Background: Generative Artificial Intelligence (GenAI), embodied by large language and diffusion models (e.g., ChatGPT, Bard, DALL·E), is fundamentally transforming higher education (HE), necessitating a systematic and comprehensive synthesis of its pedagogical and institutional implications.

Methods: This systematic review analyzed a core body of recent (2020–2024) peer-reviewed literature (N=16 references) to map the transformative applications, inherent ethical and policy challenges, and required future pedagogical frameworks for GenAI integration in HE.

Results: The findings confirm that GenAI is fundamentally reshaping the educational landscape. The strongest impact identified, synthesized from 12 key studies, is its capacity for enabling personalized instruction and adaptive learning, especially within English-Medium Instruction (EMI) contexts. Furthermore, GenAI is demonstrably driving innovation in assessment design, enhancing digital multimodal composing, and necessitating an overhaul of academic integrity frameworks. Crucially, a significant competency gap among faculty and substantial institutional policy-practice disconnects present the most critical barriers to equitable and effective integration.

Conclusion: GenAI offers substantial and non-negotiable benefits—including efficiency, accessibility, inclusivity, and creativity—but its responsible integration is complicated by significant ethical and policy challenges, notably algorithmic bias, data privacy, equitable resource access, and intellectual property concerns. Future research must pivot to focus on implementation science, faculty professional development, and advanced ethical governance, necessitating immediate interdisciplinary collaboration to establish robust, responsible, and inclusive AI-driven educational frameworks.

Generative AI, Higher Education, Systematic Review, Academic Integrity

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