Utilizing Artificial Intelligence for Personalized Digital Learning - Nendy Nendy Akbar Rozaq Rais (Artificial Intelligence Systems and Its Applications, 2025)
The digital transformation in education has opened up significant opportunities for leveraging artificial intelligence (AI) to personalize learning. This study aims to explore the use of AI in adapting content, methods, and learning pace to individual learner characteristics. The research method employed is a literature study with a descriptive qualitative approach, involving the analysis of various scientific sources from the last five years relevant to AI and digital education. The findings indicate that AI can enhance learning motivation, accelerate concept comprehension, and improve academic outcomes through features such as content recommendation systems, personal tutors, and adaptive assessments. Furthermore, AI supports more interactive and emotional learning experiences through the use of learning agents such as chatbots. Nevertheless, the implementation of AI faces several challenges, including data privacy, teacher readiness, infrastructure limitations, and algorithmic bias. The discussion highlights the need for regulation, educator training, and the development of ethical and inclusive systems to optimize the benefits of AI. These findings demonstrate that AI has great potential to revolutionize the digital learning ecosystem, but its implementation must be conducted wisely and responsibly.