Use of artificial intelligence in construction
Game changer AI: building for the future
The digitalization of construction and the associated automation of various planning and building processes is continuing to pick up speed. Nevertheless, the building sector remains largely analogue when compared to other branches of industry. A wealth of recurring tasks – fields of activity that have long since been solved by robots and controlled digitally in the automotive sector, for example – still need to be carried out on our construction sites by hand and with physical strength. However, artificial intelligence (AI) and machine learning form an important foundation here for making planning and building more automated, efficient and high-quality in future. And AI reduces the strain on the many people who go about their challenging work every day on construction sites and in architecture and planning offices.
That makes them a game changer in an industry in which work has so far been more analog and manual than digital and logarithmbased. And it’s why digitalBAU 2026 has made AI a key topic and will be focusing in detail on this disruptive technology at the trade fair stands, in specialist lectures, trade fair forums, and live talks.
In addition, AI reduces the strain on the many people who go about their challenging work every day on construction sites and in architecture and planning offices. In particular, the automation of repetitive tasks through AI support, and the use of robots and machines for bricklaying, plastering, construction site supervision, and measuring or improving quality and safety in construction operations is now growing substantially.
The benefit of using AI across all industries and established technologies is currently being described again and again and predicted by numerous studies. But it is not possible to predict exactly what economic added value artificial intelligence and machine learning will achieve over the next decade. However, the conceivable optimizations from automating standard processes in the construction industry are so striking that we can assume a potential of several billion euros in the next decade in Germany alone. Research paints a similar picture for the global market. The market research institute Global Market Insights expects AI-generated sales in the construction industry to exceed USD 15 billion by 2032. The market researchers see the greatest potential in the areas of project and risk management, construction supervision, and building operation.
Building remains a craft to this day
The reason for this is obvious: To this day, building is still a manual process with all the advantages and disadvantages that go with it. Intelligence in building has always primarily come from the know-how that architects and planning offices, construction companies and specialist trades companies enter in the planning and building process, and therefore have significant control of the quality of our architecture. Human intelligence, not artificial intelligence, is therefore the compass on which the further development of intelligent systems must be based. This is what sets the direction of digital developments. In addition, there is also the diversity of the tasks that arise during the design, planning and construction process and the subsequent operating phase of a building, as well as the various planning partners and protagonists involved in a complex structure of technical requirements, standards and regulations, implementation options and solution approaches for the built environment.
If you look at the network of dependencies, it quickly becomes clear where the greatest development potential for artificial intelligence in the construction industry currently lies:
- in the automation of planning,
- in the standardization of construction processes and
- in the reduction of personnel on construction sites.
Driving automation in planning
Digital planning methods such as Building Information Modeling (BIM) create a comprehensive pool of data and information early in the planning phase which can enable the use of machine learning. AI already offers a significant boost to efficiency in the form of “deep learning” during the tendering and awarding process, as this is usually similar regardless of the construction project itself and enables a high degree of digitization thanks to database-supported processes.
Algorithms are already being used by forward-looking construction and planning companies around the world to determine the optimal (which is not always the cheapest) offer for project and construction services from various bidders. An objective evaluation is carried out for the respective project requirements based on previously defined parameters (e.g. proven know-how for the special task, advanced use of technology, efficiency advantage in the market). The understanding of the bid requirements, which results from a broad application of deep learning in various construction applications, areas of application and tasks, then flows back into the software and allows the intelligent algorithms to learn again from new decisions in the next project.
Generative design in the building sector
This example illustrates that machine learning and AI enable new qualities in the planning process, especially in the case of recurring planning tasks with redundant tasks. Nevertheless, human knowledge in architecture and planning offices is still an important foundation for all digitally initiated learning processes of software and technology. Generative design – simply put, designing under consideration of previously stored parameters and continuous optimization of the design result – is another area of AI application in construction. Still relatively young, parametric-based planning is nevertheless a promising field of work in the architectural sector.
Although parametric-based planning has so far mainly been used for individual and lighthouse projects, it is nevertheless a promising field of work in the architecture sector, especially in combination with AI tools.
Since many parameters are specified when planning buildings and the individual user requirements, construction, location and function of the rooms as well as the connected technical systems are directly related to each other, they can be intelligently combined in generative design. In the specific planning application, this means that technical regulations and standards, planning specifications and spatial dependencies flow into the generative process. The result is, for example, optimized floor plan variants that take into account all the properties required by building law and desired by the client. However, by no means does this make experienced project architects or highly specialized structural engineers redundant. Rather, their work is made easier thanks to the support from AI. At the same time, the risk of simply forgetting important points in the draft is reduced.
