A Study on Institutional Improvement Strategies for Activating Spin-on of Private Advanced Technologies in the Field of Military Intelligent Virtual Training
This study highlights the urgent need to introduce scientific training systems based on Artificial Intelligence (AI) and Extended Reality (XR) in response to the rapid decline in military personnel and the evolving defense environment.While private-sector virtual reality and simulation technologies have advanced significantly, the "Spin-on" process -integrating private technologies into the defense sector -has been hindered by complex regulations and closed defense acquisition structures.Specifically, the study emphasizes bridging the technological gap between rapid private innovation and rigid military acquisition to enable timely modernization.Accordingly, this research explores institutional improvement strategies to swiftly incorporate private-sector disruptive innovation technologies into military virtual training frameworks.The methodology involves analyzing domestic and international literature, as well as the plans and ongoing initiatives of relevant organizations, to identify practical barriers.As key alternatives, this study proposes enhancing the effectiveness of the rapid demonstration acquisition system, applying security guidelines flexibly, and establishing an open virtual training platform for data sharing among the public, private, and military sectors.Ultimately, this study aims to lower entry barriers for private innovative technologies to advance military virtual training systems.Furthermore, it seeks to contribute to the creation of a national strategic Spin-on model and a virtuous cycle ecosystem where defense advancements flow back into private industries, bolstering overall national competitiveness.
Authors
- Jeong Soo Park
Institutions
- Kyungwoon University (KR)
Publication Details
- Journal
- Asia-pacific Journal of Convergent Research Interchange
- Published
- 2026-10-29
- DOI
- https://doi.org/10.47116/apjcri.2026.10.09
- Primary Topic
- Technology Assessment and Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00