AI affordance and its influence on adoption intention of salesperson

Abstract

Purpose: This study empirically investigates the drivers of AI adoption intention among business-to-business (B2B) sales professionals. It proposes and tests a comprehensive model examining how AI affordances influence adoption intention through the mediating psychological states of psychological ownership, perceived enjoyment, and cognitive effort, while also considering the moderating role of individual thinking styles.
Methodology: A quantitative, cross-sectional research design was employed. Data were collected from 415 B2B sales professionals in India with experience using AI-powered sales tools. The proposed theoretical model, including ten hypotheses, was tested using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 4 software.
Findings: The results provide strong support for the proposed model. AI affordances were found to be a significant positive predictor of psychological ownership (β=0.685) and perceived enjoyment (β=0.650), and a significant negative predictor of cognitive effort (β=-0.590). Psychological ownership (β=0.350), perceived enjoyment (β=0.320), and cognitive effort (β=-0.280) all significantly influenced AI adoption intention. The mediation analysis confirmed partial mediation for all three psychological states.
Theoretical Implications: This study extends technology adoption literature by integrating AI affordance theory with key psychological constructs (psychological ownership, enjoyment, cognitive effort) and cognitive style theory, providing a nuanced, user-centric model that explains the mechanisms through which technological features translate into behavioral intentions.
Managerial Implications: To drive adoption, AI tools should be designed to be customizable (fostering ownership), engaging (enhancing enjoyment), and intuitive (minimizing effort). A one-size-fits-all approach is suboptimal; tailoring AI interfaces and training to accommodate different thinking styles can maximize adoption and effectiveness.
Originality/Value: This research is among the first to empirically test a comprehensive model of AI adoption in the B2B sales context, offering a novel integration of affordance theory and psychological factors, and providing a granular understanding of the human-centric drivers of AI adoption.