The AI is transforming how countries learn by providing adaptable, data-driven learning experiences that respond to learners' cognitive states, behavioral patterns, and educational paths. This paper explores the convergence of AI and educational psychology, investigating how an AI-assisted learning system operationalizes recent psychological concepts, such as cognitive load theory, self-regulated learning (SRL), and Vygotsky's Zone of Proximal Development, to maximize the instructional process. Based on recent empirical data from meta-analyses and randomized controlled trials, this research reports that AI-supported learning significantly increases academic performance (cohensions d = 0.68, 95% CI [0.41, 0.95]) compared with traditional learning. Moreover, AI-personalized learning systems reduce additional cognitive load by 34 percent among learners with cognitive deficits. The evidence indicates that AI is useful for learning when it provides purposeful practice and profound thinking that align with learners' cognitive development.