Generative Artificial Intelligence in Education: Opportunities, Risks and Pedagogical Implications: A Systematic Review

Abstract

The rapid emergence of generative artificial intelligence (GenAI), particularly large language models (LLMs) such as ChatGPT, is transforming educational systems by creating new opportunities and challenges for teaching and learning. This systematic review synthesizes recent research on the opportunities, risks, and pedagogical implications of generative AI in education following PRISMA 2020 guidelines. A comprehensive search across SciSpace, Google Scholar, PubMed, and ArXiv identified 345 publications from 2020–2026. After deduplication and relevance screening, 30 key studies were selected for detailed synthesis. The findings highlight major opportunities including personalized learning, enhanced content generation, improved accessibility, programming and writing assistance, automated feedback, and innovative teaching practices. However, significant risks were identified: academic integrity concerns, over-reliance on AI tools, reduced critical thinking, algorithmic bias, privacy challenges, equity gaps, and misinformation from AI hallucinations. The review underscores the need for curriculum redesign, assessment reform, teacher professional development, ethical governance frameworks, and AI literacy integration. Generative AI holds transformative potential for education, but effective adoption requires balanced policies and responsible pedagogical strategies. Future research should focus on longitudinal learning outcomes and evidence-based implementation frameworks across diverse educational contexts.