In language assessment, AI technology has been incorporated in task design, assessment delivery, automated scoring of performance-based tasks, score reporting, and provision of feedback. AI technology is also used for collecting and analyzing performance data in language assessment validation. Research has been conducted to investigate the efficiency and functionality of assessment technologies, but empirical explorations on test-taker engagement in AI technology-mediated language assessment are remarkably scarce. In this commentary, we first examine the impact of AI technology on test takers, in terms of both the benefits and the challenges that it poses in the critical stages of language assessment development and validation. Next, we propose a conceptual model to facilitate the implementation and evaluation of test-taker engagement in AI technology-mediated language assessment. The model delineates two forms of test-taker engagement: test takers' participation in technology-mediated assessment activities and their perceptions of technological innovations in language assessment. We then review the articles in this special issue based on this model and discuss directions for future research. We conclude by offering some guidance for maximizing test-taker engagement in technological innovations, thereby promoting learning-oriented and equity-minded language assessment.