From Recruitment to Retention: AI Tools for Human Resource Decision-Making

От найма до удержания: инструменты искусственного интеллекта для принятия решений в управлении человеческими ресурсами
Mitra Madanchian
2024-12-16

AI in human resourcesapplicant tracking systemsautomated onboardingindividualized trainingpredictive analytics
HR decision-making is changing as a result of artificial intelligence (AI), especially in the areas of hiring, onboarding, and retention. This study examines the use of AI tools throughout the lifecycle of an employee, emphasizing how they enhance the effectiveness, customization, and scalability of HR procedures. These solutions streamline employee setup, learning, and documentation. They range from AI-driven applicant tracking systems (ATSs) for applicant selection to AI-powered platforms for automated onboarding and individualized training. Predictive analytics also helps retention and performance monitoring plans, which lowers turnover, but issues such as bias, data privacy, and ethical problems must be carefully considered. This paper addresses the limitations and future directions of AI while examining its disruptive potential in HR.
1
AI adoption in HR raises unresolved concerns about algorithmic bias, data privacy, ethics, limitations, and future governance.
2
AI tools can support HR decision-making across the employee lifecycle, including recruitment, onboarding, training, performance monitoring, and retention.
3
AI-driven applicant tracking systems streamline applicant selection, while automated platforms improve onboarding and documentation processes.
4
AI-powered individualized training solutions enhance the customization and scalability of employee learning and development.
5
Predictive analytics can support retention and performance-monitoring strategies and may reduce employee turnover.

AI tools used throughout the employee lifecycle for human resource decision-making

The effectiveness, customization, scalability, and ethical implications of AI-assisted hiring, onboarding, training, retention, and performance monitoring

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2024-12-16
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Mitra Madanchian
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