Abstract
The rapid advancement of Artificial Intelligence (AI) is transforming Human Resource Management (HRM) from a primarily administrative function into a data-driven strategic partner. In the post-pandemic environment, organizations in the Information Technology Enabled Services (ITeS) sector have accelerated the adoption of AI-based systems to enhance workforce planning, decision-making quality, and operational efficiency. However, despite this growing adoption, the determinants of AI acceptance in HRM remain insufficiently understood, particularly in emerging economies. This study examines AI adoption in HRM using an integrated framework that combines the Technology Acceptance Model (TAM) and the Technology–Organization–Environment (TOE) model, with trust as a mediating factor. Primary data were collected from 421 HR managers working in ITeS organizations in the Delhi National Capital Region (NCR) through a structured questionnaire. The data were analyzed using Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that technological factors (relative advantage, complexity, security, and cost effectiveness), organizational factors (top management support and readiness), environmental factors (competitive pressure), and trust dimensions (reliability and credibility) significantly influence perceived usefulness and perceived ease of use of AI systems. Furthermore, AI capabilities including machine learning, natural language processing, predictive analytics, automation, augmentation, and bias detection have a significant positive impact on HRM practices. Bias detection and predictive analytics demonstrate the strongest effects on HR outcomes. The study contributes to the literature by providing an empirically validated TAM–TOE–Trust framework for understanding AI adoption in HRM. It also offers practical implications for HR leaders, technology developers, and policymakers to support responsible and effective integration of AI in the ITeS sector.
