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

Artificial Intelligence (AI) and Big Data are transforming the economy – including in Thuringia. IAB Weimar supports companies in using AI and data analysis in a practical way and driving forward innovations in construction and interdisciplinary fields of application. We spoke with Sebastian Gawron about research, implementation, and future trends.

What tasks and priorities does the IAB Weimar have as a business-oriented research institution – 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 built up the AI department. What makes us special: We have our own laboratories, technician teams and accredited testing facilities. This means we can not only research, but also directly test and validate. And since 2024, we have even been an affiliated institute of the Bauhaus University Weimar, which further strengthens our scientific foundation.

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

Sebastian Gawron: Our work is aimed at companies in the construction industry, building materials industry, energy and infrastructure – from SMEs to large corporations. Collaborations are essential for us. Many projects are developed together with industrial partners, universities and research institutions. Numerous companies are involved through our support association FIAB e. V., and companies often approach us directly with specific needs. A first project quickly turns into a long-term partnership. On the scientific side, as an affiliated institute we work closely with the Bauhaus University Weimar as well as within the network of the Zuse Community, but also with Fraunhofer and Leibniz Institutes. And from summer 2026 we will be part of the European Digital Innovation Hub. A highlight is our events such as the IAB Concrete Days and IAB Energy. In the future, we want to focus this dialogue even more on future topics, for example with a planned AI workshop next April together with the Bauhaus Academy Schloss Ettersburg. There we want to show concretely how AI can be used in the construction industry.

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

Sebastian Gawron: Our focus is on application-oriented research – with the clear goal that a product emerges in the end that works on the construction site. Basic research or initial prototypes are carried out by the Bauhaus University or the MFPA – we see ourselves as bridge builders who develop marketable solutions from this. A good example is the topic of recycling and resource efficiency: We develop sensor-based sorting processes for construction waste to recover high-quality raw materials. In parallel, we research CO₂-reduced alternatives such as activated clays or lightweight granules from masonry rubble. We also conduct intensive research on concrete recycling, as its production is very energy- and cost-intensive. And of course, AI plays an important role – for example, in the early detection of cracks in structures. This allows damage to be detected early, materials to be used more specifically, and life cycles to be extended.

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

Sebastian Gawron: In our department, we focus on three main areas. The first is Computer Vision. Here, we use AI-powered image analysis to recognize objects, conditions, and patterns – for example, for quality assurance of bricks or masonry. The second focus is on data analysis and forecasting. With our GetStarted2gether partner orbit Sensorfusion, we are working on the project “Samba” on an intelligent detection box that evaluates sounds on construction sites and thus recognizes construction progress - without on-site supervision and in a data protection-compliant manner. Third, we develop language models and knowledge systems, i.e., organization-specific AI solutions that make internal knowledge usable – that is, chatbots and assistance systems trained on proprietary data. We also advise on funding opportunities and help turn ideas into concrete research projects.

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

Sebastian Gawron: In AI-powered image recognition, the clear trend is toward automated object detection – for example, for quality control or safety inspections. The topic of Edge-AI, i.e., AI that runs directly on devices, is particularly exciting. This makes applications faster and more data protection-friendly because no sensitive data needs to be transmitted. In the area of data analysis, predictive analytics for forecasting maintenance intervals, material testing, or energy consumption, as well as sensor data fusion and digital twins, are gaining importance. And with language models, the trend is moving away from generic solutions toward company-specific applications, e.g., AI-powered knowledge platforms and assistants based on internal data, used for automated document search and knowledge processing or in customer service. Above all, the topic of sustainability stands out. Because AI consumes enormous amounts of energy. And we need trustworthy AI with secure and transparent data spaces.

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

Sebastian Gawron: The first pain point is unstructured and non-machine-readable data. In addition, many companies lack a clear strategy: Where can AI provide concrete support? You have to take the time to analyze processes. Another point is the generational issue. Especially in the construction industry, many managers are still traditionally oriented. As soon as the next generation takes over, you notice significantly more openness to digital approaches. It is also difficult when companies try to manage this on their own, with small budgets and without AI specialists. My advice is: start with small pilot projects, gather experience, then scale, and if necessary, look for partners. The IAB is happy to advise SMEs that have needs here and on suitable funding programs. And last but not least, there are data protection and regulation. The AI Act is a step, a beginning, but such initiatives often lag behind market dynamics.

Which typical problems can you solve most quickly with AI and data science, and how does the process from problem definition to a working solution proceed?

Sebastian Gawron: When starting with AI, it is about identifying the "low-hanging fruits", i.e., to identify small, quickly implementable projects with visible added value. This is especially important for SMEs because high initial investments are often off-putting. We deliberately focus on compact pilot projects that can be set up quite quickly with existing AI models and facilitate the initial steps. In the field of computer vision, these include, for example, automated quality controls and object recognition. Data analysis can also help quickly, e.g., in anomaly detection and predictive maintenance of sensor and machine data. This helps to avoid disruptions or failures in production. For 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 building data strategies and introducing data management systems. The process follows the sequence: problem analysis, prototype development, practical test, and transition to regular operation. It is important to us to involve and train employees early on so that companies can work independently in the long term. 

Can you present a project in the field of AI at the IAB that particularly excites you or that you see as an innovative milestone?

Sebastian Gawron: There are three projects that I personally find exciting because they show how versatile 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 is technologically quite demanding because lighting conditions, movements, and environments are constantly changing. The AI runs directly on the device, as edge AI, completely without cloud and internet. A second highlight is “Revincus“. Here we analyze wastewater streams acoustically. The AI essentially listens to 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 programming. 

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

Sebastian Gawron: For companies, we offer various ways of collaboration. A classic option is direct contract research: we develop and test procedures that are precisely tailored to the company's requirements. Additionally, within the framework of service projects, companies can use our laboratories and test facilities – for example, for material testing or process optimization. Another option is integration as a subcontractor in ongoing IAB projects if they have specific expertise. A good example is drone surveying: when we need aerial image data for a project, we work with specialized companies that carry out the drone flights, while we handle the AI-supported evaluation. 

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: FFunding 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 or BMBF, but also with state funding through the Thüringer Aufbaubank. I would particularly like to highlight the European Digital Innovation Hub (EDIH) Thuringia: Here, SMEs can collaborate with consortium partners and receive up to 50% discount on our services from July 2026. We achieved particular successes as part of “Get Started2gether“, a funding program of the Thuringian Ministry of Economic Affairs. All the start-ups we have supported so far are still on the market today. Real value creation is taking place here. 

What role does networking play – for example through clusters or Innovativ Thüringen – in your work and knowledge transfer? You are also a member of the Strategic Advisory Board in the specialization field "ICT, innovative and production-related services". What impulses do you contribute there and what do you take away for your work at the IAB?

Sebastian Gawron: Networking is essential for us. Innovativ Thüringen offers great platforms for exchange. The AI Forum on October 1 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 impulses on topics such as digital twins, sustainable AI, trustworthy data spaces, or the transfer of research into marketable solutions. For the IAB, this means that we are very close to the topics 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 think AI will fundamentally change the construction industry – keyword smart construction sites. In addition, digital twins of buildings and infrastructures will make planning, condition monitoring, and maintenance more efficient. And in sustainable construction, AI will help to use resources more specifically, optimize recycling, and close cycles. Thuringia can take on a leading role in AI training and skilled worker development if research, industry, and universities work closely together. That is a major challenge – but also a huge opportunity for the location.

Thank you for the conversation.