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In the current era of digital transformation, organizations are increasingly turning to Artificial Intelligence (AI) to enhance the precision and agility of managerial decisions. This study investigates how AI adoption within management accounting systems influences decision-making efficiency and managerial performance. Using survey data collected from managers and accountants in medium-to-large firms across Central Java, the research applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine the hypothesized relationships. The results reveal that AI adoption significantly improves decision-making efficiency, which in turn enhances managerial performance. Furthermore, leadership support strengthens the relationship between AI adoption and decision-making efficiency, indicating that human and organizational factors remain critical for realizing technological benefits. The findings contribute to management accounting literature by elucidating the mechanism through which AI technologies create managerial value specifically, by accelerating analytical processes and improving the quality of managerial judgments. Practically, the study suggests that firms should focus on leadership involvement, data governance, and employee training to ensure that AI systems complement, rather than replace, human judgment. Overall, this study highlights that successful AI adoption in management accounting is not merely a technical transition but a strategic and cultural evolution toward evidence-based decision-making.