AI-Driven Transformation of Higher Education a Systematic Review

Artificial Intelligence (AI) is a powerful catalyst for change, fundamentally reshaping the landscape of higher education by altering traditional methods of teaching, learning, and administration. This study aims to provide a comprehensive overview of this AI-driven transformation by systematically reviewing recent scholarly literature. The object of this research is to identify, categorize, and analyze the primary applications and documented impacts of AI within higher education institutions. Employing a Systematic Literature Review (SLR) methodology guided by PRISMA principles, this study analyzes 62 peer-reviewed articles sourced from the Scopus database, published between 2021 and 2024. The results indicate a significant and accelerating global research interest in this domain, with key applications concentrated in academic support, personalized learning enhancement, automated assessment, and administrative efficiency. While the findings confirm that AI integration significantly enhances educational outcomes and operational effectiveness, they also reveal critical challenges. A prominent theme across the literature is the emergence of significant ethical concerns, including inequities in technology access, data privacy, and the potential for over-reliance on AI tools, which may hinder the development of critical thinking skills. In conclusion, while AI offers transformative potential for higher education, its successful and ethical integration is not guaranteed. The findings imply an urgent need for policymakers and institutional leaders to establish robust governance frameworks that balance technological innovation with pedagogical integrity and equity, ensuring that AI serves as a tool for positive and inclusive educational advancement.