Understanding Salesperson Intention to Use AI Feedback and Its Influence on Business-to-Business Sales Outcomes

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Purpose: Artificial intelligence (AI) is a rapidly growing frontier. One promising area for AI is its potential to assist sales managers in providing salesperson feedback. Despite this promise, little work has been done within the business-to-business (B2B) sales domain to investigate the potential impact of AI feedback on critical sales outcomes. The purpose of this research is to explore these issues and respond to calls in the literature to determine how AI can enhance salesperson adaptability and performance. Design/methodology/approach: Survey data from a sample of 246 B2B salespeople was used to test the conceptual model and research hypotheses. The data were analyzed using partial least squares structural equation modeling (PLS-SEM). Findings: The findings provide broad support for the model. An AI-feedback rich environment and salesperson feedback orientation predicted perceived accuracy of AI feedback which, in turn, strengthened intentions to use AI feedback. These favorable reactions to AI feedback positively related to adaptive selling behaviors, and adaptive selling behaviors mediated the relationships between intentions to use AI feedback and organizational commitment, as well as sales performance. Contrary to expectations, it did not mediate the relationship between intentions to use AI feedback and job satisfaction. Practical implications: The managerial implications of this study lie in explaining practical considerations for the implementation and use of AI feedback in the sales context. Originality/value: This study extends literature on technology adoption, performance feedback and the use of AI in the B2B sales domain. It offers practical insight for sales managers and those responsible for implementing AI solutions in sales.