From Automation to Personalization: A Comprehensive Survey on the Role of AI in Modern e-Learning

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in e-Learning, enhancing the way educational content is delivered, accessed, and personalized. Rooted in technologies such as machine learning, natural language processing, and intelligent agents, AI now powers systems that adapt to learners’ needs, automate assessments, and provide real-time feedback. This paper presents a comprehensive survey tracing the evolution of AI in e-Learning, beginning with early automation tools, such as static content delivery systems and rule-based intelligent tutors, and progressing to advanced personalization strategies that tailor instruction based on learner behaviour, preferences, and engagement. It explores foundational AI technologies, key application domains across, higher education, and corporate training, and highlights global platforms like Coursera, Duolingo, and Squirrel AI that exemplify modern AI-driven education. The paper also outlines core evaluation metrics, including personalization accuracy, engagement levels, learning gains, and data privacy considerations. In addition to documenting achievements, the study critically examines challenges such as algorithmic bias, explainability gaps, equity issues, and teacher-AI collaboration. Looking forward, it identifies open research areas including hybrid human-AI teaching models, culturally aware personalization, and the integration of multimodal learning data. Ultimately, this survey advocates for the responsible, inclusive, and ethically grounded development of AI systems to ensure that future e-Learning environments are not only intelligent, but also equitable and human-centered.