Scaling AI Access Across State Universities: A Multi-Institutional Platform Approach
Abstract
Multi-institutional AI infrastructure faces a fundamental tension: centralized solutions risk single points of failure and reduced flexibility, while decentralized approaches lead to duplicated efforts and fragmented expertise. This paper presents KI:connect.nrw, a platform addressing this challenge through distributed procurement combined with centralized infrastructure. Individual institutions maintain procurement autonomy while sharing development costs, technical infrastructure, and operational expertise.
Fields of Study & Subjects
Scientific Computing and Data Management
Ethics and Social Impacts of AI
Research Data Management Practices
Publication details
- Journal / source
- Proceedings of the 2026 ACM SIGUCCS Annual Conference
- Publisher
- ACM
- Pages
- 49–54
- Publication date
- 24 March 2026