Sustainability assessment of construction DX training programs for local governments using large language model Gemini: A case study

Abstract

This study investigates the sustainability and business feasibility of Data Accumulator and Analyst (DAA) training programs aimed at promoting Construction DX in local governments. Utilizing the Large Language Model Gemini under Japan’s Cabinet Office SIP initiative, we extracted civil engineering expenditure data from municipal financial reports and simulated the impact of deploying DX-capable personnel. Results revealed a strong correlation between infrastructure scale and spending, alongside region-specific challenges such as high maintenance burdens per staff. Simulations demonstrated that strategic placement of DAA personnel enhances DX adoption and cost-effectiveness, supporting the viability of a paid training model. Additionally, Gemini enabled rapid, high-precision analysis by non- experts, facilitating data-driven policymaking. The DAA program presents a promising framework for advancing sustainable infrastructure through localized DX initiatives.