<![CDATA[The rapid integration of Human Resource Technology (HR Tech)—encompassing Artificial Intelligence (AI) resume screening, Applicant Tracking Systems (ATS), conversational chatbots, and predictive candidate assessment—has fundamentally transformed contemporary talent acquisition. This systematic critical review synthesizes empirical and theoretical literature published between 2021 and 2026 (N=16) to evaluate how advanced HR technology enhances recruitment efficiency and strategic talent acquisition outcomes. Adhering to PRISMA 2020 guidelines, this investigation examines key operational mechanisms, including screening friction reduction, candidate experience optimization, and algorithmic bias mitigation. Findings demonstrate that AI-driven automated screening and ATS workflows reduce time-to-hire by 38% to 52% and lower cost-per-hire by up to 41%, while conversational AI chatbots enhance candidate engagement. However, algorithmic opacity, procedural fairness concerns, and systemic training data biases emerge as major boundary conditions that risk eroding applicant trust and quality-of-hire. Based on a meta-synthesized structural equation model, this study proposes a multi-level governance framework that integrates human-in-the-loop oversight, continuous algorithmic auditing, and ethical compliance to maximize talent acquisition performance in the digital era.]]>
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