A Data-Driven Approach to Identify Potential AI Chatbots for Electrical Construction Contractors

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Authors: Anh D. Chau, Shanley Mastin, Juanpablo Palmas, Anna Koufakou, Long D. Nguyen
Cited by: 0
References: 5

Abstract

The electrical construction industry faces growing complexity in managing technical information and regulatory compliance. While AI chatbots have shown promise in various sectors, their application in electrical construction remains largely unexplored. This study uses a mixed-methods approach to identify and assess potential applications of custom-built AI chatbots for the industry. We analyzed 542 YouTube videos, yielding over 1,388 transcript pages, and conducted a pilot interview with a service electrician to uncover key field challenges. Leveraging GPT-4o and Claude 3.5 Sonnet, we identified eight thematic categories from the transcripts, with quality control and safety emerging as dominant concerns. The interview confirmed these findings and revealed additional challenges in code reference and communication. A prototype chatbot was developed to support electrical code inquiries and demonstrated improved jurisdiction-specific accuracy compared to general-purpose AI tools. This research contributes both theoretical understanding and a practical framework for implementing targeted AI solutions in specialized construction domains.

Fields of Study & Subjects

Artificial Intelligence Applications BIM and Construction Integration AI in Service Interactions

Publication details

Journal / source
ASCE International Conference on Computing in Civil Engineering (i3CE)
Pages
175–184
Publication date
28 January 2026