[2603.03302] Developing an AI Assistant for Knowledge Management and Workforce Training in State DOTs

Computer Science > Computation and Language arXiv:2603.03302 (cs) [Submitted on 7 Feb 2026] Title:Developing an AI Assistant for Knowledge Management and Workforce Training in State DOTs Authors:Divija Amaram, Lu Gao, Gowtham Reddy Gudla, Tejaswini Sanjay Katale View a PDF of the paper titled Developing an AI Assistant for Knowledge Management and Workforce Training in State DOTs, by Divija Amaram and 3 other authors View PDF HTML (experimental) Abstract:Effective knowledge management is critical for preserving institutional expertise and improving the efficiency of workforce training in state transportation agencies. Traditional approaches, such as static documentation, classroom-based instruction, and informal mentorship, often lead to fragmented knowledge transfer, inefficiencies, and the gradual loss of expertise as senior engineers retire. Moreover, given the enormous volume of technical manuals, guidelines, and research reports maintained by these agencies, it is increasingly challenging for engineers to locate relevant information quickly and accurately when solving field problems or preparing for training tasks. These limitations hinder timely decision-making and create steep learning curves for new personnel in maintenance and construction operations. To address these challenges, this paper proposes a Retrieval-Augmented Generation (RAG) framework with a multi-agent architecture to support knowledge management and decision making. The system integrates structured ...