Can Large Language Model Predict Employee Atrition?

Abstract

Employee attrition is a critical issue faced by organizations, with significant costs associated with turnover and the loss of valuable talent. Traditional methods for predicting attrition often rely on statistical techniques that, while useful, struggle to capture the com- plexity of modern workforces. Recent advancements in machine learning (ML) have provided more accurate, scalable solutions, al- lowing organizations to analyze diverse data points and predict attrition with greater precision. However, the emergence of large language models (LLMs) has opened new possibilities in human resource management by offering the ability to interpret contextual information from employee communications and detect subtle cues related to turnover.

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