Machine learning for design and analysis of steel frame halls The use of digital tools in design and construction processes increases efficiency, especially for recurring tasks and processes, such as the dimensioning of components or structures, which follow similar patterns. This paper develops an artificial intelligence (AI)‐based assistant for use in the pre‐design and design of steel frame halls as a prototypical co‐pilot. For this purpose, the necessary database of steel frame halls is first compiled from project archives of TRAGRAUM Partnerschaft Beratender Ingenieure mbB. This will be examined in the context of data analyses according to the decisive description parameters and similarities, so that finally suitable AI surrogate models for the prediction of the hall parameters are trained by means of regression analyses. Furthermore, an interface to the finite element program SOFiSTiK is implemented, which passes the predictions of the AI regarding the parameters of the steel frame halls to a parameterized input file and triggers the calculation and design. In the course of the calibration of the AI substitute models, in addition to the approximation qualities, possible safety margins to be provided are also discussed in the context of this article. This article shows that the prototypical co‐pilot for the preliminary design of steel frame halls could be successfully implemented. Furthermore the AI newly generated hall frames can be classified as stable with respect to the validation considerations. An outlook on future further developments of this approach as well as the transfer to other applications complete this paper. [ABSTRACT FROM AUTHOR]