[Purpose/significance] This paper identifies the research team in the artificial intelligence field, and extracts the leading research team from multi-dimensional indicators, aiming to enrich the process and method of identification of the research team, and provide the basis for analyzing the context, frontier and theme of the field of artificial intelligence from the perspective of the research team.[Method/process] This paper was based on the publication data of the Web of Science category Computer Science, Artificial Intelligence from 2009 to 2018, and did data cleaning via programming and manual check. Global co-author network is constructed based on the fractional counting method, and the Louvain algorithm was used to dynamically tune and identify the research teams. Moreover, the leading research team was extracted based on different indicators with parameter adjustment.[Result/conclusion] From practical view, the study has constructed a set of rules for cleaning publication data of artificial intelligence field. The process of identifying artificial intelligence research teams based on co-authorship is constructed. The study proposes the method of tuning the parameter by eliminating edge nodes in the collaboration network and further taking the known research teams as baseline. The worldwide research teams of artificial intelligence field are systematically and accurately identified. The leading research teams are further extracted based on indicators of six dimensions, i.e. number of publications、number of citations、h index、weighted degree centrality、betweenness centrality、closeness centrality. Exemplary analysis is conducted on leading research teams of each dimension by combining the publication data and web information survey.