Understanding task-specific AI adoption among academic professionals: AI literacy, professional role, and responsible...

Artificial intelligence (AI) tools are increasingly embedded in academic work; however, little is known about why academics adopt them for some tasks but not others. Drawing on technology adoption, professional identity, ethical decision-making, and professional technology-use perspectives, this study examines how demographic/professional characteristics and AI literacy dimensions are associated with academics' use of AI tools for general academic tasks, academic writing, literature reviews, and visual content creation. Survey data were collected from 368 academics working at 116 universities in Türkiye. Binary logistic regression was the main explanatory approach, and supplementary machine learning analyses were used for predictive validation. The findings show that academic AI adoption is task-specific rather than uniform. Usage competence significantly predicted general academic use and literature review, whereas awareness, evaluation, and ethics did not show consistent direct effects on these outcomes. Academic title differentiated adoption in general academic use, academic writing, and literature reviews. Gender was associated with the literature review, whereas the visual content creation model showed limited explanatory power. This study provides empirical evidence regarding task-specific human-AI interaction and professional technology-use research by showing that academic AI use is associated with practical competence, professional role expectations, perceived task value, and task legitimacy, rather than generalized technology acceptance alone.