Campus AI vs Commercial AI: A Late-Breaking Study on How LLM As-A-Service Customizations Shape Trust and Usage Patterns
2025/05/15 by Leon Hannig, Hannig, Leon, Annika Bush +7
Business, Management and Accounting · Computer Science · #Big Data and Business Intelligence #Blockchain Technology Applications and Security #Privacy-Preserving Technologies in Data #cs.CY
paper · pdf · doi:10.48550/arxiv.2505.10490
openalex publication_date 2025/05/15 · openalex created_date 2025/10/15 · openalex updated_date 2026/07/30
Abstract
As the use of Large Language Models (LLMs) by students, lecturers and researchers becomes more prevalent, universities - like other organizations - are pressed to develop coherent AI strategies. LLMs as-a-Service (LLMaaS) offer accessible pre-trained models, customizable to specific (business) needs. While most studies prioritize data, model, or infrastructure adaptations (e.g., model fine-tuning), we focus on user-salient customizations, like interface changes and corporate branding, which we argue influence users' trust and usage patterns. This study serves as a functional prequel to a large-scale field study in which we examine how students and employees at a German university perceive and use their institution's customized LLMaaS compared to ChatGPT. The goals of this prequel are to stimulate discussions on psychological effects of LLMaaS customizations and refine our research approach through feedback. Our forthcoming findings will deepen the understanding of trust dynamics in LLMs, providing practical guidance for organizations considering LLMaaS deployment.
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