Is generative artificial intelligence becoming addictive? An exploration among undergraduate students

Abstract

This study aimed to examine the multidimensional nature of Generative Artificial Intelligence (GAI) addiction among undergraduate students. For this purpose, firstly, the Generative Artificial Intelligence Addiction Scale (GAI-AS) was developed and administered to 919 undergraduate students. The GAI-AS was designed as a psychometrically valid instrument to assess addictive patterns of GAI use across four dimensions: salience, excessive dependency, mood modification, and functional impairment. The findings provide strong evidence of the scale's validity and reliability. Subsequently, the validated instrument was administered to 803 undergraduate students to investigate demographic and usage-related differences in GAI addiction tendencies. Findings revealed no significant differences in GAI-AS scores according to gender or type of GAI version used (free vs. paid). Grade-level differences were observed only in the dimension of excessive dependency, with freshman students reporting slightly lower scores than upper-class students. In contrast, frequency of GAI use emerged as a strong and consistent predictor, as daily users showed significantly higher scores across all four dimensions and on the total scale. Correlation analyses further demonstrated moderate positive associations among all GAI-AS sub-dimensions, supporting the conceptualization of GAI addiction as an interconnected behavioral and emotional phenomenon. These findings clarify GAI addiction as a psychological construct and provide a validated scale.