Development of an AI Governance Model for Higher Education Using the Capability Maturity Model Integration (CMMI) - Walhidayah, Irfan; Surendro, Kridanto (Jurnal Teknik Informatika (Jutif), 2025)
The increasing adoption of Artificial Intelligence (AI) in higher education presents strategic opportunities for institutional transformation, while introducing complex challenges related to ethics, accountability, transparency, and regulatory compliance. Responding to the growing complexity of AI implementation in academic environments , this study proposes a governance model for AI named GOVAIHEI (Governance of Artificial Intelligence for Higher Education Institutions), conceptualized using the Capability Maturity Model Integration (CMMI) framework. The model was developed using the Design Research Methodology (DRM), which consists of four stages: Research Clarification, Descriptive Study I, Prescriptive Study, and Descriptive Study II. GOVAIHEI encompasses five primary domains: Data and Information, Technology and Infrastructure, Ethics and Social Responsibility, Regulation and Compliance, and Monitoring and Evaluation. Each domain is articulated into capability areas and measurable practices, assessed using the tiered NPLF scale (Not, Partial, Largely, Fully Achieved) to determine institutional capability and maturity levels. The model was validated through expert judgment by three domain specialists, confirming its relevance, methodological soundness, and alignment with CMMI principles. A web-based evaluation system was also developed using Laravel, PostgreSQL, Redis, and Nginx, enabling structured, efficient, and automated assessments. Implementation in a case study at Institute XYZ revealed an initial maturity level (Level 1) with development goals toward Level 3 (Defined). The findings demonstrate a practical foundation for navigating the multifaceted nature of AI adoption in higher education through a structured and adaptable governance approach, which aligns with the increasing demand for robust digital governance frameworks in technology-driven environments.