DEVELOPING A PRIORITY MODEL FOR THE MATURITY OF AI-DRIVEN ERP INTEGRATION IN SRI LANKAN CONTEXT

Abstract

The integration of Artificial Intelligence (AI) with Enterprise Resource Planning (ERP) systems is emerging as a critical driver of digital transformation, enabling organizations to enhance operational efficiency, optimize decision-making processes, and maintain a competitive edge. Despite its potential, the successful integration of AI into ERP systems is influenced by a variety of organizational, technological, and leadership factors, which can differ significantly across regions and industries. This study investigates the key factors affecting AI-ERP integration within the Sri Lankan business environment, aiming to develop a comprehensive priority model that reflects the maturity of AI integration in this specific context. A thorough literature review was conducted to identify relevant success factors, which were then validated through consultations with industry experts. These validated factors were incorporated into a structured questionnaire distributed to a targeted sample population within the Sri Lankan corporate sector. The collected data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to determine the significance and impact of each factor. Based on the analysis, a five-level priority model was developed to represent the maturity stages of AI-ERP integration. The model provides a structured framework that highlights the most critical areas organizations should focus on to ensure successful integration. This research offers valuable insights for Sri Lankan enterprises seeking to adopt AI-enabled ERP systems and provides a strategic benchmark for assessing integration readiness. Furthermore, the findings serve as a foundation for future academic research and contribute practical implications for decision-makers and technology leaders in developing effective AI-ERP integration strategies.