Artificial intelligence (AI) describes the ability of computers to learn without being explicitly programmed for tasks (Arthur Samuel 1959). Due to the ever-growing amount of data in the construction industry, AI models can be trained and continuously improved.  The multitude of available data sources makes it possible to find even weak correlations in large data sets.  

For the training of AI models, standard algorithms are usually used, to make predictive decisions on repetitive tasks. For the training of the algorithms, the existence of labeled data sets is particularly crucial. These data sets are made more easily accessible by the SDaC research project, so that small and medium-sized companies in the construction industry can also use AI models efficiently. 

Human thinking processes differ from AI models primarily in the targeted use of intuition and implicit knowledge. Complex issues can only be understood and solved through the targeted use of human-machine interaction.