Abstract
The integration of artificial intelligence (AI) is reshaping recruitment by automating resume screening, candidate evaluation, and workforce planning. AI tools reduce costs and manual workload while improving decision-making through predictive analytics and natural language processing. This study compares traditional workflows with AI-enhanced applicant tracking systems (ATS) to show how AI improves hiring accuracy and supports long-term talent strategies. Yet, these benefits raise ethical and operational concerns, including bias, privacy risks, and compliance with the EU AI Act and GDPR. Drawing on empirical evidence, the paper evaluates these challenges and proposes mitigation strategies such as adversarial debiasing, federated learning, and bias audits. Finally, it advances a hybrid model that combines AI efficiency with human oversight, ensuring fairness, transparency, and sound judgment in recruitment.