Artificial intelligence (AI) seems to introduce fresh prospects for language testing. Within the scope of activity theory, which emphasizes the combination of cultural and technical aspects of human actions, AI has the potential to present a dynamic experience in language testing. The testing process comprises preparation, adaption, scoring, and feedback within this theoretical framework. On the other hand, the use of AI in language testing includes certain drawbacks as well as its potential benefits. In addition, AI-based language testing has only recently started attracting scholarly attention. Thus, this entry presents an overview of the utilization of AI in language testing so far. For this purpose, the role of AI in language testing is highlighted before a theoretical framework is drawn within the scope of activity theory. Then, after defining AI-based language testing, the four steps are clarified: test preparation, adaptation, scoring, and feedback. The item also includes a brief discussion on the advantages and disadvantages of AI usage in language testing and recommendations about teacher training and ethical considerations.