Measuring AI Fluency Among Business Students: A Technology Acceptance Model Approach for Digital Transformation in Indonesian Higher Education
Abstract
This study examines AI fluency among business students in Indonesian higher education by extending the Technology Acceptance Model (TAM) with AI literacy, digital self-efficacy, and institutional support. Using a quantitative survey of 385 business students at Universitas Bunda Mulia, data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results show that AI literacy significantly predicts perceived usefulness (beta = 0.521, p < 0.001), perceived ease of use (beta = 0.486, p < 0.001), and behavioral intention to use AI tools (beta = 0.412, p < 0.001). Attitude also predicts behavioral intention (beta = 0.328, p < 0.001), while digital self-efficacy strengthens the relationship between AI literacy and behavioral intention (beta = 0.256, p < 0.001). Institutional support positively influences both perceived usefulness and perceived ease of use, although with smaller effect sizes. The model explains 52.3% of the variance in behavioral intention. The study contributes by clarifying the conceptual boundary between AI literacy and AI fluency within an extended TAM framework and by showing how individual confidence and institutional support condition AI adoption among Indonesian business students. Because the study uses cross-sectional self-reported data from a single institution, the findings should be interpreted as evidence of perceived and intention-based AI fluency rather than objective AI performance or causal development over time.
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