The In(congruent) Effects of AI Ambidexterity in Digital Entrepreneurship: Insights from the Entrepreneurial Event Model

Abstract The increasing integration of artificial intelligence into entrepreneurial activities has transformed how individuals engage with digital innovation. This study examines the correlation between the congruence and incongruence of innovative and routine use of generative artificial intelligence (ambidexterity) and digital entrepreneurial intention. Drawing on the entrepreneurial event model, polynomial regression, and response surface analysis, the study examines the congruence and incongruence between routine and innovative uses of generative artificial intelligence, capturing their complex interactions and joint effects. Data collected from 1,061 undergraduate students at Vietnamese universities revealed significant congruence effects, showing that alignment between high levels of routine and innovative uses enhances students’ digital entrepreneurial intention, perceived desirability, and feasibility. Furthermore, the incongruence between these uses has a negative relationship with entrepreneurial outcomes. The study also confirms that perceived desirability and feasibility mediate the relationships between generative artificial intelligence use (routine and innovative) and digital entrepreneurial intention. These findings extend current understandings of how digital tools support entrepreneurship education, highlighting the importance of balancing exploitation (routine use) and exploration (innovative use). Practically, the results suggest that educators and policymakers should encourage students to simultaneously develop both routine and innovative competencies in generative artificial intelligence to nurture digital entrepreneurial aspirations effectively.