Scaling AI Access Across State Universities: A Multi-Institutional Platform Approach

ACM SIGUCCS Annual Conference (SIGUCCS), pp. 49–54

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.

Authors 3

1. Bernd Decker Aachen IT centre

   RWTH Aachen University

   Affiliation as printed

   IT Center, RWTH Aachen University, Aachen, NRW, Germany

2. Uta Christoph Aachen IT centre

   RWTH Aachen University

   Affiliation as printed

   IT Center, RWTH Aachen University, Aachen, NRW, Germany

3. Sarah Grzemski Aachen IT centre

   RWTH Aachen University

   Affiliation as printed

   IT Center, RWTH Aachen University, Aachen, NRW, Germany