InnoVIEW: “AI will fundamentally change the construction industry” – How the IAB Weimar is making an entire industry future-proof.

Artificial intelligence (AI) and big data are transforming the economy – including in Thuringia. The IAB Weimar supports companies in using AI and data analysis in practical applications and driving innovation in the construction industry and interdisciplinary fields. We spoke with Sebastian Gawron about research, implementation, and future trends.

What are the tasks and priorities of the IAB Weimar as a research institution closely linked to industry – and how do you ensure the practical relevance of your work for companies?

Sebastian Gawron: The IAB Weimar, with around 130 employees, develops practical solutions – from building materials and process engineering to building systems, energy and building technology, and civil engineering and pipeline construction. Since 2022, we have also established an AI department. What makes us special: We have our own laboratories, teams of technicians, and accredited testing facilities. This means we can not only conduct research but also test and validate directly. And since 2024, we have even been an affiliated institute of the Bauhaus University Weimar, which significantly strengthens our scientific foundation.

Which industries or company sizes benefit most from your research and projects, and what role do collaborations with companies, universities, and research partners play?

Sebastian Gawron: Our work is geared towards companies in the construction, building materials, energy, and infrastructure sectors – from SMEs to large corporations. Cooperation is essential for us. Many projects are developed jointly with industry partners, universities, and research institutions. Numerous companies are involved through our supporting association, FIAB e. V., and companies often approach us directly with specific needs. An initial project then quickly develops into a long-term partnership. From the academic side, as an affiliated institute, we work closely with the Bauhaus University Weimar and within the Zuse Association network, as well as with Fraunhofer and Leibniz Institutes. And starting in summer 2026, we will be part of the European Digital Innovation Hub. Highlights include our events such as the IAB Concrete Days and IAB Energy. In the future, we want to focus this dialogue even more strongly on future-oriented topics, for example, with a planned AI workshop next April in collaboration with the Bauhaus Academy Schloss Ettersburg. There, we aim to demonstrate concretely how AI can be used in the construction industry.

How do you manage to translate research ideas into marketable solutions, and what efficiency gains, quality improvements, or cost reductions have been achieved in companies through your research?

Sebastian Gawron: Our focus is on application-oriented research – with the clear goal of ultimately creating a product that works in real-world construction projects. Basic research and initial prototypes are conducted by the Bauhaus University and the MFPA – we see ourselves as bridge builders, developing marketable solutions from this foundation. A good example is recycling and resource efficiency: We are developing sensor-based sorting processes for construction waste to recover high-quality raw materials. In parallel, we are researching CO₂-reduced alternatives such as activated clays or lightweight granules made from crushed masonry. We are also conducting intensive research into concrete recycling, as its production is very energy- and cost-intensive. And, of course, AI plays a crucial role – for example, in the early detection of cracks in buildings. This allows for early damage detection, more targeted material use, and extended life cycles.

What tasks and goals does the "Artificial Intelligence and Data Science" department of the IAB Weimar pursue, and what topics are currently at the forefront of your team's work?

Sebastian Gawron: In our department, we focus on three key areas. The first is computer vision. Here, we use AI-supported image analysis to recognize objects, conditions, and patterns – for example, for quality assurance in bricks or masonry. The second focus is on data analysis and forecasting. With our GetStarted2gether partner, orbit Sensorfusion, we are working on the "Samba" project, an intelligent detection box that analyzes sounds on construction sites and thus recognizes construction progress – without site supervision and in compliance with data protection regulations. Thirdly, we develop language models and knowledge systems, i.e., organization-specific AI solutions that make internal knowledge usable – such as chatbots and assistance systems trained with the organization's own data. We also advise on funding opportunities and help transform ideas into concrete research projects.

Which trends or technologies in the field of AI and data science will be particularly relevant for companies in the coming years? 

Sebastian Gawron: In AI-powered image recognition, the trend is clearly toward automated object recognition—for example, for quality control or security checks. Edge AI, meaning AI that runs directly on devices, is an exciting area. This makes applications faster and more privacy-friendly because no sensitive data needs to be transmitted. In the field of data analysis, predictive analytics for forecasting maintenance intervals, material tests, or energy consumption, as well as sensor data fusion and digital twins, are gaining importance. And in language models, the trend is moving away from generic solutions toward company-specific applications, such as AI-powered knowledge platforms and assistants based on internal data, used for automated document searches and knowledge retrieval or in customer service. Above all, sustainability is paramount. AI consumes enormous amounts of energy, and we need trustworthy AI with secure and transparent data spaces.

Where are the biggest obstacles to innovation currently – and how can companies overcome them? 

