This study examines how artificial intelligence (AI) can enhance learning outcomes in Chinese high schools, with a particular focus on bridging regional disparities between resource-rich coastal regions and under-resourced inland provinces. Utilizing AI-driven Personalized Learning Paths (PLPs), the research demonstrates that tailored and adaptive learning environments not only boost academic performance but also help to mitigate educational inequities. Grounded in Constructivist Learning Theory and Self-Determination Theory, our analysis employs Partial Least Squares Structural Equation Modeling (PLS-SEM) to reveal that AI positively influences learning outcomes both directly and indirectly through the mediation of PLPs. The findings offer practical recommendations for policymakers and educators, including targeted investments in technological infrastructure and teacher training programs, thereby providing a roadmap for achieving a more equitable and effective educational system.
