Artificial Intelligence and Digital Maturity in Asia–Pacific Higher Education: A Co-occurrence Analysis and Evidence-Informed Research Agenda

Juan Jose Prieto-Gutierrez

Juan Jose Prieto-Gutierrez Complutense University of Madrid Spain jujpriet@ucm.es

Abstract

This study synthesizes the supplied analysis of artificial intelligence (AI) and digital maturity in Asia–Pacific (APAC) higher education and reorganizes the findings into a coherent research framework. The analysis combines a conceptual map, keyword co-occurrence networks, a co-occurrence strength matrix, a staged research agenda, an impact feasibility prioritization matrix, a gap to agenda mapping, thematic coverage assessment, and an illustrative latent growth model (LGM) framework for institutional AI-DMI trajectories. Across these outputs, AI and infrastructure emerge as central hubs, while teaching and learning, research, connectivity, high-performance computing (HPC), leadership, strategy, training, utilization, incentives, and curriculum form an interconnected maturity ecosystem. The analysis indicates that the most actionable challenges are not limited to technology availability; rather, utilization, incentives, shared capacity, and the alignment between institutional strategy and implementation represent major leverage points. The proposed research agenda therefore progresses from short-term longitudinal measurement and evaluation of existing pilots to medium-term studies of incentives, shared computing capacity, and curriculum effects, and finally to system-level maturity pathways, governance, ecosystem design, and inclusive AI transformation. The LGM framework extends the analysis from static benchmarking to longitudinal explanation by allowing institutions to differ in baseline maturity and rates of change and by testing predictors of those trajectories.

References

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