Requirements elicitation and modeling refer to the process of obtaining explicit or implicit requirements from the requirements text described in natural language, and constructing the corresponding models through tabular, graphical, and formulaic methods. Requirements elicitation and modeling is an extremely critical step in software development process, which paves the way for subsequent system design and implementation, improves the efficiency and quality of software development, and improves the stability and feasibility of software systems. Researchers have obtained a series of research achievements in requirements elicitation and modeling. Requirements elicitation and modeling can be generally divided into three steps: requirements knowledge extraction, requirements knowledge classification and requirements model construction. Due to the fact that traditional requirements elicitation and modeling approaches have problems in terms of accuracy and efficiency of model construction, in recent years, more and more researchers have integrated widely applicable artificial intelligence techniques with these approaches, and put forward a series of intelligent require-ments elicitation and modeling approaches, so as to make up for the deficiencies of the traditional methods. This paper focuses on the perspective of intelligent requirements elicitation and modeling, and sorts out and summarizes the research progress of requirements elicitation and modeling in recent years. The main contents include: 1)statistics and analysis of the artificial intelligence techniques applied in requirements knowledge extraction, requirements knowledge classification and requirements model construction; 2)summarizing the verification and evaluation methods used in the process of intelligent requirements elicitation and modeling; 3)summarizing the key issues of intelligent require-ments elicitation and modeling from two aspects of scientific problems and technical difficulties, and elaborating on the six research trends including integrated and dynamic model construction, mining the relationships among intelligent requirements elicitation and modeling and other software engineering activities, refining the granularity of intelligent requirements modeling, data sets construction, evaluation metrics construction and industrial practice as the possible solutions to the above problems. The future development trend of intelligent requirements elicitation and modeling research is also discussed.