Abstract:
International partnership development in higher education traditionally relies on the tacit knowledge and personal
networks of international office staff. While these human skills remain essential, institutions increasingly face challenges
from staff shortages, high turnover, and the loss of organizational memory, leaving valuable collaboration histories
fragmented across individuals.
To address this, our institution initiated a digital transformation (DX) strategy, integrating research publication data,
international collaboration records, and grant information into a shared digital foundation. This infrastructure preserves
institutional knowledge and enhances the visibility of regional connections. As this digital base matured, AI tools were
introduced as a natural extension of DX to support data analysis, pattern discovery, and opportunity identification within
the Asia-Pacific region.
This approach does not replace human expertise. Instead, AI manages large-scale data processing, while professional
staff contribute strategic judgment, cultural awareness, and trust-building capabilities.
Drawing on an ongoing pilot project, this presentation shares practical lessons in building institutional memory.
Participants will gain actionable insights into using DX and AI to reduce dependency on individual expertise and develop
sustainable international partnership strategies, demonstrating how technology can empower university workflows while
keeping human relationships at the center of global collaboration.
Learning objectives:
By attending this presentation, participants will be able to:
– Identify the operational risks of relying entirely on individual staff networks and the importance of Digital
Transformation (DX) in preserving institutional knowledge.
– Understand how to integrate fragmented institutional data, such as research publications and grants, into a shared
digital foundation to map existing regional connections.
– Learn practical ways to introduce AI tools as a natural extension of DX to analyze data and discover new
partnership opportunities.
– Explore effective Human-AI collaboration models that support strategic decision-making while maintaining humancentered
relationship management.
– Formulate practical approaches to transition from person-dependent practices toward sustainable, data-informed
internationalization strategies at their own institutions.
Target audience:
International office directors, global partnership managers, research development professionals, and university
administrators facing workforce constraints or seeking data-informed strategies to transition from person-dependent
practices to sustainable, institutional intelligence systems for global engagement.