Individual propensity to use an AI coaching chatbot in the contact centre environment

Purpose The contact centre industry is a high-intensity, resource-constrained environment that faces growing challenges in balancing effective coaching to improve employee performance with retention while maintaining productivity. Traditional coaching methods are often limited by cost and time constraints. Given these challenges, AI coaching chatbots could provide a scalable and cost-effective solution. However, despite the promise of AI coaching, the barriers to adoption of these technologies amongst individuals in the contact centre environment are not well understood. Design/methodology/approach This study explores the factors influencing individual propensity to use AI coaching chatbots in the contact centre environment by combining an adapted version of the unified theory of acceptance and use of technology (UTAUT2) model with the technology adoption propensity (TAP) index. Partial least squares structural equation modelling (PLS-SEM) was used for the analysis of a cross-sectional survey ( n = 139). Findings The results revealed that performance expectancy (can the chatbot help me?), effort expectancy (is it easy to use?) and hedonic motivation (is it fun to use?) directly influence the intention to use the chatbot. The study also found that vulnerability (the fear of potentially harmful impacts of technology) influences the intention to use a coaching chatbot, highlighting a clear need for transparent data usage policies and procedures. Originality/value This study informs strategies to facilitate the adoption of AI coaching chatbots in contact centres and potentially other high-pressure environments and contributes to a scarce but growing body of knowledge on the context and user sensitivity of AI coaching.