Transforming Physics Education Through Artificial Intelligence: A Systematic Review

Artificial Intelligence (AI) is progressively transforming the landscape of education, offering novel approaches to teaching, learning, and assessment. Artificial intelligence (AI) is advanced technology and physics is old natural science. The merging of two fields and setting new trends in physics education is inspiring for students. AI is an interesting learning tool for physics education. AI tools are efficiently applied in physics to enhance data intensive techniques. In physics education, characterized by abstract concepts and complex problem-solving, AI tools hold significant potential to enhance both instructional methods and learner outcomes. This paper reveals the reviewed data about AI- driven tools and its application in physics education. This systematic review examines the current applications, trends, and implications of AI technologies in physics education across secondary and higher education contexts. By analyzing studies published over the last decade, author identify key AI technologies employed, including personalized learning, machine learning-based assessment tools, adaptive learning platforms, and AI-powered simulations. A comprehensive search strategy will be applied across major academic databases including Google Scholar and Web of Science, focusing on studies published between 2020 and 2024.Our review highlights how these technologies contribute to personalized learning experiences, improved conceptual understanding, and increased student engagement. Through a thematic analysis of selected literature, we also explore future directions for research and development. The review concludes by offering recommendations for educators and policymakers aiming to leverage AI in physics education, stressing the need for evidence-based strategies and ethical considerations. Overall, this paper provides a comprehensive overview of how AI is shaping physics education today and suggests pathways for its effective and responsible use in the future. This article aims to provide review of the AI paradigm in physics and inspire physics learners to explore new advances in physics.