Artificial Intelligence (AI) has become increasingly integrated into Human Resource Management, particularly in employee recruitment, as organizations seek to improve hiring effectiveness, reduce recruitment time, and enhance the overall quality of recruitment decisions. This study aims to examine the impact of AI-assisted recruitment on employee recruitment quality. A quantitative research approach was employed using a cross-sectional survey of 250 Human Resource (HR) professionals working in digital companies, technology firms, service organizations, and startups that have implemented AI-assisted recruitment systems. Data were collected through a structured questionnaire using a five-point Likert scale and analyzed using Partial Least Squares Structural Equation Modeling (SEM-PLS). The findings reveal that AI-assisted recruitment has a positive and statistically significant effect on employee recruitment quality. Specifically, AI improves candidate-job matching, enhances hiring accuracy, increases recruitment efficiency, strengthens hiring effectiveness, and reduces recruiters' manual workload by automating repetitive administrative tasks. These findings indicate that AI serves as an effective decision-support tool that enables organizations to identify qualified candidates more consistently and efficiently. The study concludes that AI-assisted recruitment can substantially improve employee recruitment quality when implemented responsibly through appropriate human oversight, ethical governance, algorithm transparency, and continuous performance evaluation, thereby supporting more effective and sustainable talent acquisition strategies in the digital era.
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