Navigating the AI-Education Nexus: Mitigating Academic Integrity Challenges in the Era of Generative AI

Generative AI is reshaping teaching and assessment in higher education, but its capacity for misuse raises new concerns about academic integrity. This study examines approaches that higher education educators can take to safeguard honesty in students’ academic work while also harnessing AI to enrich learning and evaluation. Based on a systematic literature review (SLR) method, this study identified five interconnected strategic themes: (1) Policy and Guidelines for AI in Education; (2) AI Education and Training; (3) Attitudes towards GenAI in Education; (4) Transparency, Communication, and Engagement; and (5) Assessment Design and Format. These elements are integrated into a holistic conceptual framework that connects capability development, cultural transformation, and structural safeguards, and presents practical guidance to address key academic integrity challenges. Our findings show that isolated efforts by academics are not enough, and only an integrated, values-led approach can maintain assessment integrity, foster critical and creative skills, and prepare graduates for workplaces increasingly shaped by AI.