Revolusi Rekrutmen Berbasis AI: Antara Efisiensi dan Jebakan Bias

The digital transformation of recruitment has significantly reshaped human resource management by accelerating hiring processes, standardizing candidate evaluation, and increasing organizational capacity to handle large applicant pools. Technology-driven recruitment systems offer notable efficiency gains through reduced recruitment time and operational costs while supporting strategic workforce planning. Despite these advantages, the growing reliance on automated selection mechanisms raises concerns related to bias, fairness, and ethical accountability. Bias embedded in historical data and system design may unintentionally reproduce structural inequalities and influence both decision quality and applicant perceptions. This study adopts a qualitative literature-based approach to critically examine the dual role of technology in recruitment, focusing on the tension between efficiency and justice. The findings indicate that fair and effective recruitment requires strong governance frameworks, transparent data management, human oversight in decision-making, and enhanced digital literacy among human resource practitioners. Integrating efficiency with ethical responsibility is essential for sustaining organizational competitiveness, trust, and legitimacy in an increasingly digital labor market.