AI-Driven Learning Management System Integration In Selected Local Colleges and Universities (LCUs) In Calabarzon: A Readiness Assessment Framework

The rapid advancement of artificial intelligence (AI) is reshaping the educational landscape, offering new opportunities to enhance learning experiences and administrative efficiency. This study assesses the readiness of selected Local Colleges and Universities (LCUs) in Calabarzon in integrating an AI-driven Learning Management System (LMS). The study evaluates three key dimensions: (1) technology readiness, which includes IT infrastructure—hardware, software, and network capabilities; (2) people readiness, focusing on AI literacy among faculty and students, including AI knowledge, skills, ethical awareness, and attitudes toward AI; and (3) process readiness, which examines behavioral determinants such as performance expectancy, effort expectancy, and social influence, shaping stakeholders’ acceptance of AI-driven LMS. A descriptive quantitative research design was employed, utilizing structured surveys, interview, and observations to gather data from administrators, faculty, and students. Findings indicate varying levels of preparedness among LCUs, with some institutions demonstrating strong IT infrastructure while others face limitations. AI literacy among stakeholders was found to be moderate, with a need for further training to develop technical competencies. Behavioral factors significantly influenced stakeholders' willingness to adopt AI, with concerns over data privacy, system reliability, and institutional policies emerging as potential barriers. The study proposes a Readiness Assessment Framework that integrates technology, people, and processes, guided by the International Organization for Standardization (ISO/IEC 42001) standards. The findings underscore the need for strategic planning, investment in IT infrastructure, AI literacy training, and the development of institutional policies to facilitate AI adoption in education. By addressing these areas, LCUs can ensure a seamless transition to AI-driven LMS, ultimately improving the quality of teaching and learning.