This review looks at the challenges and methods for using generative AI in academic writing across many subjects. Recent studies (2023–2024) that used mixed methods, case studies, and theory show many ways AI is used in schools. Students use AI tools for brainstorming, creating ideas, and check-ng their work [1]. There are problems with academic honesty, basic learning, and grading methods [2]. In science and tech, AI-written text can sometimes match or even be better than student work. In subjects like history and literature, it is hard to keep a student’s unique voice and style [3]. Students and teachers see AI very differently. This gap grows because schools do not give enough training and the rules are not clear [4]. Studies show that AI affects each sub-ject in its own way. There are concerns about keeping work real and helping students think clearly [5].