Marín Díaz, GabrielGalán Hernández, José JavierKerre, Etienne E.Lu, JieMartínez, LuisLi, TianruiMontero, JavierFlores-Vidal, Pablo2026-01-122026-01-122024-07-21Díaz Marín, G., & Galán Hernández, J. J. Decoding Employee Attrition: A Unified Approach with XAI and AHP. In Intelligent Management of Data and Information in Decision Making (pp. 367–375). https://doi.org/10.1142/9789811294631_00462972-446510.1142/13882https://hdl.handle.net/20.500.14352/129925In 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.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/conference paperhttps://www.worldscientific.com/worldscibooks/10.1142/13882https://www.worldscientific.com/doi/10.1142/9789811294631_0046open access004.8519.226303.4004.6331XAIartificial intelligenceAHPhuman resourcestalent attractionInteligencia artificial (Informática)Técnicas de Investigación SocialTeoría de la decisiónTrabajo1203.04 Inteligencia Artificial1209.04 Teoría y Proceso de decisión5311.04 Organización de Recursos Humanos1209.03 Análisis de Datos