The rapid evolution of artificial intelligence (AI) is transforming global education, with significant implications for how teaching and learning are designed, delivered, and evaluated. Among the most promising developments are the applications of AI in personalizing learning paths, automating content creation, and providing intelligent feedback. These functions not only address the challenges of large-scale education but also hold the potential to make learning more adaptive, efficient, and inclusive. This paper explores three interconnected domains: (1) how AI systems personalize learning through data-driven insights and adaptive pathways; (2) how generative AI automates learning material creation, offering scalable and dynamic resources; and (3) how AI-powered assessment tools provide real-time, intelligent feedback that supports learner progression. By reviewing current literature, industry applications, and emerging case studies, this research analyzes the pedagogical, technological, and ethical implications of AI in education. It also highlights opportunities for integrating generative AI models into higher education and professional development, while acknowledging the risks of bias, over-reliance, and data privacy concerns. The findings suggest that AI, when used responsibly, can enhance learner agency, empower educators, and reshape assessment practices for the 21st century.
S. Chakraborty (Sun,) studied this question.