This paper provides a systematic literature review of the application of Artificial Intelligence (AI) in education, with a particular focus on AI-driven approaches that enhance self-regulated personalized learning (SRPL)—an emerging educational framework combining both self-regulation and personalized learning approaches. The study aims to explore how AI can support the development of learners’ self-regulation skills through personalization of learning processes while also identifying existing research gaps and proposing directions for future exploration in AI’s integration into educational contexts. AI has been shown to significantly enhance personalized learning experiences and support student self-regulation. With the steady evolution of Artificial Intelligence technologies, research on self-regulated personalized learning (SRPL) is uncovering new theoretical, empirical, and methodological nuances to support learners. Notable developments include the increasing focus on hybrid AI-human collaboration and the expanding role of predictive analytics for early intervention. Future research should address the integration challenges of AI in education, with particular attention to ethical concerns.