Appropriating AI Tools in the Academic Workplace: Evaluation, Adaptation, and Incorporation among College Teachers

Abstract

 This study examined the appropriation of artificial intelligence tools among college teachers using the Model of Technology Appropriation as a framework and viewing the process through a human resource management lens. A total of 165 college teachers from the Philippines, selected through purposive sampling, completed an online questionnaire measuring six constructs across three levels of appropriation: evaluation, adaptation, and incorporation. The results showed that all six constructs fell within the strongly agree range, with the evaluation level scoring highest and the adaptation level scoring lowest; institutional support, in particular, showed the widest variation among teachers. All three levels were strongly and significantly correlated with one another, and among the two adaptation constructs, social shaping showed a stronger relationship with incorporation than institutional support. When grouped by teacher profile, licensure status showed no significant difference in incorporation, with licensed and non-licensed teachers reporting identical median scores. Academic rank showed a significant difference, with associate professors scoring higher than both assistant professors and instructors. Years of teaching experience and age both showed small but statistically significant negative correlations with incorporation. The results indicate that teachers reported favorable evaluation of the usability and value of AI tools, together with lower and more variable ratings of institutional support. Institutional support, social shaping, and differences across academic ranks are therefore areas that merit closer attention. The study offers practical implications for how academic institutions might design more targeted, rather than uniform, support for AI tool integration across their teaching workforces.