Artificial Intelligence and Digital Maturity in Asia-Pacific Higher Education: A Co-occurrence Analysis and Evidence-Informed Research Agenda
Juan Jose Prieto-Gutierrez
International Journal of Information Studies, Vol. 18, No. 4, 2026.
DOI: https://doi.org/10.6025/ijis/2026/18/4/205-226
Link: https://www.dline.info/ijis/fulltext/v18n4/ijisv18n4_3.pdf
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.