Abstract
Enterprise resource planning (ERP) systems are fundamental to modern business operations, yet traditional ERP solutions demand extensive manual configuration, maintenance, and monitoring. This paper proposes a novel AI-driven autonomous ERP framework that leverages machine learning (ML), process mining, and large language models (LLMs) to optimize enterprise workflows in real time.
In the context of engineering management, the framework introduces self-learning modules that continuously adapt to business trends, user behavior, and operational inefficiencies, reducing human intervention while enhancing efficiency, security, and scalability. This paper outlines the architecture, key components, implementation challenges, and the managerial impact of autonomous ERP systems.