The increased use of artificial intelligence (AI) in management curricula raises the need to integrate AI into assessment systems. For this purpose, this study used anxiety and resistance to change with an integrated variable, adoption readiness' to examine university teachers' attitudes towards AI-based assessment systems. We collected data from university teachers in social sciences and management disciplines from West Malaysia. Confirmatory factor analysis (CFA) was applied to determine the ability of the UTAUT model antecedent to the proposed method. After eliminating the distorting observed variable, this study used performance expectancy, effort expectancy, and facilitating conditions as ‘adoption readiness’. The results of path analysis indicated that (1) anxiety has a significant negative impact on adoption readiness and attitude of university teachers; (2) positive but insignificant impact of resistance to change on adoption readiness and attitude; (3) adoption readiness mediates the relationship between anxiety and attitude while; (4) no mediation role of adoption readiness was found between the relationship of resistance to change and attitude of the university teachers towards an AI-based assessment systems. This study significantly contributes to the existing pedagogical literature by synthesizing the UTAUT model's antecedents in a novel way to examine technology adoption readiness which further adds in the originality of this study.