Artificial Intelligence in Education and Territorial Governance a Bibliometric Analysis of Educational Inequalities

Artificial intelligence (AI) is rapidly transforming educational systems and governance models worldwide. While recent advances in digital technologies, machine learning, and educational platforms offer unprecedented opportunities for personalized learning and regional development, they simultaneously amplify deep-seated structural concerns regarding educational inequalities, the geographic digital divide, and unequal resource distribution. This study provides a rigorous bibliometric analysis of the scientific literature mapping the intersection of AI in education, territorial governance, and socio-educational equity. Utilizing a refined dataset of 663 peer-reviewed documents extracted from the Scopus database, we deploy the Bibliometrix and Biblioshiny Rpackages alongside VOSviewer to conduct performance analytics and structural science mapping. Our findings reveal an exponential field expansion characterized by an annual growth rate of 47.95 percent, driven by major academic hubs in the Asian region.Keyword co-occurrence networks and programmatic thematic mapping identify a crucial shift from technical algorithmic configurations toward specialized socio-technical domains-specifically generative AI governance, inclusive educational analytics, and digital equity.This paper provides a conceptual framework to understand how advanced machine learning intersects with local policy boundaries, offering a strategic roadmap for researchers and policymakers to leverage digital tools while mitigating systemic marginalization.