<![CDATA[The rapid proliferation of artificial intelligence (AI) in talent acquisition has fundamentally transformed personnel selection from an interpersonal evaluative process into a socio-technical decision system. For Generation Z (born late 1990s–early 2010s) entering the global workforce, this technological shift presents a profound behavioral paradox. As digital natives, Generation Z applicants expect modern, technology-enabled hiring workflows, yet empirical studies demonstrate that fully automated candidate screening, asynchronous video interviews (AVIs), and non-explainable decision algorithms elicit widespread algorithm aversion, feelings of de-individuation, and heightened perceived procedural injustice. Drawing on organizational justice theory, signaling theory, person-environment fit, social exchange theory, and psychological contract theory, this paper presents a systematic literature-based analysis of peer-reviewed empirical studies and meta-analyses published between 2022 and 2026. The findings synthesize how recruitment automation, candidate experience, perceived fairness, and process explainability influence candidate trust, organizational attractiveness, and post-hire workplace engagement. Results reveal that while algorithmic efficiency enhances processing speed and administrative reach, non-explainable AI tools undermine person-environment fit and re-architect psychological contracts from relational commitments to transactional exchanges. This structural shift triggers strategic candidate adaptations and downstream technostress. The paper concludes with a risk-calibrated framework for human-AI augmentation to preserve candidate trust, procedural justice, and sustained workplace engagement]]>
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