<![CDATA[This study examines the practice of human-AI collaboration in recruitment decision-making within companies in Jakarta that utilize AI-based Applicant Tracking Systems (ATS). The growing adoption of artificial intelligence in human resource management has transformed recruitment processes into more data-driven, automated, and efficiency-oriented systems. While AI enhances the speed and consistency of candidate screening, concerns regarding algorithmic bias, transparency, and accountability remain significant. Therefore, the concept of human-in-the-loop becomes essential to ensure that managerial judgment remains central in final hiring decisions. This research employs a qualitative case study approach through in-depth interviews with HR practitioners who directly engage with AI-supported recruitment systems. The findings reveal that AI primarily functions as a decision-support tool that assists in initial candidate filtering and ranking. However, HR managers retain authority in evaluating contextual factors, cultural fit, and soft skills that cannot be fully captured by algorithmic assessment. The study highlights the importance of balancing algorithmic efficiency with human professional judgment to mitigate bias and maintain ethical accountability. These findings contribute to the literature on digital human resource management and provide practical insights for organizations integrating AI into recruitment strategies]]>
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