Evaluating the Impact of Conversational AI Integration in ERP Systems: A Structural Equation Modelling Approach Using the U-CAI Architecture

Abstract

Enterprise Resource Planning (ERP) systems are core systems for integrating organisational processes, information resources and decision-making activities. However, the widespread adoption of ERP systems has not solved a long-standing usability problem: users are still faced with complex interfaces, extensive navigation structures and process-intensive workflows. Recent advances in Conversational Artificial Intelligence (AI) and Large Language Models (LLMs) present new opportunities to streamline enterprise interactions using natural language communication. ERP adoption, ERP implementation success, technology acceptance, and AI-enabled information systems have been widely studied in prior research. However, recent studies have begun emphasising the potential of conversational AI in the enterprise context. Yet, there is no empirical evidence on how conversational AI affects user behaviour, cognitive workload, task efficiency, and adoption in ERP systems under a single unified theoretical and mathematical framework. To bridge this gap, the present study proposes and empirically validates the Unified Conversational Artificial Intelligence (U-CAI) framework for conversational AI-enabled ERP environments by integrating the Technology Acceptance Model (TAM), the Unified Theory of Acceptance and Use of Technology (UTAUT), Cognitive Load Theory (CLT), and Human–Computer Interaction (HCI) principles to examine the relationships among Conversational AI Usability, Trust in AI Systems, Cognitive Load Reduction, ERP Task Efficiency, User Adoption Intention, and ERP User Experience. A quantitative research design based on survey data collected from 300 ERP users from different organisational sectors. The proposed hypotheses were tested using regression analysis, mediation analysis, moderation analysis and Structural Equation Modelling (SEM). The results indicate that Conversational AI Usability significantly enhances ERP Task Efficiency and reduces Cognitive Load, and Trust in AI Systems has a positive effect on User Adoption Intention. Cognitive Load Reduction partially mediates the effect of usability on efficiency, while ERP User Experience has a significant moderating effect on this relationship. Collectively, these results validate the U-CAI framework and show that conversational AI can improve ERP usability, reduce cognitive load, improve operational performance, and help users adopt them in today’s enterprise environments.