Structural design is an important part of the architectural engineering design stage, which must ensure that the building is safe, reliable, economical, and durable. Artificial intelligence can replace structural designers with a lot of training and repetitive operations to find the optimal design results and improve design efficiency. In order to comprehensively understand the relevant research and application hotspots of artificial intelligence in structural design, the current research status of artificial intelligence in the three stages of scheme design, preliminary design and construction drawing design was summarized from the perspective of the entire structural design process. Through reviewing literatures, it is found that artificial intelligence methods such as expert systems, decision trees, annealing algorithms, genetic algorithms, neural networks, and linear regression have been widely used in the field of building structure design, which has brought new development directions and approaches. At present, artificial intelligence methods are more widely used in the design of aboveground structures, but less in underground structures (foundations, basements, etc.), and their application in underground structures needs to be strengthened. In addition, the quantitative translation technology of normative provisions is relatively mature, but the qualitative translation technology of normative provisions still needs to be broken, and it is necessary to strengthen the research on rule-based or machine learning-based natural language processing.