AI AND THE FUTURE OF PUBLIC SECTOR ERP: INTELLIGENT AUTOMATION BEYOND DATA ANALYTICS

Abstract

Enterprise Resource Planning (ERP) systems are foundational to the operations of public sector institutions, enabling the management of critical functions such as finance, procurement, human resources, and citizen services. Traditionally, these systems have been constrained by their reliance on structured data and deterministic processes, offering limited adaptability in the face of increasing complexity and evolving public expectations. With the advent of Artificial Intelligence (AI), a new frontier is emerging—one where ERP systems are no longer static repositories but intelligent platforms capable of autonomous decision-making, contextual understanding, and predictive intervention. This research explores the transformative role of AI in public sector ERP systems, focusing on intelligent automation beyond conventional data analytics. It investigates how technologies such as machine learning, natural language processing, and robotic process automation can be leveraged to optimize processes, reduce manual effort, and enhance responsiveness in government operations. The paper presents architectural models, real-world case studies, and comparative analyses to illustrate the tangible benefits and strategic potential of AI integration.

Furthermore, the study identifies key implementation challenges—ranging from legacy system integration and ethical considerations to skill shortages and regulatory constraints. It also outlines a roadmap for AI-enabled ERP transformation tailored to the unique needs of public sector environments. By advancing the discourse beyond analytics toward cognitive automation, this article contributes a forward-looking perspective on the future of ERP in the era of intelligent governance.