Enhancing Work Efficiency and Learning Effectiveness with Generative AI Chatbots in Civil Engineering

Abstract

In the civil engineering and construction industry, generative AI chatbots can significantly streamline tasks such as report creation and safety activities. However, relying on AI may reduce opportunities for human learning and skill development. This paper proposes an evaluation method to balance AI-driven efficiency with human capability growth. We developed three chatbots to support reporting, safety activities, and root cause analysis, and present a framework to measure both productivity and learning outcomes through user logs and workplace performance. Our findings suggest that properly designed AI-assisted tools can enhance efficiency and simultaneously foster skill improvement.