Exploring Human Artificial Intelligence Using the Knowledge Behavior Gap Model

Acceptance of emerging technologies such as artificial intelligence (AI) exhibits significant variability across different demographic groups and geographic regions. Despite a gradual increase in acceptance and adoption over recent years, skepticism and resistance persist. Therefore, this study employs the Knowledge Behavior Gap (KBG) model to gain deeper insights into human perceptions of AI. It includes a quantitative analysis of 200 survey responses from 41 countries, investigating the pathways from knowledge about AI to its use. The research findings validate and expand the applicability of the KBG model in the broader context of emerging technologies, elucidating how knowledge influences acceptance and intention, leading ultimately to actual use behavior. The study also reveals two noteworthy moderating effects. Specifically, individuals with higher educational levels exhibit a stronger connection between knowledge and behavior, while acceptance is a more robust predictor of intention among older individuals. Overall, this work contributes to the broader discourse on technological adoption, offering insights pertinent to academic research and practical applications in technology management and organizational hyper-performance.