Workplace Digital Twin (WDT): Unleashing AI Workforce Twins for Next-Gen HR Management

Abstract

The changing landscape of workforce management requires a fundamental shift in how organizations oversee, enhance, and support their employees. Conventional HR systems often work in isolation, missing the intricate connections between employee well-being, team dynamics, leadership potential, and ethical standards. This paper introduces an AI-Powered Workforce Digital Twin (WDT)—a detailed, real-time simulation of an organization’s workforce that utilizes advanced artificial intelligence to transform HR decision-making. By developing digital twins of employees, our framework combines various AI subsystems, such as mental health monitoring, team chemistry forecasting, HR ethical auditing, shadow leadership identification, and workplace conflict detection and resolution. Using modern machine learning models especially sentiment analysis, and predictive analytics, we can get real-time, data-driven insights to boost workforce productivity and promote a healthier workplace culture. By integrating AI, workforce analytics, and HRM, this research presents a groundbreaking approach to creating intelligent, proactive, and ethical HR ecosystems. Our proposed model establishes a foundation for the future of AI- driven workforce management—where digital simulations enable organizations to make smarter, fairer, and more human-centered HR decisions.