Healthcare building projects are recognised for their complexity, in which services, flows and activities from different stakeholders lead to several requirements. In this context, regulatory requirements have a fundamental role as they describe minimum attributes from a compliance perspective, as well as define a basic framework upon which the design of healthcare buildings needs to be developed. In the UK, the healthcare regulatory framework includes statutory and guidance documents presented in a convoluted suite of requirements, which is difficult to use in practice. This challenging backdrop affects the efficiency of regulatory compliance and the quality of the healthcare built environment, potentially influencing health outcomes. The use of automation to improve regulatory compliance in building projects has been a frequent research topic. Despite the several potential benefits pinpointed by existing research, practical outcomes are still limited to specific types of requirements (e.g., representing quantitative and objective information). Such exploration has happened mostly through the adoption of a compliance checking perspective, which is often perceived as detached from the design process, revealing a disconnection between the way automated regulatory compliance has been explored by existing research and the overall design process. The aim of this research is to devise a model to enable automated regulatory compliance in healthcare building design. Design Science Research was the methodological approach adopted in this investigation. It consists of a mode to produce scientific knowledge by creating and implementing artefacts to solve real-world problems. The research process was based on two empirical studies that supported the continuous development and evaluation of the model (i.e., the research artefact). The proposed model includes three main stages: (i) method to classify regulatory requirements; (ii) requirements’ processing; and (iii) automated regulatory compliance and design instance. One of the main contributions of the proposed approach is to understand and classify information from regulatory requirements by using a requirements’ taxonomy. The model contrasts with existing literature by addressing regulatory compliance from the design process perspective and highlighting key automated approaches that can be adopted during the design development with consideration of inputs from human designers. Key theoretical contributions of this research relate to the proposition of two different classifications for subjective requirements, defined as natural and artificial subjectivity, emerging after the redevelopment of a requirements taxonomy utilised to classify regulatory requirements. Furthermore, the analysis of interviews revealed different understandings that automated regulatory compliance has in design practice, better reflecting characteristics of the design process such as creativity, subjectivity and the problem-solution co evolution. The development, implementation and evaluation of the model also enabled recommendations to emerge. These are associated with the development or revision of regulatory documents; support to designers in the implementation of some level of automated regulatory compliance, as well as describing key needs of software development in this context.