When it comes to digitalization, the construction industry is more conservative and slower in implementation than other sectors. Professional fields that are heavily data-based, such as meteorology, banking or healthcare, can already use AI technologies more effectively for interrelated processes. Currently, generative AI applications that create texts and images from data input (“prompts”) are the most common. In addition, there are plug-ins and software solutions that can already be used in architecture and are used for individual planning tasks. The following use cases for AI technologies in planning already exist or are under development:
- Text generators for research, tenders, public relations, etc.
- Image generators for brainstorming, design, visualization, etc.
- AI for simulations and optimizations (climate, lighting, wind, traffic analysis, energy balance, etc.)
- AI for creating variants (façades, floor plans, etc.) and feasibility studies (area potential analyses, cost estimates, etc.)
- AI for as-built surveys and model creation
- AI for damage assessment and risk prediction
- AI for monitoring and documentation during construction
- AI in construction robotics (production, assembly, surveying, etc.)
- AI in plan checking and building permits
- AI in building automation for optimizing operations
However, it is clear from existing applications that the results generated by AI are often fuzzy or contain errors. Results therefore still require human quality control and correction and primarily offer initial guidance. From a professional policy perspective, AI technologies should therefore only be understood and used as assistance systems, so that final decisions always remain with humans.