The science of reading meets the science of learning: memory systems, structured literacy, and the role of AI.

As terms like the Science of Reading and Science of Learning gain prominence in education policy and practice, there is a growing need to clarify what learning entails at a cognitive systems level. In this perspective review, we argue that meaningful instructional practice, particularly in the context of artificial intelligence (AI), must align with the distinct yet interacting memory systems that support human learning across development. Drawing on cognitive science, neuroscience, and educational psychology research, we provide a functional overview of implicit and explicit memory systems and examine their relevance for literacy development. We then frame Structured Literacy within the instructional hierarchy, illustrating how each learning phase (i.e., acquisition, fluency, generalization, adaptation) involves specific learning mechanisms and instructional demands. Finally, we evaluate how AI tools may support or undermine these processes and propose phase-specific approaches to responsible integration. AI should be judged not by its technical sophistication, but by its capacity to support memory systems, preserve teacher agency, and promote lasting, transferable literacy outcomes, especially for vulnerable learners. These are empirical questions. This perspective review is intended to motivate future research into Structured Literacy framed within a more expansive understanding of the science of learning and the responsible, efficacious use of AI in education.