Artificial Intelligence and the Future Construction Workforce: A Qualitative Study of Emerging Skill Demands

Abstract

The U.S. construction industry is in a transitional phase characterized by the gradual yet accelerating integration of digital technologies across both field and administrative operations. This transformation is occurring amidst acute skilled labor shortages and an aging workforce, compelling firms to explore automation and artificial intelligence (AI) systems to enhance productivity, efficiency, and safety. While most existing research on AI in construction largely prioritizes technological innovation, the corresponding shifts in workforce skill demands remain under-explored. This qualitative study seeks to address this gap by examining the anticipated changes in workforce competencies resulting from the adoption of AI-enabled tools in the construction industry. Based on six in-depth semi-structured interviews with construction experts engaged in AI implementation, the study investigates emerging workforce competencies and projected role shifts across short and mid-term timeframe. The findings include three primary skill competency categories: (1) AI-enabled operational proficiency: referring to the ability to work effectively with technologies such as drones, robotic equipment, and predictive analytics tools; (2) analytical interpretation: encompassing the capacity to critically engage with AI-generated data across functions such as scheduling, risk assessment, and cost management; and (3) integrated digital-trade fluency: which captures the intersection of technological literacy and domain-specific construction expertise. This study contributes to the body of knowledge by understanding the construction workforce transformation and emerging competencies essential for sustained adaptability of AI in the construction industry. These preliminary findings form part of a broader ongoing research study involving over twenty industry interviews, which will inform a forthcoming peer-reviewed journal article.