A Systematic Review of AI-Backed Tools in Education

Artificial Intelligence (AI) has rapidly transformed education, offering personalization, automation, and learning scalability opportunities. As AI tools gain popularity, there is an immediate need to categorize, evaluate, and understand their varied functionalities and implications within educational environments. This study provides a structured taxonomy of AI-backed tools currently used in education, organizing them into three primary categories: solver tools, multimedia creation tools, and feedback/rephrasing tools. Each category is examined for its functionality and associated challenges, including ethical concerns, data privacy, and potential misuse. The study reviews recent literature and tools to understand methods to reshape the teaching-learning ecosystem. This study intends to inform educators, developers, and policymakers on effective integration strategies and responsible use. It also highlights the importance of AI detection tools, identifies unresolved risks such as AI misinformation and guardrail evasion, and argues for a balanced approach to AI adoption in educational contexts.