To conduct a visual analysis of relevant literature on the application of artificial intelligence in Parkinson's disease research through bibliometric analysis. Methods: The Web Of Science core database was used as the data source for this paper. CiteSpace 6.3.R1 and VOSviewer1.6.20 software were used to conduct bibliometric analyses on the annual number of publications, country/region, institution, keywords, authors and cited literature. Results: Ultimately, 2 043 articles meeting the criteria were included, and the number of publications in this field has been growing rapidly. Articles in this research area have been published by a total of 87 countries/regions. Among them, the United States, China, and Italy are high-yield countries, with Harvard Medical School being the leading institution. The top three authors in terms of publication volume are Gabriella Olmo, Alice Nieuwboer, and Lynn Rochester. High-frequency keywords in this field mainly include Parkinson's disease, deep brain stimulation, and gait, etc.; the latest emerging term is rehabilitation. The application of AI in the field of Parkinson's disease (PD) is mainly distributed in neuroscience, electrical engineering, clinical neurology, and other fields. Among the journals where papers are published, SENSORS ranks first in both publication volume and H-index, while MOVEMENT DISORDERS has the highest impact factor (IF). The most frequently co-cited literature primarily focuses on the integration of electroencephalogram (EEG) signals with AI technology for the early diagnosis of PD. Conclusion: In recent years, AI has been developing rapidly in the medical field, and its application to PD has been increasing year by year, mainly focusing on the prediction of risk factors, diagnosis and treatment of PD.