AI-Enabled HRM: Rethinking Talent Acquisition and Employee Performance in the Era of Digital Work

Abstract

The rapid expansion of digital work has accelerated the adoption of artificial intelligence (AI) within Human Resource Management (HRM), particularly in talent acquisition and employee performance management. This study aims to examine the role of AI-enabled HRM in enhancing talent acquisition effectiveness and employee performance in the era of digital work. Using a quantitative approach, data were collected through a structured questionnaire from 230 employees and HR practitioners working in organizations that have adopted digital work practices. Data analysis was conducted using Structural Equation Modeling (SEM) to assess the measurement and structural models. The results indicate that AI-enabled HRM has a positive and significant effect on talent acquisition and employee performance, highlighting the strategic value of AI in improving recruitment accuracy, performance analytics, and data-driven decision-making. The findings further demonstrate that AI-enabled HRM facilitates the transformation of HR from an administrative function into a strategic partner within organizations. This study contributes to the HRM and digital transformation literature by providing empirical evidence on the strategic implications of AI-enabled HRM, while offering practical insights for organizations seeking to adopt AI ethically and effectively in managing human resources in digital work environments.