The adoption of artificial intelligence technology in accounting managers' financial decisions is of great importance due to its potential benefits in improving accuracy, speed, and efficiency. However, the factors affecting the adoption of this technology in the context of Iranian organizations, especially companies in Alborz province, have not been fully identified. This study aimed to investigate the effect of perceived usefulness, perceived ease of use, and user satisfaction on behavioral intention and the effect of behavioral intention on the actual use of artificial intelligence in accounting managers' financial decisions in Alborz province companies. The present study is applied in terms of purpose and descriptive in terms of method, and is of survey and correlation type. The statistical population included all accounting managers in Alborz province companies, of which 265 people were selected as a sample based on the Krejci and Morgan table by simple random method. The data collection tools were the standard questionnaires of Davtas and Diamantaplos (2017), Jamal and Sharafeddin (2014), and Wessels and Dornan (2010). The validity and reliability of the instruments were confirmed using confirmatory factor analysis and Cronbach's alpha coefficients and composite reliability. Data analysis was performed using structural equation modeling and Smart PLS3 software. The findings showed that perceived usefulness, perceived ease of use, and user satisfaction have a positive and significant effect on managers' behavioral intention. Behavioral intention also has a positive and significant effect on the actual use of artificial intelligence. The research model was able to explain a significant percentage of the variance in behavioral intention and actual use. Based on the results, it is recommended that company managers provide the basis for wider acceptance of this technology by holding training courses to increase the perception of the usefulness of artificial intelligence, improving the user interface for ease of use, and creating feedback mechanisms to increase user satisfaction. Future research can provide a deeper understanding of the process of adopting artificial intelligence in the financial field by considering moderating variables and using longitudinal methods.