<![CDATA[This study aims to analyze the effect of Generative Artificial Intelligence (AI) utilization on middle manager performance in the digital creative industry of Malang City using the Technology-to-Performance Chain (TPC) approach. Specifically, this study examines how Task Characteristics and Technology Characteristics influence Task-Technology Fit (TTF), and their subsequent impact on manager performance through Utilization as a mediating variable. The research method employed is quantitative cross-sectional. Data were collected via questionnaires from 182 middle managers and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that complex task characteristics and reliable AI technology characteristics significantly influence the formation of Task-Technology Fit. Furthermore, TTF is proven to have a positive and significant effect on middle manager performance, both directly and indirectly through utilization as a mediator. These findings indicate that the fit between Generative AI capabilities and managerial task requirements drives more intensive technology utilization, which ultimately enhances efficiency and decision-making quality.]]>
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