Since the introduction of ChatGPT in November 2022, applications based on artificial intelligence have become increasingly established in both our private and professional environments. The use of AI applications (large language models such as ChatGPT) in Germany has more than doubled from around 23% in 2023 to 53% in 2025. Among 16- to 35-year-olds, almost 80% of respondents use AI applications.

A similar trend is emerging in the construction industry. According to a survey conducted in German-speaking countries, 48% of site managers report having already used AI applications in a professional context. At the same time, a significant discrepancy can be observed between the predicted potential of AI applications in construction management processes and the actual competencies available. Initial expert interviews indicate that the greatest challenges are seen in the acceptance of AI applications, the complex integration into existing processes, and skepticism towards automated decision-making. It should also be noted that small and medium-sized enterprises (SMEs) face different conditions and opportunities when introducing disruptive technologies due to their organizational structures, compared to large corporations. Therefore, a separate analysis of these economic actors is likely to yield insights that differ from those obtained through an examination of the industry average.

The aim of the research is to gain an overview of the competencies of small and medium-sized enterprises in civil engineering with regard to the use of AI applications in construction management processes, and to assess the extent to which the predicted potentials are actually being realized. Based on the insights gained, the framework conditions and scope for action of SMEs in this disruptive field of development will be derived. Within these boundaries, pilot studies are to be developed and implemented. This research aims to contribute to the integration of AI applications in construction management processes of SMEs in civil engineering by providing abstracted use cases with clearly defined framework conditions.