This research was conducted with the aim of investigating the impact of feedback from artificial intelligence tools on students' motivation and personalized learning in English language acquisition. The research method was quasi-experimental with a pre-test and post-test design. The statistical population included high school students, from whom 45 students were selected using a purposive sampling method and divided into three equal groups: a teacher feedback group, an AI feedback group, and a hybrid feedback group. The educational intervention was implemented over a 6-session period. The research instruments included the Hermans 1977 Achievement Motivation Questionnaire and a researcher-made personalized learning questionnaire. Covariance analysis was used to analyze the data. The results showed that both the AI feedback and hybrid feedback groups had a significant impact on increasing students' achievement motivation and enhancing their personalized learning. Furthermore, in a comparison among the groups, hybrid feedback was significantly more effective than teacher feedback, but in the area of personalized learning, no significant difference was observed between AI feedback and hybrid feedback. These findings indicate the high potential of artificial intelligence as an effective tool for increasing motivation and enhancing personalized learning in students.