Generative AI in Education: Opportunities, Risks and Academic Integrity

Abstract - ChatGPT and similar tools have entered universities faster than policies could be written for them. To understand what this means in practice, this paper brings together the findings of five recent peer-reviewed studies on generative AI (GenAI) in higher education, covering teaching, learning and assessment, and then turns to the situation in India. The studies are read through a thematic analysis built around four areas: academic integrity and detection, learning opportunities, privacy, bias, copyright and ethics, and policy readiness. They agree that GenAI can offer students personalised feedback and support different kinds of learners. They also agree that detection software is unreliable, and that unclear rules, weak infrastructure and limited teacher training hold back the benefits. From these findings the paper proposes a four-part framework for responsible use, with recommendations for institutions, teachers, students and policymakers. It concludes that assessment redesign, clear rules and AI literacy protect integrity better than detection tools alone, and that field research in Indian institutions is still needed.