The digital transformation of the AEC industry through BIM has improved productivity during detailed design and construction planning phases. Early design choices influence a project's success but have yet to benefit from BIM-based approaches. This paper investigates the feasibility and acceptance of employing Generative Design (GD) to optimize early Mechanical, Electrical, and Plumbing (MEP) designs in residential real estate for space efficiency. Interviews indicate the main issue is acceptance due to the belief that a GD approach needs to be more robust. BIM is integrated with GD, utilizing the architectural layout (IFC) as input to generate design variants tailored to minimize technical space while ensuring installation feasibility. Robustness is assessed via Monte Carlo Simulation, revealing an estimated success rate of 99% (81% with 95% confidence). These results quantify the robustness of the approach, paving the way to broader acceptance of GD in the early phases of AEC projects. •Optimized technical spaces in early-stage residential building projects.•Generative Design in BIM using a tuned Genetic Algorithm for optimization.•Identified algorithmic robustness as crucial for acceptance of Generative Design.•Generated multiple acceptable designs representing the Pareto Front in optimization.•Genetic Algorithm robustness proved with 99% success via Monte Carlo Simulation.