with companies with diverse interests and needs—from the automotive industry to the pharmaceutical sector. How do their expectations differ from those of the academic world?

Every field is different, and for us, it doesn’t matter whether our partners are from manufacturing, the medical field, or air traffic control—what matters is whether they want real change. Companies often view us, as a university, as a business and expect a software solution that includes management and maintenance. Or they simply want to acquire an existing solution at a lower price. However, our strength lies in designing innovative solutions and creating prototypes. We possess the expertise and experience in the field of optimization and advanced artificial intelligence algorithms that companies themselves do not have and cannot possess. We are not database administrators or web application developers.

The collaboration between companies and researchers in the Czech Republic still isn’t working as it should. I find that companies lack the courage and ambition when it comes to innovation. Unfortunately, we often see that the courage to change something remains at the level of a PowerPoint presentation or fades the moment local company management is supposed to discuss project preparations with the company’s leadership abroad. And when I spoke about the challenges of digitization, another moment when companies lose the courage to change is when we ask them for data from their processes.

How do you use artificial intelligence in your work today, and where does traditional mathematical optimization make more sense?

In this case, it depends on the specific application. There are cases where artificial intelligence methods are highly beneficial, but on the other hand, there are many applications where it is better to rely purely on mathematics. In any case, terms such as “artificial intelligence” must be used with caution. Artificial intelligence is a very broad term, and these days it is overused—both by companies and by us scientists.

What do you think will be the key topic for industrial informatics in the next five to ten years?

It’s definitely digitization. I feel like there’s more talk about it than actual action. However, the big question is what software development will look like in five or ten years. We probably won’t use programming languages as much as we do today, but will generate software from some form of technical specification. This raises questions about reliability and security, to which we don’t yet have a clear answer.

From your perspective, what is an interesting challenge in the energy sector today?

The concept of energy is changing significantly. The technologies that are beginning to be used require much more complex management than was the case with traditional energy sources. Efficiency is also a much greater focus. This opens up significant opportunities for the use of optimization algorithms. However, it is always important to objectively assess the benefits of each solution. We are currently preparing a study for the Ministry of Industry and Trade on the use of electrolysers for hydrogen production and the simultaneous provision of power balancing services. I must note that the use of this technology is by no means black and white, and a precise assessment is always necessary to determine whether a given technology is viable in a specific situation or not.

Where else do you see interesting opportunities?

Currently, I see them primarily in defense and healthcare. Defense is driven by the geopolitical situation. Countries like Poland are investing significant resources in this sector. If the Czech Republic wants to maintain its market position, it must innovate in this area. I believe that many solutions designed for the automotive industry can be further developed specifically in this sector. In healthcare, we have a lot of catching up to do from the past, particularly in terms of efficiency. When I look at process management in this environment, I see many opportunities for improvement. At the same time, a great deal of inspiration for improvement in healthcare can also be drawn from industry, specifically from the manufacturing sector. If today’s hospitals were subjected to the same competitive pressure that manufacturing plants face, they would fail due to poor process management efficiency.

Has your department managed to bring about any changes in healthcare?

Yes, we have, but given how many opportunities there are here, it’s still woefully insufficient. For example, we created a digital twin of the laboratory line system for analyzing clinical samples, such as blood, urine, etc. Our digital twin is used in Central Europe to design the configuration of these laboratory systems. Because every hospital is unique, it is by no means easy to properly design and configure this system to ensure that test results are delivered to patients on time. In the future, we want to expand our solution so that it can automatically determine which part of the line should perform which type of test, thereby shortening the time it takes to deliver results or reducing operating costs.

If you could wish for something to help your department, what would it be?

My wish would be to see more companies that have the courage to work with us to create innovative solutions. I feel that it is precisely this courage to take on new challenges that is lacking. Changes cannot be implemented immediately; they don’t happen right away. More people need to be involved in analyzing processes in manufacturing, industry, and healthcare, and they must be willing to participate in the change. Nothing kills innovation quite like the desire to stick to established practices.

I would also like to see more job opportunities in the Czech Republic for people capable of driving innovation. Lately, I’ve noticed that our graduates complain that they’re doing routine work at companies and that there’s a complete lack of innovative challenges, so they’re considering pursuing a Ph.D. here instead. I’ve never seen this before. There’s more talk about artificial intelligence, optimization, machine learning, digitization, and other opportunities than there is actual change. If we want the Czech Republic to succeed, we must create our own solutions that will succeed in foreign markets. Universities and research institutes such as CIIRC should also contribute to this. However, to achieve this, we need bold companies that will work with us to make it happen.