Thesis:

Title : Artificial Intelligence Adoption and Digital Entrepreneurship Intentions

This study aims to investigate the relationship between the acceptance of artificial intelligence and digital entrepreneurial intentions. The present study is applied in terms of its purpose and descriptivecorrelational in nature with a quantitative approach. The statistical population of this study included all managers of funds and non-governmental financial institutions in Sabzevar city, about 175 people. The current era has witnessed profound changes that have occurred in all economic and social dimensions due to the emergence of new technologies, especially artificial intelligence. These technologies have provided a platform for traditional business concepts to evolve towards new models, including "digital entrepreneurship". The present study aims to investigate the "relationship between the acceptance of artificial intelligence and digital entrepreneurial intentions" among managers and employees of private sector financial institutions in Sabzevar city .This study is applied in terms of its purpose and descriptivesurvey in terms of its implementation method and is of a correlation type based on structural equation modeling. The statistical population of the study included all managers and employees of private sector financial institutions in Sabzevar city. A standard questionnaire was used to collect data, and the validity and reliability of the measurement tool were confirmed. Data analysis and testing of research hypotheses were performed using the Structural Equation Modeling (SEM) technique. The results of data analysis showed that all 16 research hypotheses were confirmed. Based on the findings, perceived ease and usefulness of AI tools have a positive and significant effect on AI acceptance, and digital innovation, as an exogenous driver, strengthens this acceptance. On the other hand, AI acceptance has a positive effect on the dimensions of the Theory of Planned Behavior, including attitude, subjective norms, and perceived behavioral control. The results also confirmed that attitude, subjective norms, and perceived behavioral control, along with risk appetite, are powerful predictors for the formation of digital entrepreneurial intention. Finally, examining the role of the moderating variable showed that “digital entrepreneurial selfefficacy” significantly moderates and strengthens the relationship between attitude and digital entrepreneurial intention The findings of this study, while expanding the boundaries of knowledge in the field of digital economy and entrepreneurship, suggest that financial institution managers and regional policymakers should provide the necessary platform for developing innovation and launching digital businesses by promoting artificial intelligence tools and improving employee self-efficacy

Keywords: Keywords: Artificial intelligence adoption, digital entrepreneurial intention, digital entrepreneurial selfefficacy.