Role of Generative Artificial Intelligence in Transforming Construction Safety Training

Abstract

The construction industry continues to face high levels of accidents despite the use of various safety training approaches, highlighting the need for more effective and responsive methods. This study examines the role of Generative Artificial Intelligence (GenAI) in potentially improving construction safety training by exploring the development of training practices and identifying the shortcomings of existing approaches. A systematic literature review (SLR) was conducted to analyse safety training methods and emerging GenAI applications, followed by validation interviews with industry experts in South Australia to ensure practical relevance. Emergent findings show that safety training has progressed through three main stages: instructor-led, digital and GenAI-enabled. However, instructor-led and digital approaches remain limited by non-interactive learning, limited flexibility to different learner needs, lack of real-time feedback and weak alignment with actual site conditions. In contrast, GenAI offers opportunities to support more interactive, personalised and context-aware training through technologies such as large language models (LLMs), adaptive learning systems, computer vision and scenario generation. Despite these benefits, significant challenges related to data quality, system reliability, ethical concerns and organisational readiness continue to affect implementation. Based on these findings, the study develops an integrated framework that links training evolution, key challenges and GenAI capabilities, providing practical guidance to improve safety training in construction.