AI support for concept and design
In the past two years, following digitalBAU 2024, more and more text-to-image models and other imaging AI tools have come onto the market. The leading software providers in the construction industry, but also smaller startups, offer initial guidance with their tools, especially in early design phases, on the way to an optimized architectural design. These tools, which are integrated into BIM planning software or run independently as an application or virtually in the cloud, make it possible to quickly visualize architectural concepts based on text input. This makes early design variants and concept sketches clear and interactive, bringing them to life for developers, investors, and project partners. With requirements formulated precisely in the prompt and AI put to optimum use, they actively support designers and planners in formulating design ideas, thus enabling conceptual bandwidth and a clear head to focus on important tasks. Further added value: They facilitate communication with the participants during a competition or later in the project.
Digital tools for circular construction
The course for sustainable and recyclable architecture is set early on in the planning process. Understanding architecture as a potential raw materials depot for the future and focusing on long service lives and the continued use of building components and materials in the building life cycle are fundamental to that. Material registers, in which used building components from conversion and dismantling are recorded, also rely on database-supported AI. After extensive training on real data sets, it is able to suggest suitable or similar components that take account of individual planning requirements. By analyzing material flows in detail, AI can also determine which materials are used in existing buildings, when they are available for reuse, and for which type of projects they can be reused. The necessary systems are already available: AI-based platforms such as Madaster and syte enable comprehensive and accurate recording and evaluation of existing buildings and materials. Solutions like these facilitate planning for conversion or dismantling, support reuse and thus lay the foundation for future nationwide material registers.
Livable cities for the future
Artificial intelligence also opens up a wide range of new applications for urban planning. AI systems are able, for example, to analyze and process the huge amounts of data that are generated every day in a thriving metropolis, identify potential for optimization, and make targeted recommendations for action. They recognize trends or simulate scenarios that help make urban spaces and the entire urban fabric more livable. That also includes intelligent energy and water management. AI systems help to efficiently manage individual consumption and the communal supply to citizens, and to develop sustainable concepts for the future. AI generates optimized land use and street maps, forecasts traffic flows, and provides support in needs analysis and planning infrastructure buildings, green spaces and parks, or living space. Participation is another field in which AI can collect, structure, and mediate: It encourages the involvement of citizens through digital participation tools. The automated evaluation of feedback from citizen participation also enables the population to participate more broadly in planning processes that affect their personal living environment.
The use of building models created as part of BIM planning can also be extended to the construction site. This creates added value in terms of both planning and construction: On the one hand, self-propelled construction machines or robots access adapted BIM model data for their autonomous movement over the construction site or the execution of construction work (masonry robots, automated excavation pits with GPS-controlled excavators, digitally supported construction progress and quality management with animaloid robots). On the other hand, the new data generated when using them can be used in reverse, to compare the planning and actual situation on the construction site, to discover and evaluate relevant deviations and thus to avoid expensive execution errors.
In the near future, artificial intelligence in construction should make it possible to design the multitude of recurring work processes on a construction site efficiently and automatically. The basis for this must always be an extensive pool of available data and information. For example, the more detailed and specific the information from the building model and the specialist planner models is, and the more empirical values are already available from previous projects, the more intelligently processes can be automated. The aim should be to enable work such as excavating the construction site, tying steel reinforcements and manual formwork or simple masonry and concrete work to be carried out automatically and under the quality control of qualified skilled workers in the future – but no longer with any physical effort for these strenuous construction tasks. The acceptance and relevance of modular construction and prefabrication in the construction sector will continue to grow, as will the efficiency of the construction process. Likewise, construction site activities will become significantly more attractive in the future, since the proportion of physically demanding work is noticeably decreasing.
Man is the measure of all things
In the context of our architecture, humans play the most important role in the use of AI and machine learning, deep learning, generative design or the use of robots in construction. The structural quality of the architecture created by AI technology, high cost security and minimizing of sources of error for planning, construction and operation are certainly important aspects for their increased use in construction. However, it is no less important to relieve the protagonists of planning and implementation in the medium and long term. At 5 to 6 percent, the annual migra-tion of specialist staff, especially from the shell construction trades, is well above the average compared to other branches of industry (approx. 4 percent). What is particularly problematic, however, is that there are already more skilled workers retiring today than there are replacing them. The fluctuating construction industry is also contributing to increased migration.
Artificial intelligence can help to significantly increase the appeal of working in planning and on construction sites in particular. The first examples, which are leaving the research stage and are now being used on a broad scale, are an encouraging indication of smart “teamwork” between humans and artificial intelligence in future.
digitalBAU 2026 offers the topic of artificial intelligence a lot of space at the trade fair for a holistic and multifaceted view of what is for the construction industry still a young technology. Visitors to the trade fair can learn about the individual solutions and services of exhibiting companies with an AI focus, test them on site in Cologne, and speak directly with researchers from universities, colleges, and institutions. digitalBAU 2026 also features numerous specialist forums and lectures, giving visitors the opportunity to deepen their knowledge of the many possible applications of AI. That all adds up to a worthwhile visit.