Behavioral engagement and performance in AI-mediated sales training: evidence from student sales competitions

As artificial intelligence (AI) becomes increasingly integrated into professional education, limited research has examined how behavioral engagement with AI-mediated practice environments relates to performance. Existing sales research links purposeful practice to performance but largely assumes human-delivered feedback and frequently relies on self-reported practice behaviors. This study examines whether students’ behavioral engagement with feedback-rich, AI-mediated practice opportunities is associated with performance across three sales competition formats. Using Deliberate Practice Theory and Feedback Intervention Theory as complementary interpretive lenses, we analyze platform-generated engagement and performance data from a census of 2,864 participants across three AI-scored sales competitions. Regression results show that greater behavioral engagement is positively associated with higher competition performance, while comparisons based on practice frequency reveal similar performance differences across engagement groups. However, the strength of these relationships varies across competition formats, which differ in task structure and scoring procedures. The results align with expectations derived from Deliberate Practice Theory and Feedback Intervention Theory, while direct tests of their motivational and attention-allocation mechanisms require additional measures of learner goals, feedback engagement, and strategy adaptation. The study contributes evidence about engagement–performance relationships in AI-mediated sales training and offers guidance for designing scalable, feedback-rich practice environments.