This study introduces a toolset that uses OpenAI’s advanced text-generation model to extract and articulate descriptive insights from Enterprise Resource Planning (ERP) system data. The primary objective of this research is to augment the interpretability of complex data from ERP system, thereby streamlining decision-making processes and improving organizational efficiency. Recognizing a significant gap in the integration of AI-driven text generation with ERP systems, this paper addresses the challenge by demonstrating the development and application of an AI-based chat toolset. The toolset is designed to facilitate user interaction with ERP systems, enabling the retrieval of pertinent information without the traditional reliance on report generation or direct system access. Through a methodical approach, the research details the creation of the toolset that is precisely tailored to enhance information retrieval by seamlessly interfacing with the ERP system. The integration of the OpenAI model allows for the generation of precise and contextually relevant responses to user inquiries, effectively avoiding the need for manual report generation and system navigation. The paper outlines the critical steps involved in the development of this innovative toolset, including effective data extraction, preprocessing, and the establishment of a responsive chatbot functionality. The performance of the toolset is rigorously evaluated, showcasing its potential to significantly elevate user experience and productivity. The findings suggests implementation of such AI-powered chat toolsets can deliver substantial benefits to users navigating intricate data environments, empowering them with the ability to swiftly uncover information through intuitive natural language queries. Future research directions are proposed to explore the applicability of this AI-based chat toolset approach to other ERP systems, aiming to broaden its utility and scalability across diverse ERP platforms.