Decoding employee attrition: a unified approach with XAI and AHP

Abstract

In the face of escalating employee attrition challenges, organizations are increasingly relying on artificial intelligence (AI) to predict and address turnover. This chapter explores the application of explainable AI (XAI) to identify potential employee turnover, analyzing its impact on organizational productivity and stability. The second section focuses on AI techniques that leverage historical data to forecast attrition, enabling proactive interventions. The third part introduces XAI to enhance model transparency, providing HR professionals with deeper insights to develop targeted retention strategies aligned with individual employee needs. Integrating the Analytic Hierarchy Process (AHP) model becomes imperative to assign weights to criteria identified by AI as significant. This incorporation aims to introduce the human factor into decision-making.