Prediction of Risks Using Artificial Intelligence in Digitalized Human Resource Management

Artificial intelligence (AI) and human resource management (HRM) are changing significantly as firms move into the digital era. This study explores the potential of AI in predicting and mitigating risks within digitalized HRM systems. Leveraging machine learning algorithms and predictive analytics, the research focuses on developing a proactive framework for identifying and addressing potential risks associated with various HR functions. Initially, the research created a conceptual model for the system, specified the elements of a digital HRM system, and built a risk management plan. Next, by deftly combining the risk event graph and digital HRM risk event chains, this research presented a unique approach for risk prediction in the digital HRM system. The examination then, at that point, investigated the design and central ideas of the risk event representation layer, risk event chain module, risk event graph module, and attention fusion module. Not to mention, test results showed that the suggested approach has clear benefits for accurately and consistently predicting digital HRM risk.

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