Artificial intelligence (AI) is transforming education by enhancing experiences and learning and introducing innovative and tailored approaches to meet learners’ needs. This systematic review explores the application of emerging AI technologies in education, with a focus on adaptive learning technologies and personalized learning environments. Previous reviews have addressed AI technologies for education, but most lack comprehensiveness in addressing key challenges and approaches. This study aims to bridge the gaps through analysis and integration of AI to improve teaching and learning processes. The review identifies AI technologies, such as intelligent tutoring systems, algorithms such as predictive learning, and adaptive learning frameworks, that have shown great potential in transforming traditional education. By leveraging advanced AI technologies, institutions can enhance cognitive and customizable learning attributes, as well as enable personalized learning to improve learning outcomes. The findings highlight the role of AI in addressing systemic educational challenges, including the many discrepancies in meeting individual learners’ needs and others to improve teaching methods. This study also discusses practical implications, including the impact of AI on university systems and infrastructure, particularly in the context of recent global challenges such as the pandemic. Future research directions emphasize the importance of integrating AI into educational change, and examining the social and cultural implications, to address the limitations of current AI applications. Through critical assessments of recent developments, this review provides a roadmap for leveraging AI to revolutionize education and improve learner engagement, adaptability, and performance.