Driving Institutional Digital Transformation Through Ethical AI-Enabled University Technology Transfer: Insights from ICCubeX

Abstract

Technology Transfer Offices (TTOs) play a critical role in converting university research into commercial impact, yet many face severe operational strain from manual workflows and limited staffing. This paper presents an Ethical AI-Enabled University Technology Transfer architecture, developed as a Design Science Research (DSR) case study based on the ICCubeX framework at Universiti Teknologi Malaysia (UTM). Positioned at the operational micro-layer to complement macro enterprise frameworks like COBIT, TOGAF, and SAFe, the modular architecture integrates a secure Retrieval-Augmented Generation (RAG) framework via access-controlled REST APIs to safeguard institutional data sovereignty. It employs a deterministic 85% mathematical confidence threshold to automatically route codified inquiries while directing complex, cross-disciplinary cases to an asynchronous Human-in-the-Loop governance layer to preserve officer validation and override authority. To ensure empirically testable outcomes, the framework establishes a Transformation Success Matrix targeting quantifiable benchmarks across inquiry turnaround agility, triage automation rates, and legacy database interoperability. The study contributes a theoretically grounded, governance-aware digital transformation blueprint for scalable and secure university technology transfer ecosystems.