The use of algorithms to guide worker behavior, referred to as algorithmic control (AC), is increasingly prevalent in organizations. Despite its potential operational benefits, prior research indicates that workers often struggle with the opaque nature of such systems. Our research aims to explore how workers perceive, judge, and react to AC systems when exposed to two distinct facets of algorithmic transparency (AT): input and transformation AT. Through an experimental study with 121 participants, we provide empirical evidence that increased transparency about the algorithm’s transformation process significantly enhances workers’ perceived AT, which in turn positively impacts workers’ judgments and, ultimately, their continuance intention and acceptance of an AC system. In doing so, we provide practical recommendations for organizations to mitigate the adverse effects associated with algorithmic control.