["Applied Psychology, Volume 75, Issue 4, August 2026. ", "\nAbstract\nArtificial intelligence (AI) is rapidly becoming a primary channel through which employees access information and solve problems at work. Drawing on media dependency theory, we theorize that workplace AI use exerts a suppressing effect on practitioners' job self‐efficacy in task‐focused achievement contexts. Specifically, AI use can directly bolster job self‐efficacy by facilitating task accomplishment. At the same time, frequent AI use may foster AI dependency, reducing employees' engagement in competence‐relevant cognitive work and, in turn, weakening mastery‐based confidence. Across a multi‐source, time‐lagged field study and a scenario experiment, results support this competing‐process account: workplace AI use showed a positive direct association with job self‐efficacy, whereas AI dependency carried a negative indirect effect, yielding a significant suppressing effect. We further identify proactive feedback to AI as a key boundary condition that attenuates the negative effect of AI dependency on job self‐efficacy and renders the suppressing effect nonsignificant at higher levels of feedback. This research clarifies how organizations can leverage AI for performance gains while safeguarding employees' perceived capability.\n"]