Sebastian Gawron: The first pain point is unstructured and non-machine-readable data. Many companies lack a clear strategy for this: Where can AI provide concrete support? It's essential to take the time to analyze processes. Another issue is generational differences. Especially in the construction industry, many managers are still steeped in tradition. As soon as the next generation takes over, there's a noticeable increase in openness to digital approaches. It's also challenging when companies try to tackle this alone, with small budgets and no AI specialists. My advice is: Start with small pilot projects, gather experience, then scale up, and if necessary, seek partners. The IAB (Institute for Employment Research) is happy to advise SMEs with needs in this area and on suitable funding programs. And last but not least, there's data protection and regulation. The AI ​​Act is a step in the right direction, but such initiatives often lag behind market dynamics.

What are some of the most common problems that AI and data science can solve most quickly, and what is the process from problem definition to a working solution?

Sebastian Gawron: The launch with AI is about identifying the "low-hanging fruit", Our goal is to identify small, quickly implementable projects with visible added value. This is particularly important for SMEs, as high initial investments are often a deterrent. We deliberately focus on compact pilot projects that can be set up quickly using existing AI models, facilitating entry into the field. In the area of ​​computer vision, these include, for example, automated quality control and object recognition. Data analysis can also provide rapid assistance, for example, in anomaly detection and predictive maintenance of sensor and machine data. This helps to avoid disruptions or downtime in production. With language models, we start where data protection is not an obstacle, such as in the creation of marketing texts or employee briefings. We also assist in developing data strategies and implementing data management systems. The process follows the sequence: problem analysis, prototype development, practical testing, and transition to regular operation. It is important to us to involve and train employees early on so that companies can operate independently in the long term. 

Can you present an AI project at the IAB that you find particularly exciting or consider an innovative milestone?

Sebastian Gawron: There are three projects that I personally find exciting because they demonstrate the diverse ways AI is already being used today. One project is the "Smart Feeder." Here, we use AI image recognition to automatically identify and count wild boars. That sounds simple at first, but it's technologically quite demanding because lighting conditions, movements, and environments are constantly changing. The AI ​​runs directly on the device, as edge AI, entirely without the cloud or internet. A second highlight is "Revincus."“Here, we acoustically analyze wastewater flows. The AI ​​essentially "hears" how the water flows and identifies where usable heat is still present in the wastewater. And then there's E-Terry, an autonomous field robot that can distinguish weeds from crops and remove them mechanically. We support the team in further developing the algorithm and in the programming. 

What cooperation opportunities does the IAB Weimar offer for Thuringian companies, especially SMEs? 

Sebastian Gawron: We offer companies various avenues for collaboration. One classic option is direct contract research: We develop and test methods precisely tailored to the company's requirements. In addition, companies can utilize our laboratories and testing facilities as part of service projects – for example, for materials testing or process optimization. Another option is integration as a subcontractor in ongoing IAB projects, provided they possess specific expertise. A good example is drone surveys: If we require aerial imagery for a project, we collaborate with specialized companies that handle the drone flights, while we take care of the AI-supported analysis. 

What significance do state and federal funding programs (e.g., ZIM, BMWK, getstarted2gether) have for your work – and what tips do you give companies for successful project applications? 

Sebastian Gawron: FFunded projects are a central pillar of our work – they account for around 70% of our project volume. We work with federal programs such as ZIM and the Federal Ministry of Education and Research (BMBF), as well as with state funding through the Thuringian Development Bank. I would particularly like to highlight the European Digital Innovation Hub (EDIH) Thuringia: Here, SMEs can collaborate with consortium partners and receive up to a 50% discount on our services starting in July 2026. We have achieved particular success within the framework of "Get Started2gether," a funding program of the Thuringian Ministry of Economic Affairs. All the startups we have supported so far are still in business today. This is where real value is created. 

What role does networking – for example, through clusters or the "Innovativ Thüringen" initiative – play in your work and knowledge transfer? You are also a member of the strategy advisory board in the specialization area of ​​"ICT, innovative and production-related services." What input do you contribute there, and what do you take away for your work at the IAB?

Sebastian Gawron: Networking is essential for us. Innovative Thuringia offers excellent platforms for exchange. The AI ​​Forum on October 1st was a perfect example. There, we were able to present practical AI applications from the IAB and engage directly with companies, researchers, and political representatives. In the Strategy Advisory Board, I contribute ideas on topics such as digital twins, sustainable AI, trustworthy data spaces, and the transfer of research into marketable solutions. For the IAB, this means that we are very closely connected to the issues that are truly relevant in Thuringia.

Looking five to ten years ahead: How will AI sustainably change the construction industry and applied research in Thuringia?

Sebastian Gawron: I believe AI will fundamentally transform the construction industry – the key phrase being smart construction sites. Furthermore, digital twins of buildings and infrastructure will make planning, condition monitoring, and maintenance more efficient. And in sustainable construction, AI will help to use resources more effectively, optimize recycling, and close material cycles. Thuringia can play a leading role in AI training and the development of skilled workers if research institutions, businesses, and universities collaborate closely. This is a major challenge – but also a tremendous opportunity for the region.

Thank you so much for the conversation!