Utilising artificial intelligence embedded cloud computing technology to manage the archives at the colleges of education in Ghana

Abstract

Artificial intelligence embedded cloud computing technology refers to the integration of artificial intelligence capabilities directly into cloud computing and storage infrastructure to enable scalable and intelligent processing of data to protect digital archival records and ensure records can be accessed remotely. The purpose of this study was to investigate the utilisation of artificial intelligence embedded cloud computing technology in managing digital archival records at the colleges of education in Ghana. The theories underpinning this study are the Technology Fit theory and the Digital Transformation theory. The study adopted a convergent mixed methods research design, combining quantitative and qualitative data collection techniques, including questionnaires, interviews, observations, and document reviews. The population sampled included College Secretaries, Human Resource Officers and Information Technology Officers of the sampled Colleges of education. Quantitative data were analysed descriptively using tables and charts, while qualitative responses were quoted verbatim and thematically interpreted. The findings revealed significant challenges in records management practices within the colleges of education, including policy voids, outdated archival systems, infrastructural inadequacies, and limited technical skills among staff. Despite these challenges, respondents demonstrated a generally positive perception toward the adoption of artificial intelligence technologies, citing benefits such as enhanced automation, metadata creation, efficient retrieval, and reduced human errors. However, usability and effective integration of artificial intelligence systems were found to be contingent on user training, intuitive interface design, and institutional readiness. The study further identified critical skill gaps in digital and artificial intelligence literacy, and the absence of cloud-based infrastructures as major hindrances. Based on the findings, the study recommends the adoption of an artificial intelligence-powered cloud computing framework tailored to the Ghanaian College of Education context. This framework encompasses policy reforms, infrastructure development, capacity building, and user-centred system design. The proposed framework aims to transition the current fragmented, paper-based systems into a resilient, digitised and intelligent archival management ecosystem capable of supporting the data demands of modern educational institutions.