Why Do University Students Use AI: Drivers and Barriers?

As generative artificial intelligence becomes integrated into academic life, understanding what drives student adoption is essential for informed institutional policy. This study examines AI engagement among 672 students at a public midsize southern university, integrating the Technology Acceptance Model (TAM) and Social Cognitive Theory (SCT) to evaluate eight constructs: perceived usefulness, perceived ease of use, perceived trust, perceived risk, social influence, self-efficacy, anxiousness, and affection. Survey data show students frequently use AI for information retrieval and writing assistance, while specialized applications such as graphic and video generation remain underutilized. Regression analysis shows perceived usefulness, affection, and trust are the primary positive predictors of adoption, whereas anxiety and perceived risk are significant deterrents. Notably, affection, the emotional enjoyment of technology, emerged as one of the most consistent motivators across academic tasks, from research to creative ideation. These results suggest emotional and trust-based factors are as critical as functional utility in shaping student behavior. Universities should prioritize emotional comfort and ethical trust alongside technical training to foster responsible, confident AI integration..