717 Indus Journal of Social Sciences Online ISSN: 2960-219X Print ISSN: 2960-2203 Volume 3, Number 1, 2025, Pages 717 – 733 Journal Home Page https://induspublishers.com/IJSS/about Artificial Intelligence in Physics Education: Transforming Learning from Primary to University Level Muhammad Shafiq 1 , Muhammad Adnan Sami 2 , Nudrat Bano 3 , Rida Bano 4 & Muhammad Rashid 5 1 Lecturer, Kohinoor Grammar School & College, Jaranwala Road Faisalabad, Punjab, Pakistan, 38000, Email: mshafiq9996@gmail.com 2 BS Scholar, University of Agriculture, Agriculture University Road, Faisalabad, Punjab, Pakistan, 38000, Email: adnansamii.pk@gmail.com 3 MS (SE), University of Agriculture, Agriculture University Road, Faisalabad, Punjab, Pakistan, 38000, Email: nudrataliahmad@gmail.com 4 MS (SE), University of Agriculture, Agriculture University Road, Faisalabad, Punjab, Pakistan, 38000, Email: ridarana2020@gmail.com 5 Senior Subject Specialist, Education Department, Government of the Punjab, Faisalabad, 38000, Punjab, Pakistan, Email: rmuh003@aucklanduni.ac.nz, ORCID: https://orcid.org/0009-0002-1257-7686 ARTICLE INFO ABSTRACT Article History: Received: February 03, 2025 Revised: March 06, 2025 Accepted: March 08, 2025 Available Online: March 10, 2025 Keywords: Artificial Intelligence (AI), Education, Machine Learning (ML), Physics, Students The teaching and learning in physics have undergone complete transformation through AI-driven intelligent tutoring systems adaptive learning stages and virtual labs that produce enhanced student involvement, interactive simulations and immediate feedback. The AI-powered Physics Education Technology (PhET) Interactive Simulations together with ChatGPT enables students to experiment with concepts by applying detailed explanations on complex physics theories to help abstract knowledge become more understandable. The deployment of AI resolves key educational obstacles since it delivers virtual labs alongside chatbots to make quality training more accessible for differential learners and resource-challenged students. Education integration of AI in physics faces major hurdles because of equity problems together with its expense burden and human resistance to adaptation and worries related to privacy of data and algorithmic discrimination. While AI instruments deliver better solutions for complex problems and enhanced understanding of concepts they do not reach scientific problem complexity levels which require human-like reasoning and heavy reliance on AI tools could hinder students' critical thinking abilities. Organizations receiving government financing along with training programs for teachers and ethical guidance must identify these challenges to establish high-quality physics education instruments. The supportive combination of AI with augmented reality and quantum computing enables educators and policymakers and researchers to collaborate for new educational breakthroughs. Responsible AI implementation enables physics education to achieve its goal of accessibility along with producing intriguing learning experiences which deliver effective 21st-century skill acquisition. The evolution emphasizes future progress in making traditional learning practices better through AI while developing careful implementation methods to help teacher reforms. Corresponding Author: Muhammad Rashid Email: rmuh003@aucklanduni.ac.nz