The Generative Artificial Intelligence (GenAI) Divide: Exploring the Individual Factors Influencing GenAI Competency,Adoption Readiness,and Psychological Barriers

Abstract

Generative artificial intelligence (GenAI), a branch of AI capable of producing novel content from human input, is poised to transform various aspects of society. However, the benefits and challenges of GenAI adoption are not equally distributed, contributing to a new layer of digital inequality, the GenAI divide. This study examines the individual factors associated with psychological barriers, GenAI competency, and adoption readiness. Using data from a stratified online survey of 305 participants, the study explores sociodemographic variables (e.g., sex, age, race, education, and income), as well as competency factors (e.g., operational and creative skills) and psychological factors (e.g., attitudes toward AI, GenAI decision reliance, and self-efficacy). Findings reveal that operational skills and comfort with AI were significantly associated with lower anxiety and higher adoption readiness, whereas negative technology attitudes were associated with increased barriers. Furthermore, greater reliance on GenAI for decision-making was associated with lower self-assessed competency, suggesting a compensatory mechanism in which less confident users may increasingly depend on automated recommendations. These results highlight the multi-dimensional nature of the GenAI divide, emphasizing the interplay between individual-level factors and inequality-related outcomes. The study underscores the need for targeted interventions, such as AI literacy programs and supportive digital communities, to address these disparities and promote equitable access to the benefits of GenAI. By identifying key factors associated with GenAI adoption, this research contributes to a deeper understanding of digital inequality in the age of generative AI technologies.