The accelerated expansion of advanced technologies—particularly artificial intelligence, intelligent systems, and interactive digital environments—is influencing contemporary media ecosystems and contributing to changes in educational practices. This study provides a systematic and descriptive bibliometric mapping of recent scientific production on artificial intelligence in education, algorithmic ethics, and digital inequality. A total of 229 Scopus-indexed documents published between 2021 and 2026 were analyzed using Biblioshiny and VOSviewer to examine publication patterns, influential authors and sources, and the conceptual structure of the field. Results indicate a marked increase in research output since 2024, with an annual growth rate of 47.58%, an average of 8.68 citations per document, and an international co-authorship rate of 24.45%. These indicators reflect an expanding and increasingly collaborative research landscape, accompanied by a diversification of thematic priorities within the field. The analysis identifies five thematic clusters: (1) the technical foundations of AI and digital transformation; (2) intelligent and immersive learning environments; (3) personalized and adaptive learning systems; (4) AI literacy and pedagogical integration; and (5) ethical considerations, including algorithmic bias and educational robotics. The findings highlight the need for explicit justification of database selection, strengthened critical AI literacy, and context-sensitive strategies that address disparities in access, skills, and institutional capacity. Overall, this study offers a coherent overview of a research area that is currently expanding and undergoing conceptual reorganization, providing evidence-informed insights for future research, policy development, and the design of equitable AI-driven educational technologies.

This study examines institutional processes in digital justice through a mixed conceptual approach that integrates bibliometric analysis and technology-adoption modeling, incorporating artificial intelligence (AI) as a projected component rather than an implemented system. A corpus of approximately 200 Scopus-indexed documents (2003–2024) was analyzed, identifying five dominant thematic clusters: advanced technologies, institutional justice, digital government, judicial information management, and digital criminal justice. The results reveal persistent gaps in the literature, particularly in rural and underserved communities, where connectivity barriers and the limited application of adoption models hinder inclusive digital transformation. As an institutional contribution, the study presents the conceptual design of the digital solution “Travel Permits—Accessible Justice”, developed under a Service-Oriented Architecture (SOA) and projected for future integration with AI-supported components to automate judicial authorizations through biometric validation, electronic signatures, and digital delivery. To evaluate its potential acceptance, the Technology Acceptance Model (TAM) is analytically adapted and extended to the community-based judicial context, framing institutional learning processes as a prospective form of learning analytics focused on user interaction, perceived usefulness, perceived ease of use, and behavioral intention. Taken together, the integration of bibliometric evidence with an extended TAM, along with the projected incorporation of AI-supported institutional learning processes, offers a coherent foundation for future studies on inclusive digital innovation in justice environments.