Nowadays, effective document management is crucial for enhancing organizational productivity, efficiency, and adaptability, but traditional document management systems often struggle with retrieval, accessibility, and workflow automation. Thus, the present research introduces an Automated Document Management System (ADMS) prototype that integrates ChatGPT as an intelligent assistant to enhance document processing. By using natural language processing (NLP) and machine learning, the system enables users to interact with documents through conversational queries, analysis, retrieval, and summarisation requests. The ChatGPT-powered assistant operates by creating small context sessions to dynamically analyse document content. These sessions extract key insights, highlight relevant sections, and generate summaries according to user queries. By maintaining context within each session, the assistant delivers accurate and relevant responses while ensuring continuity in the conversation. This approach not only improves document accessibility and usability but also enables the integration of other knowledge domains within an organization. To evaluate its effectiveness, the prototype is validated by 30 IT experts, who identify essential functionalities, strengths, and potential challenges. Their feedback provides key insights into areas such as accuracy, scalability, and security, guiding future improvements. This research aims to demonstrate how ChatGPT can optimise information handling and support decision-making, highlighting the revolutionary potential of AI-driven document management. By automating process and project definition and enhancing search capabilities, the system offers a scalable and intelligent solution for modern document workflows. Thus, Knowledge Management (KM) evolves to focus on contextual understanding, emphasises cohesive data integration, and expands the scope of knowledge creation and sharing and their influence on knowledge domains.
Dilyan Georgiev (2025) studied this question.