TDNet Discover

The purpose of this study is to examine how artificial intelligence (AI) influences accounting workflows, efficiency, and professional expectations among accounting personnel within higher education, with a focused case analysis of Cleveland State Community College (CSCC). Guided by the Task–Technology Fit (TTF) framework and the Technology Acceptance Model (TAM), the study explores the alignment between task demands, system capabilities, and user perceptions. The problem of practice is that AI-enabled features in higher education accounting systems remain significantly underutilized, resulting in manual redundancies, inefficiencies, and inconsistent workflow practices across departments. CSCC provides an ideal setting for this investigation due to its reliance on enterprise systems such as Banner, Jaggaer, and Spend Clarity, where AI functionality exists but is not fully leveraged by accounting staff. Data for this mixed-methods action research study will be collected through employee surveys, semistructured interviews, workflow observations, and documentation analysis. Quantitative survey data will measure AI usage patterns, perceived usefulness, ease of use, and workflow efficiency, while qualitative interviews and observations will capture lived experiences, contextual barriers, and training needs. The analysis will include descriptive statistics, cross-tab inference, and thematic coding aligned to TTF and TAM constructs to triangulate findings across data sources. It is expected that the findings will support the development of targeted recommendations for improving workflow efficiency, enhancing staff confidence in AI tools, and strengthening institutional strategies for technology integration.