Is education and training delivering an AI-ready construction workforce? Evidence from AI deployment and training provision

Integration of AI for resolving the decade-long productivity issues of the construction industry is increasingly promoted, with reported claims of productivity gains, improvements in scheduling, site safety and predictive maintenance. However, whether the industry, specifically the workforce, is prepared and capable of executing the implementation, interpretation and governance of these applications is far less clear. Existing literature highlights the existence of capability gaps in the workforce but derives its evidence largely from academic literature rather than what firms actually deploy or what the education and training system actually provides. This study addresses this gap by conducting a comparative analysis of reported deployment of AI in the construction industry against capability supply.

The study executes a qualitative content analysis of publicly available documents on AI adoption and deployment by contractors, consultancies and public infrastructure agencies alongside professional training, VET training and university curricula in Australia. The AI deployment and capabilities are mapped across the lifecycle phases of projects and coded against an established eight-domain taxonomy of AI competencies.

The study maps the capabilities that AI deployment requires against those the training and education system is providing in Australia. The study contributes to academia and industry an evidence base for addressing the capability gap, and positions workforce readiness as a condition for a socially sustainable and equitable digital transition.