This study investigated the impact of AI-Powered Personalized Learning Platforms on the Academic Achievement and Motivation of Computer Science senior secondary school students in Abuja Municipal Area Council (AMAC) FCT-Abuja, Nigeria. The study raised two research questions and two corresponding hypotheses which were tested at 0.05 level of significance. The study adopted a mixed research method; of both the quasi-experimental design and descriptive survey research design. The population of the study comprised all the public senior secondary school students in Abuja Municipal Area Council (AMAC), Federal Capital Territory (FCT). A sample of 100 students was selected through a combination of purposive and simple random sampling techniques for the study. The researchers adopted Code.org as a treatment instrument while the instrument for data collection was a researchers’ designed Computer Achievement Test (CAT) and Motivation Based Questionnaire (MBQ). A draft of the questionnaire was validated through expert judgment involving three lecturers. This was done to establish the face and construct validity. The reliability of the instrument was established through a test-re-test method. A reliability co-efficient of 0.85 and 0.80 was established for both instruments (CAT & MBQ). The data collected were analysed by using independent t-test statistics to test the two formulated hypotheses. The results indicated that Code.org significantly improved the academic achievement of secondary school students compared to traditional learning methods. Furthermore, Code.org positively impacted the motivation of secondary school students. The study recommended amongst others that schools should adopt AI-powered personalized learning platforms such as Code.org for teaching and learning