This study contributes to the empirical literature by examining the impact of tax revenue and institutional quality on economic growth, considering the role of artificial intelligence (AI). The spatial scope of this research was companies listed on the Tehran Stock Exchange and the time range was between 1395 and 1403. This research is an applied research in terms of its purpose, and the research methodology is post-event; meaning that the research is conducted based on past information. In this research, a library method was used to collect data and information. In the data section, the research was carried out by collecting data from sample companies by referring to financial statements, explanatory notes, and the monthly magazine of the Stock Exchange. Based on the systematic elimination method, 137 companies were selected as a statistical sample. Descriptive and inferential statistics were used to describe and summarize the collected data. In order to analyze the data, first, the variance heterogeneity pre-tests, the F-limer test, the Hausman test, and the Jarek-Bara test were used, and then the multivariate regression test was used to confirm and reject the research hypotheses (Iviews software). In summary, the results of the study showed that there is a significant relationship between tax revenues, institutional quality, artificial intelligence, and economic growth. Artificial intelligence has a significant effect on the relationship between tax revenue quality, institutional quality, and economic growth.