Ángel Alberto Nava Chirinos
The strategic integration of Artificial Intelligence (AI) in higher education is a global priority, yet conceptual fragmentation persists regarding its effective adoption. This study identifies key drivers of AI adoption through a bibliometric review of 547 Sco-pus-indexed documents (2019–2024) using thematic mapping in RStudio to visualize topic evolution and density. Findings are organized into three dimensions: (1) essential elements, including institutional infrastructure, governance, and adoption policies; (2) practical recommendations, such as faculty training in generative AI, ethical guidelines, and curriculum integration of digital competencies; and (3) critical success factors, like stakeholder attitudes, technological trust, and institutional leadership. The study offers theoretical, methodological, and practical contributions. Theoretically, it presents a systemic framework aligning infrastructure, practices, and adoption conditions. Meth-odologically, it validates thematic mapping as a tool for structuring complex literature. Practically, it provides an evidence-based roadmap for institutional leaders, policymak-ers, and faculty developers to implement sustainable AI initiatives aligned with Education 4.0. Additionally, it highlights research gaps to inform future agendas, especially in underrepresented regions.