The field of AI-enhanced learning is rapidly evolving, with a growing focus on developing innovative solutions that support student engagement, retention, and academic achievement. Recent research has explored the potential of AI-powered tools to facilitate hybrid human-AI regulated learning, where AI provides targeted scaffolding while preserving the learners' role as active decision-makers. This approach has shown promise in fostering self-regulated learning and promoting deep cognitive engagement. However, there is also a need for critical consideration of the potential risks and limitations of AI integration in education, including the potential for cognitive atrophy, loss of agency, and unequal access to emerging technologies. Noteworthy papers in this area include the introduction of a transformative AI framework for student dropout prediction, which achieves high accuracy and generates interpretable interventions. Another notable study investigates the impact of GenAI and search technologies on retention, highlighting the need for balanced technology integration in education to promote long-term knowledge retention.