Role of AI in Enhancing Teaching Learning Processes and Academic Performance

Artificial Intelligence (AI) has emerged as a significant driver of innovation in education, reshaping teaching learning processes and influencing academic performance across educational levels. This study synthesizes Scopus- and ABDC-indexed research to examine how AI-supported technologies enhance instructional effectiveness, learner engagement, and academic outcomes. The literature indicates that AI-driven adaptive learning systems personalize instruction by aligning content and feedback with individual learner needs, leading to improved comprehension and reduced learning disparities (Cheng et al., 2020). Learning analytics and automated feedback tools further support data-informed teaching practices and continuous formative assessment, which positively influence academic persistence and performance (Sailer et al., 2021). From the learner perspective, intelligent tutoring systems and recommendation engines foster motivation, self regulation, and sustained engagement, indirectly contributing to improved academic achievement (Zhai et al., 2021). However, the effectiveness of AI integration depends on teacher readiness, pedagogical alignment, and ethical governance, with concerns related to data privacy and algorithmic bias remaining prominent (Williamson & Eynon, 2020). The study concludes that AI enhances academic performance primarily through its impact on teaching–learning processes rather than direct automation, emphasizing the need for human centered and ethically grounded AI adoption in education.