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
2024-12-16
SCID: 54.1/597kk22f
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AI in human resourcesapplicant tracking systemsautomated onboardingindividualized trainingpredictive analytics
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Abstract (AI)
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.
Key Findings
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.
Research Object
AI tools used throughout the employee lifecycle for human resource decision-making
Research Subject
The effectiveness, customization, scalability, and ethical implications of AI-assisted hiring, onboarding, training, retention, and performance monitoring
Publication Details
Publication Date
2024-12-16
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