From literacy to behavioral intention: A survey of soon-to-graduate students’ intention to use generative AI for job search through the technology acceptance model
Huai-yu Chen, Yu Chi · Computers in Human Behavior Reports · 2026
This study examines the factors associated with soon-to-graduate college students’ intention to use generative artificial intelligence (GenAI) in the context of job searching, guided by the Technology Acceptance Model (TAM). An online survey of US undergraduates expected to graduate within 12 months ( N = 300) showed that GenAI literacy significantly predicted perceived usefulness and perceived ease of use. Findings from PROCESS Model 6 indicated an indirect association between GenAI literacy and intention to use through perceived usefulness. Relative weight analysis revealed creative application as the strongest contributor to intention to use and perceived usefulness, while communication proficiency most strongly predicted perceived ease of use. Ethical competence was the least predictive across all outcomes. This study contributes a context-specific empirical application of TAM to GenAI use in job search and highlights the value of examining GenAI literacy as a multidimensional antecedent within that context. Implications for higher education, career preparation, and GenAI literacy development are discussed.